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CycPeptMPDB: A Comprehensive Database of Membrane Permeability of Cyclic Peptides
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  • Jianan Li
    Jianan Li
    Department of Computer Science, School of Computing, Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8550, Japan
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    Orcidhttps://orcid.org/0000-0002-9004-5485
  • Keisuke Yanagisawa
    Keisuke Yanagisawa
    Department of Computer Science, School of Computing, Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8550, Japan
    Middle-Molecule IT-based Drug Discovery Laboratory (MIDL), Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8550, Japan
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    Orcidhttps://orcid.org/0000-0003-0224-0035
  • Masatake Sugita
    Masatake Sugita
    Department of Computer Science, School of Computing, Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8550, Japan
    Middle-Molecule IT-based Drug Discovery Laboratory (MIDL), Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8550, Japan
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    Orcidhttps://orcid.org/0000-0002-6298-4055
  • Takuya Fujie
    Takuya Fujie
    Department of Computer Science, School of Computing, Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8550, Japan
    Middle-Molecule IT-based Drug Discovery Laboratory (MIDL), Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8550, Japan
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    Orcidhttps://orcid.org/0000-0003-2103-6195
  • Masahito Ohue
    Masahito Ohue
    Department of Computer Science, School of Computing, Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8550, Japan
    Middle-Molecule IT-based Drug Discovery Laboratory (MIDL), Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8550, Japan
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    Orcidhttps://orcid.org/0000-0002-0120-1643
  • Yutaka Akiyama*
    Yutaka Akiyama
    Department of Computer Science, School of Computing, Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8550, Japan
    Middle-Molecule IT-based Drug Discovery Laboratory (MIDL), Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8550, Japan
    *E-mail: [email protected]
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    Orcidhttps://orcid.org/0000-0003-2863-8703
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Journal of Chemical Information and Modeling

Cite this: J. Chem. Inf. Model. 2023, 63, 7, 2240–2250
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https://doi.org/10.1021/acs.jcim.2c01573
Published March 17, 2023

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Abstract

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Recently, cyclic peptides have been considered breakthrough drugs because they can interact with “undruggable” targets such as intracellular protein–protein interactions. Membrane permeability is an essential indicator of oral bioavailability and intracellular targeting, and the development of membrane-permeable peptides is a bottleneck in cyclic peptide drug discovery. Although many experimental data on membrane permeability of cyclic peptides have been reported, a comprehensive database is not yet available. A comprehensive membrane permeability database is essential for developing computational methods for cyclic peptide drug design. In this study, we constructed CycPeptMPDB, the first web-accessible database of cyclic peptide membrane permeability. We collected information on a total of 7334 cyclic peptides, including the structure and experimentally measured membrane permeability, from 45 published papers and 2 patents from pharmaceutical companies. To unambiguously represent cyclic peptides larger than small molecules, we used the hierarchical editing language for macromolecules notation to generate a uniform sequence representation of peptides. In addition to data storage, CycPeptMPDB provides several supporting functions such as online data visualization, data analysis, and downloading. CycPeptMPDB is expected to be a valuable platform to support membrane permeability research on cyclic peptides. CycPeptMPDB can be freely accessed at http://cycpeptmpdb.com.

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Introduction

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The average costs associated with developing a new drug from discovery to market far exceed one billion dollars, and the process can take more than 12 years. (1) One of the difficulties is the decreasing number of targets for conventional small-molecule and antibody drugs. It has been reported that approximately 80% of all disease-relevant human proteins, including those involved in intracellular protein–protein interactions (PPIs), cannot be tackled by conventional small-molecule drugs and antibody drugs. (2) Cyclic peptides have recently emerged as a promising pharmaceutical modality because they can access the targets which have traditionally been considered “undruggable.” Cyclic peptides exhibit several pharmacological characteristics that distinguish them from other classes of therapeutic molecules. (3,4) For example, cyclic peptide drugs have a broader interaction surface than small-molecule drugs and thus may function as inhibitors with high affinity and selectivity for PPIs. Moreover, these drugs can be produced relatively inexpensively compared to antibody drugs due to their synthetic accessibility. Previously, cyclic peptide drugs were primarily natural peptides or mimics of those peptides. (5) The random nonstandard peptides integrated discovery (RaPID) system has made it possible to synthesize a large number of cyclic peptides from an extremely diverse amino acid library and quickly select strong binders against arbitrarily chosen therapeutic targets. (6) Using this approach, numerous research teams and pharmaceutical companies are actively engaged in cyclic peptide drug discovery. Currently, at least one cyclic peptide is approved for clinical use every year on average. (7)
However, the cell membrane permeabilities of common cyclic peptides are lower than the desired range for drugs, which severely limits their biological applicability. (8) Cell membrane permeability is one of the most important indicators for assessing oral bioavailability and the possibility of intracellular targeting. In general, relatively large cyclic peptides exceeding 10 amino acid residues have high target affinity; however, they tend to have low membrane permeability due to their large size. Although cyclic peptides have a variety of membrane permeation mechanisms, passive diffusion driven by differences in concentration is one of the most prevalent mechanisms. (9) Even for passive diffusion, the process by which cyclic peptides permeate membranes is not well understood. In contrast to linear peptides, many cyclic peptides have an environment-dependent property called the “chameleonic” property, namely, the ability to change their molecular conformation and hydrophobicity in response to the surrounding environment. These chameleonic cyclic peptides prefer an “open” conformation in aqueous environments, where the polar groups are exposed to the outside and interact with water molecules to enhance water solubility, and a “closed” conformation in hydrophobic environments, where the polar groups are shielded with intramolecular hydrogen bonds or lipophilic side chains, leading to improved membrane permeability. (10−12) Therefore, the most common strategy to increase membrane permeability has been to allow cyclic peptides to have a “closed” structure inside the cell membrane by shielding the exposed NH group with backbone N-methylation. (13,14) In addition, some strategies have been tested to improve membrane permeability by amide-to-ester substitution (8) or changing the structure of the side chain to form an intramolecular hydrogen bond with the main chain. (15)
In the early stages of drug development, it is important to select candidate compounds with high membrane permeability; however, it is a costly process to randomly measure large numbers of peptides using biochemical assays such as the parallel artificial membrane permeability assay (PAMPA). Hence, a rapid computational method for predicting membrane permeability is required. Computational approaches for predicting the permeability of cyclic peptides have primarily been developed on the basis of molecular dynamics (MD) simulation. (16−18) Most MD research involves identifying conformations in aqueous solutions or organic solvents. Furthermore, there are complex studies simulating the membrane permeation process of cyclic peptides across a lipid bilayer. (19,20) Cyclic peptides tend to exist in various conformations, resulting in slow conformational transitions relative to simulation time scales. (18) As a result, many accelerated sampling techniques have been used, such as replica exchange MD (REMD). (21) In addition, analyzing simulation results by methods such as Markov state models (MSMs) can provide information on the behavior of cyclic peptides that are important for elucidating the mechanism of membrane permeation and structural optimization to increase membrane permeability. (22) However, the computational cost of the MD simulation method is still high.
In contrast to previously used methods, machine learning-based prediction methods can provide rapid predictions. However, previous reports using machine learning prediction methods did not yield a reliable level of generalization performance due to insufficient training data. (23,24) For instance, Digiesi et al. used 62 cyclic hexapeptides that have very similar structures to each other. (23) The topological polar surface area (TPSA) of these peptides ranged from approximately 150 to 250 Å2, which could only cover a very narrow chemical space. The lack of available databases that collect structurally diverse cyclic peptides is a major reason for poor generalization performance and is currently the greatest obstacle to developing comprehensive machine learning predictions. The combinations of amino acids that comprise cyclic peptides are numerous; therefore, the chemical space of possible cyclic peptides is very large. Furthermore, even a single residue change in the amino acid sequence can lead to drastic changes in membrane permeability. (25) Most studies using the available data fixed the majority of structures and measured changes in membrane permeability with very few residue changes. (22,26) Therefore, building a machine learning prediction model with high generalization performance requires a large amount of structurally diverse training data collected from a larger body of publications than employed in previous studies.
In this study, we constructed CycPeptMPDB, a comprehensive membrane permeability database for cyclic peptides with the aim of developing a machine learning-based prediction model and a computational method for cyclic peptide drug design. Because several previous publications reported various measurement experiments for the permeability data, information such as the measurement experiment system was recorded. We generated basic 2D SMILES representations and 3D structures (not crystal structures but computationally generated conformations) of cyclic peptides. Furthermore, to unambiguously represent cyclic peptides, we organized the sequence information from each source and unified the name of the monomer (substructure, such as the residue). Then, we used the hierarchical editing language for macromolecules (HELM) notation to generate sequence representations for all peptides.

Methods

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Overview of CycPeptMPDB Framework

As shown in Figure 1, CycPeptMPDB is a comprehensive database recording the membrane permeability of cyclic peptides based on data obtained from published papers and pharmaceutical patents. It mainly contains two types of data for cyclic peptides: (1) property information, i.e., experimental values of membrane permeability and physical quantities such as LogP (an index of lipophilicity) estimated from chemical structure, and (2) chemical structure information, i.e., sequence information described by HELM and monomers as partial structures constituting the cyclic peptides. CycPeptMPDB provides several functions such as data storage, statistics and visualization, searching and analysis, and downloading.

Figure 1

Figure 1. Basic framework of CycPeptMPDB. CycPeptMPDB data were collected from published papers and patents of pharmaceutical companies and then manually inspected. Information in various formats was deposited into a PostgreSQL-based database for visualization, downloading, and other web-based functions.

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Data Collection

We collected a total of 7334 structurally diverse cyclic peptide data points (the number of peptides including duplicated structures from all publication sources was 7451) and their measured membrane permeability from 45 published papers and 2 patents from pharmaceutical companies. The source list of CycPeptMPDB is shown in the Table S1. Membrane permeability in CycPeptMPDB was expressed as a log-scaled value LogPexp. For peptides whose membrane permeability could not be measured due to the detection limit, etc., LogPexp was set to the minimum value, −10.0 (1.0 × 10–10 cm/s, detailed records such as the detection limit can be viewed on the peptide detail page). The structures of peptides were recorded in CycPeptMPDB using the SMILES notation. Structural errors in the original publication were corrected (for example, when the SMILES structure attached to the publication differs from the sequence described in the publication, the structure was corrected based on the sequence information). When there was a new source directly citing the membrane permeability values of the old source, the number of these data was counted only in the old source. As shown in Table S1, most previously reported studies included a relatively small number of peptides, with only six publications reporting on over 100 peptides. In addition, as mentioned above, most of the publications deal with structurally similar cyclic peptides; therefore, the molecular weight range of peptides reported in a single paper is relatively narrow. By collecting more than 40 publications, we were able to build a database of cyclic peptides covering a wide range of molecular weights (from 342.4 to 1777.7) and TPSA (from 73.0 to 702.0 Å2). Molecular weight and TPSA were the MolWt and TPSA descriptor calculated by RDKit software, respectively. In the selected publications, there were 6941 measurements by PAMPA, 649 measurements by Caco-2 assay, 40 measurements by Madin-Darby canine kidney (MDCK) assay, and 186 measurements by Ralph Russ canine kidney (RRCK) assay. All measured values were recorded when measurements obtained by multiple assays were reported in a single publication. Of all identified peptides, the membrane permeability measurements of 365 peptides were determined using two different assays. When a peptide was measured by two assays in a single publication, the permeability of the assay with more data was used as the representative membrane permeability measurement. If the permeabilities from both assays were similar, the representative value was determined according to the following assay rank: (1) PAMPA, (2) Caco-2, (3) RRCK, and (4) MDCK. Furthermore, a detailed description of the assay protocol used in each study was also recorded as experimental conditions such as reaction time and initial concentration affect membrane permeability measurements.
Moreover, to improve the readability of the list display, collected cyclic peptides were classified into two types by membrane permeability (Figure 2). Cyclic peptides with LogPexp higher than or equal to −6.00 (1.0 × 10–6cm/s) are generally considered to have good permeability and were classified as high (5113 peptides). Conversely, cyclic peptides with LogPexp below −6.00 were classified as low (2338 peptides).

