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Expanding FTMap for Fragment-Based Identification of Pharmacophore Regions in Ligand Binding Sites

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Download Hi-Res ImageDownload to MS-PowerPointCite This:J. Chem. Inf. Model. 2024, 64, 6, 2084-2100
    Computational Biochemistry

    Expanding FTMap for Fragment-Based Identification of Pharmacophore Regions in Ligand Binding Sites
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    • Omeir Khan
      Omeir Khan
      Department of Chemistry, Boston University, Boston, Massachusetts 02215, United States
      More by Omeir Khan
      Orcidhttps://orcid.org/0000-0002-5822-1549
    • George Jones
      George Jones
      Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York 11794, United States
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    • Maria Lazou
      Maria Lazou
      Department of Biomedical Engineering, Boston University, Boston, Massachusetts 02215, United States
      More by Maria Lazou
    • Diane Joseph-McCarthy
      Diane Joseph-McCarthy
      Department of Biomedical Engineering, Boston University, Boston, Massachusetts 02215, United States
      More by Diane Joseph-McCarthy
    • Dima Kozakov
      Dima Kozakov
      Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York 11794, United States
      Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York 11794, United States
      More by Dima Kozakov
    • Dmitri Beglov
      Dmitri Beglov
      Department of Biomedical Engineering, Boston University, Boston, Massachusetts 02215, United States
      Acpharis Inc., Holliston, Massachusetts 01746, United States
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    • Sandor Vajda*
      Sandor Vajda
      Department of Chemistry, Boston University, Boston, Massachusetts 02215, United States
      Department of Biomedical Engineering, Boston University, Boston, Massachusetts 02215, United States
      *Email: [email protected]
      More by Sandor Vajda
      Orcidhttps://orcid.org/0000-0003-1540-8220
    Other Access OptionsSupporting Information (4)

    Journal of Chemical Information and Modeling

    Cite this: J. Chem. Inf. Model. 2024, 64, 6, 2084–2100
    Click to copy citationCitation copied!
    https://doi.org/10.1021/acs.jcim.3c01969
    Published March 8, 2024
    Copyright © 2024 American Chemical Society
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    Abstract

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    The knowledge of ligand binding hot spots and of the important interactions within such hot spots is crucial for the design of lead compounds in the early stages of structure-based drug discovery. The computational solvent mapping server FTMap can reliably identify binding hot spots as consensus clusters, free energy minima that bind a variety of organic probe molecules. However, in its current implementation, FTMap provides limited information on regions within the hot spots that tend to interact with specific pharmacophoric features of potential ligands. E-FTMap is a new server that expands on the original FTMap protocol. E-FTMap uses 119 organic probes, rather than the 16 in the original FTMap, to exhaustively map binding sites, and identifies pharmacophore features as atomic consensus sites where similar chemical groups bind. We validate E-FTMap against a set of 109 experimentally derived structures of fragment–lead pairs, finding that highly ranked pharmacophore features overlap with the corresponding atoms in both fragments and lead compounds. Additionally, comparisons of mapping results to ensembles of bound ligands reveal that pharmacophores generated with E-FTMap tend to sample highly conserved protein–ligand interactions. E-FTMap is available as a web server at https://eftmap.bu.edu.

    Copyright © 2024 American Chemical Society

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    Supporting Information

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    The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jcim.3c01969.

    • Additional discussion and figures and combined benchmark set of fragment–lead pairs: (https://github.com/OmeirK/E-FTMap-Combined-Benchmark-Set/). (PDF)

    • PDB ID, residue names, and SMILES strings of ligands used for ligand-derived pharmacophores (XLSX)

    • Frequently occurring functional groups (XLSX)

    • Pairwise statistical potential for frequently occurring functional groups (XLSX)

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    Most electronic Supporting Information files are available without a subscription to ACS Web Editions. Such files may be downloaded by article for research use (if there is a public use license linked to the relevant article, that license may permit other uses). Permission may be obtained from ACS for other uses through requests via the RightsLink permission system: http://pubs.acs.org/page/copyright/permissions.html.

    Cited By

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    This article is cited by 2 publications.

    1. Omeir Khan, George Jones, Dima Kozakov, Dmitri Beglov, Diane Joseph-McCarthy, Sandor Vajda. E-FTMap: A Protein Structure Based Pharmacophore Identification Server for Guiding Fragment Expansion. Journal of Molecular Biology 2025, 8 , 168956. https://doi.org/10.1016/j.jmb.2025.168956
    2. Ayan Das, Mumtaza Mumu, Tanjilur Rahman, Md Abu Sayeed, Md Mazharul Islam, John I. Alawneh, Mohammad Mahmudul Hassan. An In Silico Approach to Discover Efficient Natural Inhibitors to Tie Up Epstein–Barr Virus Infection. Pathogens 2024, 13 (11) , 928. https://doi.org/10.3390/pathogens13110928
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    Journal of Chemical Information and Modeling

    Cite this: J. Chem. Inf. Model. 2024, 64, 6, 2084–2100
    Click to copy citationCitation copied!
    https://doi.org/10.1021/acs.jcim.3c01969
    Published March 8, 2024
    Copyright © 2024 American Chemical Society
    Request reuse permissions

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