Figure 2

Figure 2. Permeability (LogPexp) distribution of all peptides. The background color of the high permeability range is yellow, and the background color of the low permeability range is green.

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3D Structure Generation of Cyclic Peptides

Chemical structural information on the collected cyclic peptides was recorded in SMILES notation. Additionally, as conformation generation for cyclic peptides is computationally expensive, we generated the 3D structure of each cyclic peptide using RDKit software (version 2020.09.1) allowing users to quickly start relevant research. We generated 5000 conformations per peptide and removed redundant conformations with RMSD less than 1.0 Å. Next, the structure optimization of each conformation was performed using the UFF force field, and the top structure with the lowest potential energy was selected. This approach provided a computationally efficient way to obtain the 3D structure of cyclic peptides. However, it should be noted that the minimum energy conformation obtained by molecular mechanics force fields may not necessarily reflect the true conformations of the peptides in biological systems. Furthermore, most peptides are likely to populate conformational ensembles rather than a single conformation. The 3D structure of the cyclic peptide can be viewed online and downloaded in SDF format.

Sequence Representation of Cyclic Peptides by HELM

Cyclic peptides are relatively large compared to small molecules, and appropriate sequence representation is essential for good readability. Therefore, we used the HELM notation to generate a unified sequence representation of collected cyclic peptides. HELM can hierarchically represent complex structures with relatively high molecular weights, such as antisense oligonucleotides, short interference RNAs, peptides, proteins, and antibody drug conjugates. (27) HELM consists of four level hierarchies: complex polymer, simple polymer, monomer, and atom (Figure 3(A)). First, a complex polymer expresses information about the chemical structure of the entire macromolecule. Its components are simple polymers and their connections (including hydrogen bonds and attributes). Second, a simple polymer is composed of monomers of the same polymer type. A simple polymer is defined as a single linear chain; branching and cycling structures are not covered in this hierarchy. Certain polymer types have explicit rules for connections between monomers, and the position and rules of connections can express the direction of monomer sequences (e.g., PEPTIDE notation represents amino acid sequences from N-terminus to C-terminus). Moreover, monomers are composed of atoms and bonds and can be represented in formats such as Molfile and CXSMILES (Figure 3(B), Chemaxon Extended SMILES). Each monomer was given a unique symbol similar to the amino acid code represented in the peptide sequences (e.g., A, G). Here, the definition of monomer also includes the positions of its connections (i.e., attachment points). When describing linear peptides, the original HELM definition dictates that monomers are connected by peptide bonds. The attachment point R1 is defined as the N atom of the amino group, and R2 is defined as the C atom of the carboxyl group (the attachment points after R3 is the branch of the side chain). R1 and R2 in the terminal can only be used to form the main chain of the linear peptide (R1 and R3, R2 and R3 can form a ring). Contrary to the original definition, the N-terminus and C-terminus of linear peptides are often connected in the case of cyclic peptides. Therefore, in this study, N-terminal R1 and C-terminal R2 were able to be used to form a ring (like 1:R1–6:R2 in Figure 3(A), HELM in PubChem and ChEMBL databases is also like our definition). In addition, the O atom changed from the N atom was also set as R1 because there were many cyclic peptides with amide-to-ester substitutions.

Figure 3

Figure 3. (A) Example of HELM notation (PEPTIDE1[dL].[dL].L.[dL].P.Y$PEPTIDE1, PEPTIDE1,1:R1-6:R2$$$) and its constituent parts in this study. If the simple polymer is a peptide, write the simple polymer as PEPTIDEx (where x is a number, and in the case of RNA is RNAx). The connection section means that R1 of the first monomer of PEPTIDE1 and R2 of the sixth monomer of PEPTIDE1 are connected. The hydrogen bonds and attributes sections of all peptides in this study are empty. (B) Example of monomer definition of tyrosine (Y).

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Monomer Definition in CycPeptMPDB

As mentioned in the previous section, the method used to define monomers that comprise peptides is important and should be standardized for all entries in the database. However, many of the selected publications did not record sequence representations, and even when records were available, the representation of special amino acids tended to differ notably between these publications. Therefore, we defined the partial structure obtained after cleaving the peptide bonds and ester bonds of the cyclic peptide as a monomer (Figure 3(B), CycPeptMPDB has no peptide containing disulfide bonds). As a result, a total of 312 types of monomers were obtained. There were 305 monomers with the backbone monomer type (having two or more attachment points) and 7 monomers with the terminal monomer type (used for terminal modification of peptide sequences with only one attachment point). Monomers were described in CXSMILES to represent positions of attachment points. For monomers included in the PubChem database, their general compound and International Union of Pure and Applied Chemistry (IUPAC) names were recorded. When not included in the PubChem database, their IUPAC names were generated from SMILES using STOUT software (version 2.0, https://github.com/Kohulan/Smiles-TO-iUpac-Translator). (28) Furthermore, when setting the symbol (the monomers short display name in HELM) and natural analog of monomers, we referred the PubChem database and the monomer library of ChEMBL database (version 29, contained 2851 types of monomers). At this stage, there were 112 types of monomers that did not have suitable symbols, and their symbols were set as Mono1 to Mono112. The explanation of the naming method of symbol is shown in the Table 1. Additionally, we defined two types of peptide molecule shapes: Circle and Lariat. This classification was based on HELM sequence information. Peptides with cyclization positions at both the N- and C-terminal ends of the sequence were considered Circle peptides, and peptides with cyclization positions not at the end of the sequence, i.e., cyclized between a terminal and a side chain, were considered Lariat peptides. Moreover, when calculating descriptors for monomers, the presence of hydrogen bond donors and acceptors for the amide and carboxyl groups may not accurately represent the partial physicochemical properties of the cyclic peptide before cleavage. Therefore, if the original attachment point atom was N or O (amide-to-ester substitution), it was capped with methyl (CH3). If the original attachment point atom was C, a hydrogen atom (H) was added. All monomer descriptors shown in CycPeptMPDB were calculated from such processed molecules. Similar to the method of classifying cyclic peptides by membrane permeability described in the Data Collection section, monomers were classified into four types by LogP (Wildman–Crippen atom-based LogP value, MolLogP descriptor calculated by RDKit software) based on the LogP values of natural amino acids (Figure 4). Monomers with LogP < −0.60 were set as extremely hydrophilic (35 monomers, lower than G: −0.60). Those with −0.60 ≤ LogP < 0.40 were set as hydrophilic (66 monomers, lower than V: 0.43, general hydrophilic amino acids, such as G: −0.60, A: −0.21, and P: 0.28). Those with 0.40 ≤ LogP < 1.40 were set as hydrophobic (127 monomers, general hydrophobic amino acids, such as V: 0.43, I: 0.82, L: 0.82, and F: 1.02). Those with 1.40 ≤ LogP were set as extremely hydrophobic (84 monomers, extremely hydrophobic amino acids, such as W: 1.50).
Table 1. Explanation of Symbols Naming Method
Explanation of naming methodExample of symbol
1. Natural amino acidsA, L, dV
2. Monomers with a general compound nameAbu, Sar, dCha
3. Monomers with side chain modificationsAla(tBu), dGlu(OMe), dPhe(4-F)
4. Monomers with N-terminal modificationsMe_Cha, Bn_Gly, 3-pyridylethyl_Gly
5. Monomers with C-terminal modificationsGlu_NH2
6. Monomers with amide-to-ester substitution(N->O)Val, d(N->O)Val
7. Combination of above 1 to 7Me_Phe(3-Cl), Cys(EtO2H)_NH2
8. Terminal modification of cyclic peptidesac-, -pip
9. Monomers could not named by 1 to 8Mono1 – Mono112

Figure 4

Figure 4. LogP distribution of all monomers. The background color for extremely hydrophilic monomers is blue, hydrophilic monomers light blue, hydrophobic monomers orange, and extremely hydrophobic monomers red.

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Results and Discussion

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Peptide Browsing Function

As mentioned previously, CycPeptMPDB includes 7334 structurally diverse cyclic peptides (the number including duplicated structures from all publications was 7451) from 45 papers and 2 pharmaceutical company patents. As shown in Table S1, only six publications reported more than 100 peptides, 2020_Townsend (29) with 3086 peptides accounting for more than 40% of the total. In addition, when browsing peptides, we prepared three classification methods in addition to browsing by data source: assay type, monomer length, and molecule shape (Figure 5(A)). When classified by monomer length (peptide sequence length), according to the monomer splitting method used in this study (cleavage of peptide and ester bond), the monomer length ranged from 2 to 15. Furthermore, the behavior of side chains of cyclic peptides, and the formation of hydrogen bonds between side chains and the main chain, can have a significant impact on membrane permeability; therefore, it may be necessary to separate the treatment of Circle and Lariat peptides. Circle peptides accounted for under 70% (5115) of the total and Lariat peptides for about 30% (2336). Moreover, detailed information for the source can also be accessed if browsed by data source, as shown in Figure 5(B). After navigating to the corresponding subset list page, the brief table of peptides displays basic information on peptides, including CycPeptMPDB ID, 2D structure image, HELM, permeability, molecular weight, monomer length, and LogP (Figure 5(B)). If users want to further refine the list of accessed peptides, the search function on the upper right of the table can be used. This search function differs from the search function described in the Peptide Search Function for Quick Data Retrieval section in that it can filter peptides that partially match the contents of the table (data source name, publication year of source, original name in source, and molecule shape are provided in addition to the table contents).

Figure 5

Figure 5. (A) Classification method selection for browsing peptides and browsing page. The case when monomer length is selected is shown as an example. (B) Peptides list page. The background color of the permeability cell is yellow when the permeability is high (LogPexp ≥ −6.00) and green when it is low (LogPexp < −6.00).

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Peptide Search Function for Quick Data Retrieval

In addition to peptide browsing, users can use the peptide search function to quickly find their target peptides. The search module supports conditional searches for peptides by seven options and their logical combinations. These options include publication year of source, permeability, assay type, original compound name in source, molecular weight, monomer length, and molecule shape. Numeric options such as permeability can also be searched by range, see CycPeptMPDB usage for specific search examples and detailed instructions. In addition to the homepage, users can also use the peptide search function from the search box in the upper right corner of each page.

Visualization Functions on Peptide Detail Page

We incorporated several useful functions in the peptide detail page for peptides and monomers. First, for peptides of the same structure reported in multiple sources, we listed all published membrane permeability measurements in the peptide information section (Figure 6(A)). In addition to measurements from different assays of the same source, the measured membrane permeabilities between each source are also different. This function allows users to quickly select the measured membrane permeability values obtained under different measurement environments. Because the number of 3D structures that cyclic peptides can take is enormous, the generation of 3D structures requires a large amount of computational resources. Therefore, to facilitate the use of CycPeptMPDB, we generated 5000 conformations per peptide with RDKit software as described in the 3D Structure Generation of Cyclic Peptides section. The most stable single conformation was selected and stored (Figure 6(B)). Finally, to increase the readability of the HELM representation and support sequence-based analysis, we also created HELM image and LogP and TPSA transition diagrams for the sequence (Figure 6(B)). By using these functions, users can quickly capture the change in peptide sequence and partial characterization.

Figure 6

Figure 6. (A) Peptide information section of peptide detail page. (B) Structural information section of peptide detail page. HELM images and LogP transition diagrams are colored by the LogP value of each monomer.

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Browsing and Visualization Functions of Monomers

A total of 312 monomers were defined as substructures that comprise the peptides, and they were classified into 21 categories by their natural analog (20 natural amino acids and unknown (X)). Natural analogs were established by referring to the description of each monomer in PubChem and the monomer library of ChEMBL. Among these 21 categories, categories F (38) and G (38) included the most monomers, and there were other two categories with more than 20 monomers: A (25) and S (26). We provided a browsing function for monomers by natural analog (Figure 7(A)). After navigating to the corresponding subset list page, the brief table displays basic information on monomers, including symbol, 2D structure image, monomer type (backbone or terminal), natural analog, attachment points (R1–R3), molecular weight, and LogP (Figure 7(B)). Next, as shown in Figure 8(A), we included the PubChem CID of the monomer and created a link to PubChem in the monomer detail page. Users can obtain more diverse information on the monomer from PubChem. Moreover, the monomer detail page lists the distribution of the number of peptides containing each monomer and the membrane permeability distribution of these peptides (Figure 8(B)). This function will assist users in performing monomer-level analysis.

Figure 7

Figure 7. Monomer (A) browsing and (B) list pages. LogP cell background color is blue when LogP is extremely hydrophilic (LogP < −0.60), light blue when hydrophilic (−0.60 ≤ LogP < 0.40), orange when hydrophobic (0.40 ≤ LogP < 1.40), and red when extremely hydrophobic (1.40 ≤ LogP).

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Figure 8

Figure 8. (A) Monomer information section of monomer detail page. (B) Statistics section of peptides containing current monomer.

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Conclusion

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This study reports our development of CycPeptMPDB, a comprehensive database of membrane permeability measurements of cyclic peptides with a web interface, consisting of 7334 cyclic peptides collected from 47 publications. In addition to providing a peptide’s component information, sequence representations essential for cyclic peptide drug discovery were created using HELM notation, and monomers that comprise cyclic peptides were constructed. Browsing and searching functions are incorporated to facilitate the rapid acquisition of targeted peptides. CycPeptMPDB provides several additional functions such as online data visualization, data analysis, and downloading, making it a useful platform to support membrane permeability studies. We will continue to collect membrane permeability data of cyclic peptides and record them in CycPeptMPDB. Future improvements to the CycPeptMPDB online analysis platform will include an improved user-friendly interface and more integrative functions. We collected over 7000 structurally diverse cyclic peptide data and have enabled the development of a machine learning-based membrane permeability prediction model with reliable generalization performance. Next, we intend to develop a prediction model that accounts for mechanisms specific to cyclic peptide membrane permeation, such as the “chameleonic” property. At that time, it may be necessary to generate conformers not only from a single environment but from both water and membrane-mimicking environments (such as chloroform).

Data Availability

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All information recorded in CycPeptMPDB can be downloaded from http://cycpeptmpdb.com/download/. The structure and membrane permeability of all cyclic peptides recorded in CycPeptMPDB were collected from published papers and patents. The list of source publications is shown in the Supporting Information (Table S1) or http://cycpeptmpdb.com/resources/statistics/. The implementations of CycPeptMPDB used Docker (https://www.docker.com/). All data were stored in a PostgreSQL-based database and managed by pgAdmin4 (version 6.14, https://www.pgadmin.org/). The website was implemented by Django (version 3.2, https://www.djangoproject.com/), a high-level web framework with Python (version 3.8.3). The web page was constructed using HTML, CSS, and JavaScript; dynamic chart visualization was performed using Highcharts (https://www.highcharts.com/), and 3D structures were presented using ChemDoodle Web Components (https://web.chemdoodle.com/). In addition, RDKit software (version 2020.09.1, https://www.rdkit.org/) was used for 3D structure generation of cyclic peptides, descriptor calculation of cyclic peptides and monomers, and 2D structures image generation of cyclic peptides and monomers. Furthermore, as mentioned in the Methods section, the IUPAC names of monomers referred to the PubChem database (https://pubchem.ncbi.nlm.nih.gov/) were included, and some of them were generated by STOUT software (version 2.0, https://github.com/Kohulan/Smiles-TO-iUpac-Translator). (28)

Supporting Information

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The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jcim.2c01573.

  • Source list for CycPeptMPDB (Table S1): number of peptides, molecular weight range, and assay type of membrane permeability for each source (PDF)

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Author Information

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  • Corresponding Author
    • Yutaka Akiyama - Department of Computer Science, School of Computing, Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8550, Japan;  Middle-Molecule IT-based Drug Discovery Laboratory (MIDL), Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8550, Japan;  Orcidhttps://orcid.org/0000-0003-2863-8703;  Email: [email protected]
  • Authors
    • Jianan Li - Department of Computer Science, School of Computing, Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8550, Japan;  Orcidhttps://orcid.org/0000-0002-9004-5485
    • Keisuke Yanagisawa - Department of Computer Science, School of Computing, Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8550, Japan;  Middle-Molecule IT-based Drug Discovery Laboratory (MIDL), Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8550, Japan;  Orcidhttps://orcid.org/0000-0003-0224-0035
    • Masatake Sugita - Department of Computer Science, School of Computing, Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8550, Japan;  Middle-Molecule IT-based Drug Discovery Laboratory (MIDL), Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8550, Japan;  Orcidhttps://orcid.org/0000-0002-6298-4055
    • Takuya Fujie - Department of Computer Science, School of Computing, Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8550, Japan;  Middle-Molecule IT-based Drug Discovery Laboratory (MIDL), Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8550, Japan;  Orcidhttps://orcid.org/0000-0003-2103-6195
    • Masahito Ohue - Department of Computer Science, School of Computing, Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8550, Japan;  Middle-Molecule IT-based Drug Discovery Laboratory (MIDL), Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8550, Japan;  Orcidhttps://orcid.org/0000-0002-0120-1643
  • Notes
    The authors declare no competing financial interest.

Acknowledgments

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This work was partially supported by KAKENHI (Grants No. 20K19917 and No. 22H03684) of the Japan Society for the Promotion of Science (JSPS), SPRING program (Grant No. JPMJSP2106) of the Japan Science and Technology Agency (JST), FOREST program (Grant No. JPMJFR216J) of the Japan Science and Technology Agency (JST), and Basis for Supporting Innovative Drug Discovery and Life Science Research (BINDS) (Grant No. JP22ama121026) of the Japan Agency for Medical Research and Development (AMED).

References

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    Rationalization of the Membrane Permeability Differences in a Series of Analogue Cyclic Decapeptides
    Witek, Jagna; Wang, Shuzhe; Schroeder, Benjamin; Lingwood, Robin; Dounas, Andreas; Roth, Hans-Jorg; Fouche, Marianne; Blatter, Markus; Lemke, Oliver; Keller, Bettina; Riniker, Sereina
    Journal of Chemical Information and Modeling (2019), 59 (1), 294-308CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
    Cyclization and selected backbone N-methylations are found to be often necessary but not sufficient conditions for peptidic drugs to have a good bioavailability. Thus, the design of cyclic peptides with good passive membrane permeability and good soly. remains a challenge. The backbone scaffold of a recently published series of cyclic decapeptides with six selected backbone N-methylations was designed to favor the adoption of a closed conformation with β-turns and four transannular hydrogen bonds. Although this conformation was indeed adopted by the peptides as detd. by NMR measurements, substantial differences in the membrane permeability were obsd. In this work, we aim to rationalize the impact of discrete side chain modifications on membrane permeability for six of these cyclic decapeptides. The thermodn. and kinetic properties were investigated using mol. dynamics simulations and Markov state modeling in water and chloroform. The study highlights the influence that side-chain modifications can have on the backbone conformation. Peptides with a D-proline in the β-turns were more likely to adopt, even in water, the closed conformation with transannular hydrogen bonds, which facilitates transition through the membrane. The population of the closed conformation in water was found to correlate pos. with PAMPA log Pe.
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    Ono, S.; Naylor, M. R.; Townsend, C. E.; Okumura, C.; Okada, O.; Lokey, R. S. Conformation and Permeability: Cyclic Hexapeptide Diastereomers. J. Chem. Inf. Model. 2019, 59, 2952– 2963,  DOI: 10.1021/acs.jcim.9b00217
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    Conformation and Permeability: Cyclic Hexapeptide Diastereomers
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    Journal of Chemical Information and Modeling (2019), 59 (6), 2952-2963CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
    Conformational ensembles of eight cyclic hexapeptide diastereomers in explicit cyclohexane, chloroform, and water were analyzed by multicanonical mol. dynamics (McMD) simulations. Free-energy landscapes (FELs) for each compd. and solvent were obtained from the mol. shapes and principal component anal. at T = 300 K; detailed anal. of the conformational ensembles and flexibility of the FELs revealed that permeable compds. have different structural profiles even for a single stereoisomeric change. The av. solvent-accessible surface area (SASA) in cyclohexane showed excellent correlation with the cell permeability, whereas this correlation was weaker in chloroform. The av. SASA in water correlated with the aq. soly. The av. polar surface area did not correlate with cell permeability in these solvents. A possible strategy for designing permeable cyclic peptides from FELs obtained from McMD simulations is proposed.
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    Cipcigan, F.; Smith, P.; Crain, J.; Hogner, A.; De Maria, L.; Llinas, A.; Ratkova, E. Membrane Permeability in Cyclic Peptides is Modulated by Core Conformations. J. Chem. Inf. Model. 2021, 61, 263– 269,  DOI: 10.1021/acs.jcim.0c00803
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    Membrane Permeability in Cyclic Peptides is Modulated by Core Conformations
    Cipcigan, Flaviu; Smith, Paul; Crain, Jason; Hogner, Anders; De Maria, Leonardo; Llinas, Antonio; Ratkova, Ekaterina
    Journal of Chemical Information and Modeling (2021), 61 (1), 263-269CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
    Cyclic peptides have the potential to bind to challenging targets, which are undruggable with small mols., but their application is limited by low membrane permeability. Here, using a series of cyclic pentapeptides, established physicochem. criteria of permeable peptides are heavily violated. The authors revealed that a dominant core conformation, stabilized by amides' shielding pattern, could guide the design of novel compds. As a result, counter-intuitive strategies, such as incorporation of polar residues, can be beneficial for permeability. Further core globularity is a promising descriptor, which can extend the capability of std. predictive models.
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    Sugita, M.; Sugiyama, S.; Fujie, T.; Yoshikawa, Y.; Yanagisawa, K.; Ohue, M.; Akiyama, Y. Large-Scale Membrane Permeability Prediction of Cyclic Peptides Crossing a Lipid Bilayer Based on Enhanced Sampling Molecular Dynamics Simulations. J. Chem. Inf. Model. 2021, 61, 3681– 3695,  DOI: 10.1021/acs.jcim.1c00380
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    Large-Scale Membrane Permeability Prediction of Cyclic Peptides Crossing a Lipid Bilayer Based on Enhanced Sampling Molecular Dynamics Simulations
    Sugita, Masatake; Sugiyama, Satoshi; Fujie, Takuya; Yoshikawa, Yasushi; Yanagisawa, Keisuke; Ohue, Masahito; Akiyama, Yutaka
    Journal of Chemical Information and Modeling (2021), 61 (7), 3681-3695CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
    Membrane permeability is a significant obstacle facing the development of cyclic peptide drugs. However, membrane permeation mechanisms are poorly understood. To investigate common features of permeable (and nonpermeable) designs, it is necessary to reproduce the membrane permeation process of cyclic peptides through the lipid bilayer. We simulated the membrane permeation process of 100 six-residue cyclic peptides across the lipid bilayer based on steered mol. dynamics (MD) and replica-exchange umbrella sampling simulations and predicted membrane permeability using the inhomogeneous soly.-diffusion model and a modified version of it. Furthermore, we confirmed the effectiveness of this protocol by predicting the membrane permeability of 56 eight-residue cyclic peptides with diverse chem. structures, including some confidential designs from a pharmaceutical company. As a result, a reasonable correlation between exptl. assessed and calcd. membrane permeability of cyclic peptides was obsd. for the peptide libraries, except for strongly hydrophobic peptides. Our anal. of the MD trajectory demonstrated that most peptides were stabilized in the boundary region between bulk water and membrane and that for most peptides, the process of crossing the center of the membrane is the main obstacle to membrane permeation. The height of this barrier is well correlated with the electrostatic interaction between the peptide and the surrounding media. The structural and energetic features of the representative peptide at each vertical position within the membrane were also analyzed, revealing that peptides permeate the membrane by changing their orientation and conformation according to the surrounding environment.
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    Sugita, M.; Fujie, T.; Yanagisawa, K.; Ohue, M.; Akiyama, Y. Lipid Composition Is Critical for Accurate Membrane Permeability Prediction of Cyclic Peptides by Molecular Dynamics Simulations. J. Chem. Inf. Model. 2022, 62, 4549– 4560,  DOI: 10.1021/acs.jcim.2c00931
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    Lipid Composition Is Critical for Accurate Membrane Permeability Prediction of Cyclic Peptides by Molecular Dynamics Simulations
    Sugita, Masatake; Fujie, Takuya; Yanagisawa, Keisuke; Ohue, Masahito; Akiyama, Yutaka
    Journal of Chemical Information and Modeling (2022), 62 (18), 4549-4560CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
    Cyclic peptides have attracted attention as a promising pharmaceutical modality due to their potential to selectively inhibit previously undruggable targets, such as intracellular protein-protein interactions. Poor membrane permeability is the biggest bottleneck hindering successful drug discovery based on cyclic peptides. Therefore, the development of computational methods that can predict membrane permeability and support elucidation of the membrane permeation mechanism of drug candidate peptides is much sought after. In this study, we developed a protocol to simulate the behavior in membrane permeation steps and est. the membrane permeability of large cyclic peptides with more than or equal to 10 residues. This protocol requires the use of a more realistic membrane model than a single-lipid phospholipid bilayer. To select a membrane model, we first analyzed the effect of cholesterol concn. in the model membrane on the potential of mean force and hydrogen bonding networks along the direction perpendicular to the membrane surface as predicted by mol. dynamics simulations using cyclosporine A. These results suggest that a membrane model with 40 or 50 mol % cholesterol was suitable for predicting the permeation process. Subsequently, two types of membrane models contg. 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine and 40 and 50 mol % cholesterol were used. To validate the efficiency of our protocol, the membrane permeability of 18 ten-residue peptides was predicted. Correlation coeffs. of R > 0.8 between the exptl. and calcd. permeability values were obtained with both model membranes. The results of this study demonstrate that the lipid membrane is not just a medium but also among the main factors detg. the membrane permeability of mols. The computational protocol proposed in this study and the findings obtained on the effect of membrane model compn. will contribute to building a schematic view of the membrane permeation process. Furthermore, the results of this study will eventually aid the elucidation of design rules for peptide drugs with high membrane permeability.
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    Replica-exchange molecular dynamics method for protein folding
    Sugita, Y.; Okamoto, Y.
    Chemical Physics Letters (1999), 314 (1,2), 141-151CODEN: CHPLBC; ISSN:0009-2614. (Elsevier Science B.V.)
    We have developed a formulation for mol. dynamics algorithm for the replica-exchange method. The effectiveness of the method for the protein-folding problem is tested with the penta-peptide Met-enkephalin. The method can overcome the multiple-min. problem by exchanging non-interacting replicas of the system at several temps. From only one simulation run, one can obtain probability distributions in canonical ensemble for a wide temp. range using multiple-histogram re-weighting techniques, which allows the calcn. of any thermodn. quantity as a function of temp. in that range.
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    Wang, S.; König, G.; Roth, H.-J.; Fouché, M.; Rodde, S.; Riniker, S. Effect of Flexibility, Lipophilicity, and the Location of Polar Residues on the Passive Membrane Permeability of a Series of Cyclic Decapeptides. J. Med. Chem. 2021, 64, 12761– 12773,  DOI: 10.1021/acs.jmedchem.1c00775
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    Effect of Flexibility, Lipophilicity, and the Location of Polar Residues on the Passive Membrane Permeability of a Series of Cyclic Decapeptides
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    Journal of Medicinal Chemistry (2021), 64 (17), 12761-12773CODEN: JMCMAR; ISSN:0022-2623. (American Chemical Society)
    Cyclic peptides have received increasing attention over the recent years as potential therapeutics for "undruggable" targets. One major obstacle is, however, their often relatively poor bioavailability. Here, we investigate the structure-permeability relationship of 24 cyclic decapeptides that share the same backbone N-methylation pattern but differ in their side chains. The peptides cover a large range of values for passive membrane permeability as well as lipophilicity and soly. To rationalize the obsd. differences in permeability, we extd. for each peptide the population of the membrane-permeable conformation in water from extensive explicit-solvent mol. dynamics simulations and used this as a metric for conformational rigidity or "prefolding.". The insights from the simulations together with lipophilicity measurements highlight the intricate interplay between polarity/lipophilicity and flexibility/rigidity and the possible compensating effects on permeability. The findings allow us to better understand the structure-permeability relationship of cyclic peptides and ext. general guiding principles.
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    Digiesi, V.; de la Oliva Roque, V.; Vallaro, M.; Caron, G.; Ermondi, G. Permeability prediction in the beyond-Rule-of 5 chemical space: Focus on cyclic hexapeptides. Eur. J. Pharm. Biopharm. 2021, 165, 259– 270,  DOI: 10.1016/j.ejpb.2021.05.017
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    Permeability prediction in the beyond-Rule-of 5 chemical space: Focus on cyclic hexapeptides
    Digiesi, Vito; de la Oliva Roque, Victor; Vallaro, Maura; Caron, Giulia; Ermondi, Giuseppe
    European Journal of Pharmaceutics and Biopharmaceutics (2021), 165 (), 259-270CODEN: EJPBEL; ISSN:0939-6411. (Elsevier B.V.)
    Cyclic peptides (CPs) are gaining more and more relevance in drug discovery. Since one of their main drawbacks is poor permeability, the discovery of new orally available CP drugs requires computational tools that predict CP permeability in very early drug discovery. In this study we used a literature dataset of 62 cyclic hexapeptides to evaluate the performances of a no. of in silico tools based on different computational theory to model and rationalize PAMPA and Caco-2 permeability values. In particular, we submitted the dataset to (a) online calculators, (b) QSPR strategies, (c) a physics-based tool, (d) a mixed approach and (e) a kinetic method. This latter is an emergent strategy in which a few relevant conformations retrieved from a set of mol. dynamics (MD) simulations by the Markov State Model (MSM) are used to establish the compds. permeability. Both free and com. software were used. Results were compared with a model based on exptl. physicochem. descriptors. All the computational approaches but online calculators performed quite well and show that lipophilicity and not polarity is the main determinant of the investigated event. A second major outcome of the study is that the impact of flexibility on the permeability of the considered dataset cannot be unambiguously assessed. Finally, our comparative anal., which also included not common applied strategies, allowed a sound evaluation of the pros and cons of the applied computational approaches.
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    Predicting the Permeability of Macrocycles from Conformational Sampling - Limitations of Molecular Flexibility
    Poongavanam, Vasanthanathan; Atilaw, Yoseph; Ye, Sofie; Wieske, Lianne H. E.; Erdelyi, Mate; Ermondi, Giuseppe; Caron, Giulia; Kihlberg, Jan
    Journal of Pharmaceutical Sciences (Philadelphia, PA, United States) (2021), 110 (1), 301-313CODEN: JPMSAE; ISSN:0022-3549. (Elsevier Inc.)
    Macrocycles constitute superior ligands for targets that have flat binding sites but often require long synthetic routes, emphasizing the need for property prediction prior to synthesis. We have investigated the scope and limitations of machine learning classification models and of regression models for predicting the cell permeability of a set of denovo-designed, drug-like macrocycles. 2D-Based classification models, which are fast to calc., discriminated between macrocycles that had low-medium and high permeability and may be used as virtual filters in early drug discovery projects. Importantly, stereo- and regioisomer were correctly classified. QSPR studies of two small sets of comparator drugs suggested that use of 3D descriptors, calcd. from biol. relevant conformations, would allow development of more precise regression models for late phase drug projects. However, a 3D permeability model could only be developed for a rigid series of macrocycles. Comparison of NMR based conformational anal. with in silico conformational sampling indicated that this shortcoming originates from the inability of the mol. mechanics force field to identify the relevant conformations for flexible macrocycles. We speculate that a Kier flexibility index of ≤10 constitutes a current upper limit for reasonably accurate 3D prediction of macrocycle cell permeability.
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  4. Grant Koch, Alexander Engstrom, Jaru Taechalertpaisarn, Justin Faris, Satoshi Ono, Matthew R. Naylor, R. Scott Lokey. Chromatographic Determination of Permeability-Relevant Lipophilicity Facilitates Rapid Analysis of Macrocyclic Peptide Scaffolds. Journal of Medicinal Chemistry 2024, 67 (21) , 19612-19622. https://doi.org/10.1021/acs.jmedchem.4c01956
  5. Xiaorong Tan, Qianhui Liu, Yanpeng Fang, Yingli Zhu, Fei Chen, Wenbin Zeng, Defang Ouyang, Jie Dong. Predicting Peptide Permeability Across Diverse Barriers: A Systematic Investigation. Molecular Pharmaceutics 2024, 21 (8) , 4116-4127. https://doi.org/10.1021/acs.molpharmaceut.4c00478
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  20. Xinyi Wu, Huitian Lin, Renren Bai, Hongliang Duan. Deep learning for advancing peptide drug development: Tools and methods in structure prediction and design. European Journal of Medicinal Chemistry 2024, 268 , 116262. https://doi.org/10.1016/j.ejmech.2024.116262
  21. Daria de Raffele, Ioana M. Ilie. Unlocking novel therapies: cyclic peptide design for amyloidogenic targets through synergies of experiments, simulations, and machine learning. Chemical Communications 2024, 60 (6) , 632-645. https://doi.org/10.1039/D3CC04630C
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  23. Jianan Li, Keisuke Yanagisawa, Yutaka Akiyama. CycPeptMP: Enhancing Membrane Permeability Prediction of Cyclic Peptides with Multi-Level Molecular Features and Data Augmentation. 2023https://doi.org/10.1101/2023.12.25.573282
  24. Piotr Minkiewicz, Małgorzata Darewicz, Anna Iwaniak. In Silico Analysis of Individual Fractions of Bovine Casein as Precursors of Bioactive Peptides—Influence of Post-Translational Modifications. Applied Sciences 2023, 13 (14) , 8091. https://doi.org/10.3390/app13148091
  25. Lujing Cao, Zhenyu Xu, Tianfeng Shang, Chengyun Zhang, Xinyi Wu, Yejian Wu, Silong Zhai, Liefeng Ma, Hongliang Duan. Multi_CycGT: a DL-based multimodal model for membrane permeability prediction of cyclic peptides. 2023https://doi.org/10.1101/2023.06.20.545822
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Cite this: J. Chem. Inf. Model. 2023, 63, 7, 2240–2250
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Published March 17, 2023

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  • Abstract

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    Figure 1

    Figure 1. Basic framework of CycPeptMPDB. CycPeptMPDB data were collected from published papers and patents of pharmaceutical companies and then manually inspected. Information in various formats was deposited into a PostgreSQL-based database for visualization, downloading, and other web-based functions.

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    Figure 2

    Figure 2. Permeability (LogPexp) distribution of all peptides. The background color of the high permeability range is yellow, and the background color of the low permeability range is green.

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    Figure 3

    Figure 3. (A) Example of HELM notation (PEPTIDE1[dL].[dL].L.[dL].P.Y$PEPTIDE1, PEPTIDE1,1:R1-6:R2$$$) and its constituent parts in this study. If the simple polymer is a peptide, write the simple polymer as PEPTIDEx (where x is a number, and in the case of RNA is RNAx). The connection section means that R1 of the first monomer of PEPTIDE1 and R2 of the sixth monomer of PEPTIDE1 are connected. The hydrogen bonds and attributes sections of all peptides in this study are empty. (B) Example of monomer definition of tyrosine (Y).

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    Figure 4

    Figure 4. LogP distribution of all monomers. The background color for extremely hydrophilic monomers is blue, hydrophilic monomers light blue, hydrophobic monomers orange, and extremely hydrophobic monomers red.

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    Figure 5

    Figure 5. (A) Classification method selection for browsing peptides and browsing page. The case when monomer length is selected is shown as an example. (B) Peptides list page. The background color of the permeability cell is yellow when the permeability is high (LogPexp ≥ −6.00) and green when it is low (LogPexp < −6.00).

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    Figure 6

    Figure 6. (A) Peptide information section of peptide detail page. (B) Structural information section of peptide detail page. HELM images and LogP transition diagrams are colored by the LogP value of each monomer.

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    Figure 7

    Figure 7. Monomer (A) browsing and (B) list pages. LogP cell background color is blue when LogP is extremely hydrophilic (LogP < −0.60), light blue when hydrophilic (−0.60 ≤ LogP < 0.40), orange when hydrophobic (0.40 ≤ LogP < 1.40), and red when extremely hydrophobic (1.40 ≤ LogP).

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    Figure 8

    Figure 8. (A) Monomer information section of monomer detail page. (B) Statistics section of peptides containing current monomer.

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  • References

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      Bioinformatics (2022), 38 (4), 1110-1117CODEN: BOINFP; ISSN:1367-4811. (Oxford University Press)
      Motivation: In recent years, cyclic peptide drugs have been receiving increasing attention because they can target proteins that are difficult to be tackled by conventional small-mol. drugs or antibody drugs. Plasma protein binding rate (PPB) is a significant pharmacokinetic property of a compd. in drug discovery and design. However, due to structural differences, previous computational prediction methods developed for small-mol. compds. cannot be successfully applied to cyclic peptides, and methods for predicting the PPB rate of cyclic peptides with high accuracy are not yet available. Results: Cyclic peptides are larger than small mols., and their local structures have a considerable impact on PPB; thus, mol. descriptors expressing residue-level local features of cyclic peptides, instead of those expressing the entire mol., as well as the circularity of the cyclic peptides should be considered. Therefore, we developed a prediction method named CycPeptPPB using deep learning that considers both factors. First, the macrocycle ring of cyclic peptides was decompd. residue by residue. The residue-based descriptors were arranged according to the sequence information of the cyclic peptide. Furthermore, the circular data augmentation method was used, and the circular convolution method CyclicConv was devised to express the cyclic structure. CycPeptPPB exhibited excellent performance, with mean abs. error (MAE) of 4.79and correlation coeff. (R) of 0.92 for the public drug dataset, compared to the prediction performance of the existing PPB rate prediction software (MAE = 15.08; R = 0.63).
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      The RaPID Platform for the Discovery of Pseudo-Natural Macrocyclic Peptides
      Goto, Yuki; Suga, Hiroaki
      Accounts of Chemical Research (2021), 54 (18), 3604-3617CODEN: ACHRE4; ISSN:0001-4842. (American Chemical Society)
      A review. Conspectus: Although macrocyclic peptides bearing exotic building blocks have proven their utility as pharmaceuticals, the sources of macrocyclic peptide drugs have been largely limited to mimetics of native peptides or natural product peptides. However, the recent emergence of technologies for discovering de novo bioactive peptides has led to their reconceptualization as a promising therapeutic modality. For the construction and screening of libraries of such macrocyclic peptides, our group has devised a platform to conduct affinity-based selection of massive libraries (>1012 unique sequences) of in vitro expressed macrocyclic peptides, which is referred to as the random nonstandard peptides integrated discovery (RaPID) system. The RaPID system integrates genetic code reprogramming using the FIT (flexible in vitro translation) system, which is largely facilitated by flexizymes (flexible tRNA-aminoacylating ribozymes), with mRNA display technol. We have demonstrated that the RaPID system enables rapid discovery of various de novo pseudo-natural peptide ligands for protein targets of interest. Many examples discussed in this Account prove that thioether-closed macrocyclic peptides (teMPs) obtained by the RaPID system generally exhibit remarkably high affinity and specificity, thereby potently inhibiting or activating a specific function(s) of the target. Moreover, such teMPs are used for a wide range of biochem. applications, for example, as crystn. chaperones for intractable transmembrane proteins and for in vivo recognition of specific cell types. Furthermore, recent studies demonstrate that some teMPs exhibit pharmacol. activities in animal models and that even intracellular proteins can be inhibited by teMPs, illustrating the potential of this class of peptides as drug leads. Besides the ring-closing thioether linkage in the teMPs, genetic code reprogramming by the FIT system allows for incorporation of a variety of other exotic building blocks. For instance, diverse nonproteinogenic amino acids, hydroxy acids (ester linkage), amino carbothioic acid (thioamide linkage), and abiotic foldamer units have been successfully incorporated into ribosomally synthesized peptides. Despite such enormous successes in the conventional FIT system, multiple or consecutive incorporation of highly exotic amino acids, such as D- and β-amino acids, is yet challenging, and particularly the synthesis of peptides bearing non-carbonyl backbone structures remains a demanding task. To upgrade the RaPID system to the next generation, we have engaged in intensive manipulation of the FIT system to expand the structural diversity of peptides accessible by our in vitro biosynthesis strategy. Semilogical engineering of tRNA body sequences led to a new suppressor tRNA (tRNAPro1E2) capable of effectively recruiting translation factors, particularly EF-Tu and EF-P. The use of tRNAPro1E2 in the FIT system allows for not only single but also consecutive and multiple elongation of exotic amino acids, such as D-, β-, and γ-amino acids as well as aminobenzoic acids. Moreover, the integration of the FIT system with various chem. or enzymic posttranslational modifications enables us to expand the range of accessible backbone structures to non-carbonyl moieties prominent in natural products and peptidomimetics. In such systems, FIT-expressed peptides undergo multistep backbone conversions in a one-pot manner to yield designer peptides composed of modified backbones such as azolines, azoles, and ring-closing pyridines. Our current research endeavors focus on applying such in vitro biosynthesis systems for the discovery of bioactive de novo pseudo-natural products.
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      Natural Product-Like Macrocyclic N-Methyl-Peptide Inhibitors against a Ubiquitin Ligase Uncovered from a Ribosome-Expressed De Novo Library
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      Chemistry & Biology (Cambridge, MA, United States) (2011), 18 (12), 1562-1570CODEN: CBOLE2; ISSN:1074-5521. (Cell Press)
      Summary: Naturally occurring peptides often possess macrocyclic and N-methylated backbone. These features grant them structural rigidity, high affinity to targets, proteolytic resistance, and occasionally membrane permeability. Because such peptides are produced by either nonribosomal peptide synthetases or enzymic posttranslational modifications, it is yet a formidable challenge in degenerating sequence or length and prepg. libraries for screening bioactive mols. Here, we report a new means of synthesizing a de novo library of "natural product-like" macrocyclic N-methyl-peptides using translation machinery under the reprogrammed genetic code, which is coupled with an in vitro display technique, referred to as RaPID (random nonstandard peptides integrated discovery) system. This system allows for rapid selection of strong binders against an arbitrarily chosen therapeutic target. Here, we have demonstrated the selection of anti-E6AP macrocyclic N-methyl-peptides, one of which strongly inhibits polyubiquitination of proteins such as p53.
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      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhs12htrnI&md5=14dd193429cd72bfb8dc87a9be5a7cf9
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      Cyclic peptides combine several favorable properties such as good binding affinity, target selectivity and low toxicity that make them an attractive modality for the development of therapeutics. Over 40 cyclic peptide drugs are currently in clin. use and around one new cyclic peptide drug enters the market every year on av. The vast majority of clin. approved cyclic peptides are derived from natural products, such as antimicrobials or human peptide hormones. New powerful techniques based on rational design and in vitro evolution have enabled the de novo development of cyclic peptide ligands to targets for which nature does not offer solns. A look at the cyclic peptides currently under clin. evaluation shows that several have been developed using such techniques. This new source for cyclic peptide ligands introduces a freshness to the field, and it is likely that de novo developed cyclic peptides will be in clin. use in the near future.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXjsFGksLg%253D&md5=4b9581365b92b649dad8c7b22c5bd9c3
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      Hosono, Y.; Uchida, S.; Shinkai, M.; Townsend, C. E.; Kelly, C. N.; Naylor, M. R.; Lee, H.-W.; Kanamitsu, K.; Ishii, M.; Ueki, R.; Ueda, T.; Takeuchi, K.; Sugita, M.; Akiyama, Y.; Lokey, S. R.; Morimoto, J.; Sando, S. Amide-to-ester substitution as a stable alternative to N-methylation for increasing membrane permeability in cyclic peptides. Nat. Commun. 2023,  DOI: 10.1038/s41467-023-36978-z
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      Dougherty, P. G.; Sahni, A.; Pei, D. Understanding Cell Penetration of Cyclic Peptides. Chem. Rev. 2019, 119, 10241– 10287,  DOI: 10.1021/acs.chemrev.9b00008
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      Understanding Cell Penetration of Cyclic Peptides
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      Chemical Reviews (Washington, DC, United States) (2019), 119 (17), 10241-10287CODEN: CHREAY; ISSN:0009-2665. (American Chemical Society)
      A review. Approx. 75% of all disease-relevant human proteins, including those involved in intracellular protein-protein interactions (PPIs), are undruggable with the current drug modalities (i.e., small mols. and biologics). Macrocyclic peptides provide a potential soln. to these undruggable targets because their larger sizes (relative to conventional small mols.) endow them the capability of binding to flat PPI interfaces with antibody-like affinity and specificity. Powerful combinatorial library technologies have been developed to routinely identify cyclic peptides as potent, specific inhibitors against proteins including PPI targets. However, with the exception of a very small set of sequences, the vast majority of cyclic peptides are impermeable to the cell membrane, preventing their application against intracellular targets. This Review examines common structural features that render most cyclic peptides membrane impermeable, as well as the unique features that allow the minority of sequences to enter the cell interior by passive diffusion, endocytosis/endosomal escape, or other mechanisms. We also present the current state of knowledge about the mol. mechanisms of cell penetration, the various strategies for designing cell-permeable, biol. active cyclic peptides against intracellular targets, and the assay methods available to quantify their cell-permeability.
      >> More from SciFinder ®
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      Quantifying the chameleonic properties of macrocycles and other high-molecular-weight drugs
      Whitty, Adrian; Zhong, Mengqi; Viarengo, Lauren; Beglov, Dmitri; Hall, David R.; Vajda, Sandor
      Drug Discovery Today (2016), 21 (5), 712-717CODEN: DDTOFS; ISSN:1359-6446. (Elsevier Ltd.)
      Key to the pharmaceutical utility of certain macrocyclic drugs is a 'chameleonic' ability to change their conformation to expose polar groups in aq. soln., but bury them when traversing lipid membranes. Based on anal. of the structures of 20 macrocyclic compds. that are approved oral drugs, we propose that good soly. requires a topol. polar surface area (TPSA, in Å2) of ≥0.2 × mol. wt. (MW). Meanwhile, good passive membrane permeability requires a mol. (i.e., 3D) PSA in nonpolar environments of ≤140 Å2. We show that one or other of these limits is almost invariably violated for compds. with MW > 600 Da, suggesting that some degree of chameleonic behavior is required for most high MW oral drugs.
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      Danelius, E.; Poongavanam, V.; Peintner, S.; Wieske, L. H.; Erdélyi, M.; Kihlberg, J. Solution Conformations Explain the Chameleonic Behaviour of Macrocyclic Drugs. Chem.─Eur. J. 2020, 26, 5231– 5244,  DOI: 10.1002/chem.201905599
      11
      Solution conformations explain the chameleonic behaviour of macrocyclic drugs
      Danelius, Emma; Poongavanam, Vasanthanathan; Peintner, Stefan; Wieske, Lianne H. E.; Erdelyi, Mate; Kihlberg, Jan
      Chemistry - A European Journal (2020), 26 (23), 5231-5244CODEN: CEUJED; ISSN:0947-6539. (Wiley-VCH Verlag GmbH & Co. KGaA)
      It has been hypothesised that drugs in the chem. space "beyond the rule of 5" (bRo5) must behave as mol. chameleons to combine otherwise conflicting properties, including aq. soly., cell permeability and target binding. Evidence for this has, however, been limited to the cyclic peptide cyclosporine A. Herein, we show that the non-peptidic and macrocyclic drugs roxithromycin, telithromycin and spiramycin behave as mol. chameleons, with rifampicin showing a less pronounced behavior. In particular roxithromycin, telithromycin and spiramycin display a marked, yet limited flexibility and populate significantly less polar and more compact conformational ensembles in an apolar than in a polar environment. In addn. to balancing of membrane permeability and aq. soly., this flexibility also allows binding to targets that vary in structure between species. The drugs' passive cell permeability correlates to their 3D polar surface area and corroborate two theor. models for permeability, developed for cyclic peptides. We conclude that mol. chameleonicity should be incorporated in the design of orally administered drugs in the bRo5 space.
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      Lee, D.; Lee, S.; Choi, J.; Song, Y. K.; Kim, M. J.; Shin, D. S.; Bae, M. A.; Kim, Y. C.; Park, C. J.; Lee, K. R.; Choi, J. H.; Seo, J. Interplay among Conformation, Intramolecular Hydrogen Bonds, and Chameleonicity in the Membrane Permeability and Cyclophilin A Binding of Macrocyclic Peptide Cyclosporin O Derivatives. J. Med. Chem. 2021, 64, 8272– 8286,  DOI: 10.1021/acs.jmedchem.1c00211
      12
      Interplay among Conformation, Intramolecular Hydrogen Bonds, and Chameleonicity in the Membrane Permeability and Cyclophilin A Binding of Macrocyclic Peptide Cyclosporin O Derivatives
      Lee, Dongjae; Lee, Sungjin; Choi, Jieun; Song, Yoo-Kyung; Kim, Min Ju; Shin, Dae-Seop; Bae, Myung Ae; Kim, Yong-Chul; Park, Chin-Ju; Lee, Kyeong-Ryoon; Choi, Jun-Ho; Seo, Jiwon
      Journal of Medicinal Chemistry (2021), 64 (12), 8272-8286CODEN: JMCMAR; ISSN:0022-2623. (American Chemical Society)
      A macrocyclic peptide scaffold with well-established structure-property relationship is desirable for tackling undruggable targets. Here, we adopted a natural macrocycle, cyclosporin O (CsO) and its derivs. (CP1-3), and evaluated the impact of conformation on membrane permeability, cyclophilin A (CypA) binding, and the pharmacokinetic (PK) profile. In nonpolar media, CsO showed a similar conformation to cyclosporin A (CsA), a well-known chameleonic macrocycle, but less chameleonic behavior in a polar environment. The weak chameleonicity of CsO resulted in decreased membrane permeability; however, the more rigid conformation of CsO was not detrimental to its PK profile. CsO exhibited a higher plasma concn. than CsA, which resulted from minimal CypA binding and lower accumulation in red blood cells and moderate oral bioavailability (F = 12%). Our study aids understanding of CsO, a macrocyclic peptide that is less explored than CsA but with greater potential for diversity generation and rational design.
      >> More from SciFinder ®
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      Biron, E.; Chatterjee, J.; Ovadia, O.; Langenegger, D.; Brueggen, J.; Hoyer, D.; Schmid, H. A.; Jelinek, R.; Gilon, C.; Hoffman, A.; Kessler, H. Improving oral bioavailability of peptides by multiple N-methylation: Somatostatin analogues. Angew. Chem., Int. Ed. 2008, 47, 2595– 2599,  DOI: 10.1002/anie.200705797
      13
      Improving oral bioavailability of peptides by multiple N-methylation: somatostatin analogues
      Biron, Eric; Chatterjee, Jayanta; Ovadia, Oded; Langenegger, Daniel; Brueggen, Joseph; Hoyer, Daniel; Schmid, Herbert A.; Jelnick, Raz; Gilon, Chaim; Hoffman, Amnon; Kessler, Horst
      Angewandte Chemie, International Edition (2008), 47 (14), 2595-2599CODEN: ACIEF5; ISSN:1433-7851. (Wiley-VCH Verlag GmbH & Co. KGaA)
      A complete library of the N-methylated somatostatin cyclopeptidic analog Veber-Hirschmann peptide cyclo(-PFwKTF-) has been prepd. with the aim of improving its bioavailability. Several analogs from the library were found to bind to the somatostatin receptor in the nanomolar range and one of them shows a significant oral bioavailability of 10%. Conformational anal. shows that N-methylation is allowed at specific positions without affecting the bioactive conformation.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXkvFartLw%253D&md5=42c312786da82941dde6671b1130b61b
    14. 14
      Bockus, A. T.; Schwochert, J. A.; Pye, C. R.; Townsend, C. E.; Sok, V.; Bednarek, M. A.; Lokey, R. S. Going Out on a Limb: Delineating the Effects of β-Branching, N-Methylation, and Side Chain Size on the Passive Permeability, Solubility, and Flexibility of Sanguinamide A Analogues. J. Med. Chem. 2015, 58, 7409– 7418,  DOI: 10.1021/acs.jmedchem.5b00919
      14
      Going Out on a Limb: Delineating The Effects of β-Branching, N-Methylation, and Side Chain Size on the Passive Permeability, Solubility, and Flexibility of Sanguinamide A Analogues
      Bockus, Andrew T.; Schwochert, Joshua A.; Pye, Cameron R.; Townsend, Chad E.; Sok, Vong; Bednarek, Maria A.; Lokey, R. Scott
      Journal of Medicinal Chemistry (2015), 58 (18), 7409-7418CODEN: JMCMAR; ISSN:0022-2623. (American Chemical Society)
      It is well established that intramol. hydrogen bonding and N-methylation play important roles in the passive permeability of cyclic peptides, but other structural features have been explored less intensively. Recent studies on the oral bioavailability of the cyclic heptapeptide sanguinamide A have raised the question of whether steric occlusion of polar groups via β-branching is an effective, yet untapped, tool in cyclic peptide permeability optimization. We report the structures of 17 sanguinamide A analogs designed to test the relative contributions of β-branching, N-methylation, and side chain size to passive membrane permeability and aq. soly. We demonstrate that β-branching has little effect on permeability compared to the effects of aliph. carbon count and N-methylation of exposed NH groups. We highlight a new N-methylated analog of sanguinamide A with a Leu substitution at position 2 that exhibits solvent-dependent flexibility and improved permeability over that of the natural product.
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    15. 15
      Taechalertpaisarn, J.; Ono, S.; Okada, O.; Johnstone, T. C.; Lokey, R. S. A New Amino Acid for Improving Permeability and Solubility in Macrocyclic Peptides through Side Chain-to-Backbone Hydrogen Bonding. J. Med. Chem. 2022, 65, 5072– 5084,  DOI: 10.1021/acs.jmedchem.2c00010
      15
      A new amino acid for improving permeability and solubility in macrocyclic peptides through side chain-to-backbone hydrogen bonding
      Taechalertpaisarn, Jaru; Ono, Satoshi; Okada, Okimasa; Johnstone, Timothy C.; Lokey, R. Scott
      Journal of Medicinal Chemistry (2022), 65 (6), 5072-5084CODEN: JMCMAR; ISSN:0022-2623. (American Chemical Society)
      Despite the notoriously poor membrane permeability of peptides, many cyclic peptide natural products show high passive membrane permeability and potently inhibit a variety of "undruggable" intracellular targets. A major impediment to the design of cyclic peptides with good permeability is the high desolvation energy assocd. with the peptide backbone amide NH groups. While several strategies have been proposed to mitigate this deleterious effect, only few studies have used polar side chains to sequester backbone NH groups. We investigated the ability of N,N-pyrrolidinylglutamine (Pye), whose side chain contains a powerful hydrogen-bond-accepting C:O amide group but no hydrogen-bond donors, to sequester exposed backbone NH groups in a series of cyclic hexapeptide diastereomers. Analyses revealed that specific Leu-to-Pye substitutions conferred dramatic improvements in aq. soly. and permeability in a scaffold- and position-dependent manner. Therefore, this approach offers a complementary tool for improving membrane permeability and soly. in cyclic peptides.
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    16. 16
      Witek, J.; Wang, S.; Schroeder, B.; Lingwood, R.; Dounas, A.; Roth, H.-J.; Fouché, M.; Blatter, M.; Lemke, O.; Keller, B.; Riniker, S. Rationalization of the membrane permeability differences in a series of analogue cyclic decapeptides. J. Chem. Inf. Model. 2019, 59, 294– 308,  DOI: 10.1021/acs.jcim.8b00485
      16
      Rationalization of the Membrane Permeability Differences in a Series of Analogue Cyclic Decapeptides
      Witek, Jagna; Wang, Shuzhe; Schroeder, Benjamin; Lingwood, Robin; Dounas, Andreas; Roth, Hans-Jorg; Fouche, Marianne; Blatter, Markus; Lemke, Oliver; Keller, Bettina; Riniker, Sereina
      Journal of Chemical Information and Modeling (2019), 59 (1), 294-308CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
      Cyclization and selected backbone N-methylations are found to be often necessary but not sufficient conditions for peptidic drugs to have a good bioavailability. Thus, the design of cyclic peptides with good passive membrane permeability and good soly. remains a challenge. The backbone scaffold of a recently published series of cyclic decapeptides with six selected backbone N-methylations was designed to favor the adoption of a closed conformation with β-turns and four transannular hydrogen bonds. Although this conformation was indeed adopted by the peptides as detd. by NMR measurements, substantial differences in the membrane permeability were obsd. In this work, we aim to rationalize the impact of discrete side chain modifications on membrane permeability for six of these cyclic decapeptides. The thermodn. and kinetic properties were investigated using mol. dynamics simulations and Markov state modeling in water and chloroform. The study highlights the influence that side-chain modifications can have on the backbone conformation. Peptides with a D-proline in the β-turns were more likely to adopt, even in water, the closed conformation with transannular hydrogen bonds, which facilitates transition through the membrane. The population of the closed conformation in water was found to correlate pos. with PAMPA log Pe.
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    17. 17
      Ono, S.; Naylor, M. R.; Townsend, C. E.; Okumura, C.; Okada, O.; Lokey, R. S. Conformation and Permeability: Cyclic Hexapeptide Diastereomers. J. Chem. Inf. Model. 2019, 59, 2952– 2963,  DOI: 10.1021/acs.jcim.9b00217
      17
      Conformation and Permeability: Cyclic Hexapeptide Diastereomers
      Ono, Satoshi; Naylor, Matthew R.; Townsend, Chad E.; Okumura, Chieko; Okada, Okimasa; Lokey, R. Scott
      Journal of Chemical Information and Modeling (2019), 59 (6), 2952-2963CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
      Conformational ensembles of eight cyclic hexapeptide diastereomers in explicit cyclohexane, chloroform, and water were analyzed by multicanonical mol. dynamics (McMD) simulations. Free-energy landscapes (FELs) for each compd. and solvent were obtained from the mol. shapes and principal component anal. at T = 300 K; detailed anal. of the conformational ensembles and flexibility of the FELs revealed that permeable compds. have different structural profiles even for a single stereoisomeric change. The av. solvent-accessible surface area (SASA) in cyclohexane showed excellent correlation with the cell permeability, whereas this correlation was weaker in chloroform. The av. SASA in water correlated with the aq. soly. The av. polar surface area did not correlate with cell permeability in these solvents. A possible strategy for designing permeable cyclic peptides from FELs obtained from McMD simulations is proposed.
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    18. 18
      Cipcigan, F.; Smith, P.; Crain, J.; Hogner, A.; De Maria, L.; Llinas, A.; Ratkova, E. Membrane Permeability in Cyclic Peptides is Modulated by Core Conformations. J. Chem. Inf. Model. 2021, 61, 263– 269,  DOI: 10.1021/acs.jcim.0c00803
      18
      Membrane Permeability in Cyclic Peptides is Modulated by Core Conformations
      Cipcigan, Flaviu; Smith, Paul; Crain, Jason; Hogner, Anders; De Maria, Leonardo; Llinas, Antonio; Ratkova, Ekaterina
      Journal of Chemical Information and Modeling (2021), 61 (1), 263-269CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
      Cyclic peptides have the potential to bind to challenging targets, which are undruggable with small mols., but their application is limited by low membrane permeability. Here, using a series of cyclic pentapeptides, established physicochem. criteria of permeable peptides are heavily violated. The authors revealed that a dominant core conformation, stabilized by amides' shielding pattern, could guide the design of novel compds. As a result, counter-intuitive strategies, such as incorporation of polar residues, can be beneficial for permeability. Further core globularity is a promising descriptor, which can extend the capability of std. predictive models.
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    19. 19
      Sugita, M.; Sugiyama, S.; Fujie, T.; Yoshikawa, Y.; Yanagisawa, K.; Ohue, M.; Akiyama, Y. Large-Scale Membrane Permeability Prediction of Cyclic Peptides Crossing a Lipid Bilayer Based on Enhanced Sampling Molecular Dynamics Simulations. J. Chem. Inf. Model. 2021, 61, 3681– 3695,  DOI: 10.1021/acs.jcim.1c00380
      19
      Large-Scale Membrane Permeability Prediction of Cyclic Peptides Crossing a Lipid Bilayer Based on Enhanced Sampling Molecular Dynamics Simulations
      Sugita, Masatake; Sugiyama, Satoshi; Fujie, Takuya; Yoshikawa, Yasushi; Yanagisawa, Keisuke; Ohue, Masahito; Akiyama, Yutaka
      Journal of Chemical Information and Modeling (2021), 61 (7), 3681-3695CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
      Membrane permeability is a significant obstacle facing the development of cyclic peptide drugs. However, membrane permeation mechanisms are poorly understood. To investigate common features of permeable (and nonpermeable) designs, it is necessary to reproduce the membrane permeation process of cyclic peptides through the lipid bilayer. We simulated the membrane permeation process of 100 six-residue cyclic peptides across the lipid bilayer based on steered mol. dynamics (MD) and replica-exchange umbrella sampling simulations and predicted membrane permeability using the inhomogeneous soly.-diffusion model and a modified version of it. Furthermore, we confirmed the effectiveness of this protocol by predicting the membrane permeability of 56 eight-residue cyclic peptides with diverse chem. structures, including some confidential designs from a pharmaceutical company. As a result, a reasonable correlation between exptl. assessed and calcd. membrane permeability of cyclic peptides was obsd. for the peptide libraries, except for strongly hydrophobic peptides. Our anal. of the MD trajectory demonstrated that most peptides were stabilized in the boundary region between bulk water and membrane and that for most peptides, the process of crossing the center of the membrane is the main obstacle to membrane permeation. The height of this barrier is well correlated with the electrostatic interaction between the peptide and the surrounding media. The structural and energetic features of the representative peptide at each vertical position within the membrane were also analyzed, revealing that peptides permeate the membrane by changing their orientation and conformation according to the surrounding environment.
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    20. 20
      Sugita, M.; Fujie, T.; Yanagisawa, K.; Ohue, M.; Akiyama, Y. Lipid Composition Is Critical for Accurate Membrane Permeability Prediction of Cyclic Peptides by Molecular Dynamics Simulations. J. Chem. Inf. Model. 2022, 62, 4549– 4560,  DOI: 10.1021/acs.jcim.2c00931
      20
      Lipid Composition Is Critical for Accurate Membrane Permeability Prediction of Cyclic Peptides by Molecular Dynamics Simulations
      Sugita, Masatake; Fujie, Takuya; Yanagisawa, Keisuke; Ohue, Masahito; Akiyama, Yutaka
      Journal of Chemical Information and Modeling (2022), 62 (18), 4549-4560CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
      Cyclic peptides have attracted attention as a promising pharmaceutical modality due to their potential to selectively inhibit previously undruggable targets, such as intracellular protein-protein interactions. Poor membrane permeability is the biggest bottleneck hindering successful drug discovery based on cyclic peptides. Therefore, the development of computational methods that can predict membrane permeability and support elucidation of the membrane permeation mechanism of drug candidate peptides is much sought after. In this study, we developed a protocol to simulate the behavior in membrane permeation steps and est. the membrane permeability of large cyclic peptides with more than or equal to 10 residues. This protocol requires the use of a more realistic membrane model than a single-lipid phospholipid bilayer. To select a membrane model, we first analyzed the effect of cholesterol concn. in the model membrane on the potential of mean force and hydrogen bonding networks along the direction perpendicular to the membrane surface as predicted by mol. dynamics simulations using cyclosporine A. These results suggest that a membrane model with 40 or 50 mol % cholesterol was suitable for predicting the permeation process. Subsequently, two types of membrane models contg. 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine and 40 and 50 mol % cholesterol were used. To validate the efficiency of our protocol, the membrane permeability of 18 ten-residue peptides was predicted. Correlation coeffs. of R > 0.8 between the exptl. and calcd. permeability values were obtained with both model membranes. The results of this study demonstrate that the lipid membrane is not just a medium but also among the main factors detg. the membrane permeability of mols. The computational protocol proposed in this study and the findings obtained on the effect of membrane model compn. will contribute to building a schematic view of the membrane permeation process. Furthermore, the results of this study will eventually aid the elucidation of design rules for peptide drugs with high membrane permeability.
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    21. 21
      Sugita, Y.; Okamoto, Y. Replica-exchange molecular dynamics method for protein folding. Chem. Phys. Lett. 1999, 314, 141– 151,  DOI: 10.1016/S0009-2614(99)01123-9
      21
      Replica-exchange molecular dynamics method for protein folding
      Sugita, Y.; Okamoto, Y.
      Chemical Physics Letters (1999), 314 (1,2), 141-151CODEN: CHPLBC; ISSN:0009-2614. (Elsevier Science B.V.)
      We have developed a formulation for mol. dynamics algorithm for the replica-exchange method. The effectiveness of the method for the protein-folding problem is tested with the penta-peptide Met-enkephalin. The method can overcome the multiple-min. problem by exchanging non-interacting replicas of the system at several temps. From only one simulation run, one can obtain probability distributions in canonical ensemble for a wide temp. range using multiple-histogram re-weighting techniques, which allows the calcn. of any thermodn. quantity as a function of temp. in that range.
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      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK1MXotVKrsLc%253D&md5=0fec0ff81ca7806c1e1ac29e5f50ce19
    22. 22
      Wang, S.; König, G.; Roth, H.-J.; Fouché, M.; Rodde, S.; Riniker, S. Effect of Flexibility, Lipophilicity, and the Location of Polar Residues on the Passive Membrane Permeability of a Series of Cyclic Decapeptides. J. Med. Chem. 2021, 64, 12761– 12773,  DOI: 10.1021/acs.jmedchem.1c00775
      22
      Effect of Flexibility, Lipophilicity, and the Location of Polar Residues on the Passive Membrane Permeability of a Series of Cyclic Decapeptides
      Wang, Shuzhe; Konig, Gerhard; Roth, Hans-Jorg; Fouche, Marianne; Rodde, Stephane; Riniker, Sereina
      Journal of Medicinal Chemistry (2021), 64 (17), 12761-12773CODEN: JMCMAR; ISSN:0022-2623. (American Chemical Society)
      Cyclic peptides have received increasing attention over the recent years as potential therapeutics for "undruggable" targets. One major obstacle is, however, their often relatively poor bioavailability. Here, we investigate the structure-permeability relationship of 24 cyclic decapeptides that share the same backbone N-methylation pattern but differ in their side chains. The peptides cover a large range of values for passive membrane permeability as well as lipophilicity and soly. To rationalize the obsd. differences in permeability, we extd. for each peptide the population of the membrane-permeable conformation in water from extensive explicit-solvent mol. dynamics simulations and used this as a metric for conformational rigidity or "prefolding.". The insights from the simulations together with lipophilicity measurements highlight the intricate interplay between polarity/lipophilicity and flexibility/rigidity and the possible compensating effects on permeability. The findings allow us to better understand the structure-permeability relationship of cyclic peptides and ext. general guiding principles.
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    23. 23
      Digiesi, V.; de la Oliva Roque, V.; Vallaro, M.; Caron, G.; Ermondi, G. Permeability prediction in the beyond-Rule-of 5 chemical space: Focus on cyclic hexapeptides. Eur. J. Pharm. Biopharm. 2021, 165, 259– 270,  DOI: 10.1016/j.ejpb.2021.05.017
      23
      Permeability prediction in the beyond-Rule-of 5 chemical space: Focus on cyclic hexapeptides
      Digiesi, Vito; de la Oliva Roque, Victor; Vallaro, Maura; Caron, Giulia; Ermondi, Giuseppe
      European Journal of Pharmaceutics and Biopharmaceutics (2021), 165 (), 259-270CODEN: EJPBEL; ISSN:0939-6411. (Elsevier B.V.)
      Cyclic peptides (CPs) are gaining more and more relevance in drug discovery. Since one of their main drawbacks is poor permeability, the discovery of new orally available CP drugs requires computational tools that predict CP permeability in very early drug discovery. In this study we used a literature dataset of 62 cyclic hexapeptides to evaluate the performances of a no. of in silico tools based on different computational theory to model and rationalize PAMPA and Caco-2 permeability values. In particular, we submitted the dataset to (a) online calculators, (b) QSPR strategies, (c) a physics-based tool, (d) a mixed approach and (e) a kinetic method. This latter is an emergent strategy in which a few relevant conformations retrieved from a set of mol. dynamics (MD) simulations by the Markov State Model (MSM) are used to establish the compds. permeability. Both free and com. software were used. Results were compared with a model based on exptl. physicochem. descriptors. All the computational approaches but online calculators performed quite well and show that lipophilicity and not polarity is the main determinant of the investigated event. A second major outcome of the study is that the impact of flexibility on the permeability of the considered dataset cannot be unambiguously assessed. Finally, our comparative anal., which also included not common applied strategies, allowed a sound evaluation of the pros and cons of the applied computational approaches.
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    24. 24
      Poongavanam, V.; Atilaw, Y.; Ye, S.; Wieske, L. H.; Erdelyi, M.; Ermondi, G.; Caron, G.; Kihlberg, J. Predicting the Permeability of Macrocycles from Conformational Sampling – Limitations of Molecular Flexibility. J. Pharm. Sci. 2021, 110, 301– 313,  DOI: 10.1016/j.xphs.2020.10.052
      24
      Predicting the Permeability of Macrocycles from Conformational Sampling - Limitations of Molecular Flexibility
      Poongavanam, Vasanthanathan; Atilaw, Yoseph; Ye, Sofie; Wieske, Lianne H. E.; Erdelyi, Mate; Ermondi, Giuseppe; Caron, Giulia; Kihlberg, Jan
      Journal of Pharmaceutical Sciences (Philadelphia, PA, United States) (2021), 110 (1), 301-313CODEN: JPMSAE; ISSN:0022-3549. (Elsevier Inc.)
      Macrocycles constitute superior ligands for targets that have flat binding sites but often require long synthetic routes, emphasizing the need for property prediction prior to synthesis. We have investigated the scope and limitations of machine learning classification models and of regression models for predicting the cell permeability of a set of denovo-designed, drug-like macrocycles. 2D-Based classification models, which are fast to calc., discriminated between macrocycles that had low-medium and high permeability and may be used as virtual filters in early drug discovery projects. Importantly, stereo- and regioisomer were correctly classified. QSPR studies of two small sets of comparator drugs suggested that use of 3D descriptors, calcd. from biol. relevant conformations, would allow development of more precise regression models for late phase drug projects. However, a 3D permeability model could only be developed for a rigid series of macrocycles. Comparison of NMR based conformational anal. with in silico conformational sampling indicated that this shortcoming originates from the inability of the mol. mechanics force field to identify the relevant conformations for flexible macrocycles. We speculate that a Kier flexibility index of ≤10 constitutes a current upper limit for reasonably accurate 3D prediction of macrocycle cell permeability.
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    25. 25
      Hewitt, W. M.; Leung, S. S.; Pye, C. R.; Ponkey, A. R.; Bednarek, M.; Jacobson, M. P.; Lokey, R. S. Cell-permeable cyclic peptides from synthetic libraries inspired by natural products. J. Am. Chem. Soc. 2015, 137, 715– 721,  DOI: 10.1021/ja508766b
      25
      Cell-Permeable Cyclic Peptides from Synthetic Libraries Inspired by Natural Products
      Hewitt, William M.; Leung, Siegfried S. F.; Pye, Cameron R.; Ponkey, Alexandra R.; Bednarek, Maria; Jacobson, Matthew P.; Lokey, R. Scott
      Journal of the American Chemical Society (2015), 137 (2), 715-721CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)
      Drug design efforts are turning to a new generation of therapeutic targets, such as protein-protein interactions (PPIs), that had previously been considered "undruggable" by typical small mols. There is an emerging view that accessing these targets will require mols. that are larger and more complex than typical small mol. drugs. Here, the authors present a methodol. for the discovery of geometrically diverse, membrane permeable cyclic peptide scaffolds based on the synthesis and permeability screening of a combinatorial library, followed by deconvolution of membrane-permeable scaffolds to identify cyclic peptides with good to excellent passive cell permeabilities. The authors use a combination of exptl. and computational approaches to investigate structure-permeability relationships in one of these scaffolds, and uncover structural and conformational factors that govern passive membrane diffusion in a related set of cyclic peptide diastereomers. Further, the authors investigate the dependency of permeability on side-chain identity of one of these scaffolds through single-point diversifications to show the adaptability of these scaffolds toward development of permeability-biased libraries suitable for bioactivity screens. Overall, the results demonstrate that many novel, cell permeable scaffolds exist beyond those found in extant natural products, and that such scaffolds can be rapidly identified using a combination of synthesis and deconvolution which can, in principle, be applied to any type of macrocyclic template.
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    26. 26
      Furukawa, A.; Schwochert, J.; Pye, C. R.; Asano, D.; Edmondson, Q. D.; Turmon, A. C.; Klein, V. G.; Ono, S.; Okada, O.; Lokey, R. S. Drug-Like Properties in Macrocycles above MW 1000: Backbone Rigidity versus Side-Chain Lipophilicity. Angew. Chem., Int. Ed. 2020, 132, 21755– 21761,  DOI: 10.1002/ange.202004550
      There is no corresponding record for this reference.
    27. 27
      Zhang, T.; Li, H.; Xi, H.; Stanton, R. V.; Rotstein, S. H. HELM: A hierarchical notation language for complex biomolecule structure representation. J. Chem. Inf. Model. 2012, 52, 2796– 2806,  DOI: 10.1021/ci3001925
      27
      HELM: A Hierarchical Notation Language for Complex Biomolecule Structure Representation
      Zhang, Tianhong; Li, Hongli; Xi, Hualin; Stanton, Robert V.; Rotstein, Sergio H.
      Journal of Chemical Information and Modeling (2012), 52 (10), 2796-2806CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
      When biol. macromols. are used as therapeutic agents, it is often necessary to introduce non-natural chem. modifications to improve their pharmaceutical properties. The final products are complex structures where entities such as proteins, peptides, oligonucleotides, and small mol. drugs may be covalently linked to each other, or may include chem. modified biol. moieties. An accurate in silico representation of these complex structures is essential, as it forms the basis for their electronic registration, storage, anal., and visualization. The size of these mols. (henceforth referred to as "biomols.") often makes them too unwieldy and impractical to represent at the at. level, while the presence of non-natural chem. modifications makes it impossible to represent them by sequence alone. Here we describe the Hierarchical Editing Language for Macromols. ("HELM") and demonstrate its utility in the representation of structures such as antisense oligonucleotides, short interference RNAs, peptides, proteins, and antibody drug conjugates.
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    28. 28
      Rajan, K.; Zielesny, A.; Steinbeck, C. STOUT: SMILES to IUPAC names using neural machine translation. J. Cheminf. 2021, 13, 1– 14,  DOI: 10.1186/s13321-021-00512-4
      There is no corresponding record for this reference.
    29. 29
      Townsend, C. E.; Naylor, M. R.; Jason, E.; Pye, C. R.; Schwochert, J. A.; Edmondson, Q.; Lokey, R. S. The passive permeability landscape around geometrically diverse hexa- and heptapeptide macrocycles. ChemRxiv Preprint , 2020.  DOI: 10.26434/chemrxiv.13335941.v1 .
      There is no corresponding record for this reference.

  • Supporting Information

    Supporting Information

    The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jcim.2c01573.

    • Source list for CycPeptMPDB (Table S1): number of peptides, molecular weight range, and assay type of membrane permeability for each source (PDF)


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