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FLAP: GRID Molecular Interaction Fields in Virtual Screening. Validation using the DUD Data Set

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Molecular Discovery Limited, 215 Marsh Road, Pinner, Middlesex, London HA5 5NE, United Kingdom, and Laboratory for Chemometrics and Cheminformatics, Chemistry Department, University of Perugia, Via Elce di sotto 10, I-06123 Perugia, Italy
* To whom correspondence should be addressed. E-mail: [email protected]
†Molecular Discovery Limited.
‡University of Perugia.
Cite this: J. Chem. Inf. Model. 2010, 50, 8, 1442–1450
Publication Date (Web):August 6, 2010
https://doi.org/10.1021/ci100221g
Copyright © 2010 American Chemical Society
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    Abstract

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    The performance of FLAP (Fingerprints for Ligands and Proteins) in virtual screening is assessed using a subset of the DUD (Directory of Useful Decoys) benchmarking data set containing 13 targets each with more than 15 different chemotype classes. A variety of ligand and receptor-based virtual screening approaches are examined, using combinations of individual templates 2D structures of known actives, a cocrystallized ligand, a receptor structure, or a cocrystallized ligand-biased receptor structure. We examine several data fusion approaches to combine the results of the individual virtual screens. In doing so, we show that excellent chemotype enrichment is achieved in both single target ligand-based and receptor-based approaches, of approximately 17-fold over random on average at a false positive rate of 1%. We also show that using as much starting knowledge as possible improves chemotype enrichment, and that data fusion using Pareto ranking is an effective method to do this giving up to 50% improvement in enrichment over the single methods. Finally we show that if inactivity or decoy data is incorporated, automatically training the scoring function in FLAP improves recovery still further, with almost 2-fold improvement over the enrichments shown by the single methods. The results clearly demonstrate the utility of FLAP for virtual screening when either a limited or wide range of prior knowledge is available.

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    57. Lydia Siragusa, Simon Cross, Massimo Baroni, Laura Goracci, Gabriele Cruciani. BioGPS: Navigating biological space to predict polypharmacology, off-targeting, and selectivity. Proteins: Structure, Function, and Bioinformatics 2015, 83 (3) , 517-532. https://doi.org/10.1002/prot.24753
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    60. Ali Ahmed, Faisal Saeed, Naomie Salim, Ammar Abdo. Condorcet and borda count fusion method for ligand-based virtual screening. Journal of Cheminformatics 2014, 6 (1) https://doi.org/10.1186/1758-2946-6-19
    61. Domenico Spinelli, Roberta Budriesi, Barbara Cosimelli, Elda Severi, Matteo Micucci, Massimo Baroni, Fabio Fusi, Pierfranco Ioan, Simon Cross, Maria Frosini, Simona Saponara, Rosanna Matucci, Camillo Rosano, Maurizio Viale, Alberto Chiarini, Emanuele Carosati. Playing with Opening and Closing of Heterocycles: Using the Cusmano-Ruccia Reaction to Develop a Novel Class of Oxadiazolothiazinones, Active as Calcium Channel Modulators and P-Glycoprotein Inhibitors. Molecules 2014, 19 (10) , 16543-16572. https://doi.org/10.3390/molecules191016543
    62. Fabio Broccatelli, Nathan Brown. Molecular Interaction Fields for Predicting the Sites and Products of Metabolism. 2014, 221-242. https://doi.org/10.1002/9783527673261.ch09
    63. Lydia Siragusa, Francesca Spyrakis, Laura Goracci, Simon Cross, Gabriele Cruciani. BioGPS: The Music for the Chemo‐ and Bioinformatics Walzer. Molecular Informatics 2014, 33 (6-7) , 446-453. https://doi.org/10.1002/minf.201400028
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    65. Tiziano Tuccinardi, Carlotta Granchi, Jessica Iegre, Ilaria Paterni, Simone Bertini, Marco Macchia, Adriano Martinelli, Yanrong Qian, Xiaozhuo Chen, Filippo Minutolo. Oxime-based inhibitors of glucose transporter 1 displaying antiproliferative effects in cancer cells. Bioorganic & Medicinal Chemistry Letters 2013, 23 (24) , 6923-6927. https://doi.org/10.1016/j.bmcl.2013.09.037
    66. Anna Artese, Simon Cross, Giosuè Costa, Simona Distinto, Lucia Parrotta, Stefano Alcaro, Francesco Ortuso, Gabriele Cruciani. Molecular interaction fields in drug discovery: recent advances and future perspectives. WIREs Computational Molecular Science 2013, 3 (6) , 594-613. https://doi.org/10.1002/wcms.1150
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    71. Valentina Oliveri, Maurizio Viale, Giulia Caron, Cinzia Aiello, Rosaria Gangemi, Graziella Vecchio. Glycosylated copper( ii ) ionophores as prodrugs for β-glucosidase activation in targeted cancer therapy. Dalton Trans. 2013, 42 (6) , 2023-2034. https://doi.org/10.1039/C2DT32429F
    72. Simon Cross, Massimo Baroni, Francesco Ortuso, Stefano Alcaro, Gabriele Cruciani. Disrupting Protein–Protein Interfaces Using GRID Molecular Interaction Fields. 2013, 61-82. https://doi.org/10.1007/978-3-642-37999-4_3
    73. Francesco Sirci, Laura Goracci, David Rodríguez, Jacqueline van Muijlwijk-Koezen, Hugo Gutiérrez-de-Terán, Raimund Mannhold. Ligand-, structure- and pharmacophore-based molecular fingerprints: a case study on adenosine A1, A2A, A2B, and A3 receptor antagonists. Journal of Computer-Aided Molecular Design 2012, 26 (11) , 1247-1266. https://doi.org/10.1007/s10822-012-9612-8
    74. Ansgar Schuffenhauer. Computational methods for scaffold hopping. Wiley Interdisciplinary Reviews: Computational Molecular Science 2012, 2 (6) , 842-867. https://doi.org/10.1002/wcms.1106
    75. Irene Luque Ruiz, Gonzalo Cerruela García, Miguel Ángel Gómez‐Nieto. Structural‐Similarity‐Based Approaches for the Development of Clustering and QSPR/QSAR Models in Chemical Databases. 2012, 201-228. https://doi.org/10.1002/9783527645121.ch7
    76. Marijn P. A. Sanders, Ross McGuire, Luc Roumen, Iwan J. P. de Esch, Jacob de Vlieg, Jan P. G. Klomp, Chris de Graaf. From the protein's perspective: the benefits and challenges of protein structure-based pharmacophore modeling. MedChemComm 2012, 3 (1) , 28-38. https://doi.org/10.1039/C1MD00210D
    77. Filippo Doria, Matteo Nadai, Marco Folini, Marco Di Antonio, Luca Germani, Claudia Percivalle, Claudia Sissi, Nadia Zaffaroni, Stefano Alcaro, Anna Artese, Sara N. Richter, Mauro Freccero. Hybrid ligand–alkylating agents targeting telomeric G-quadruplex structures. Organic & Biomolecular Chemistry 2012, 10 (14) , 2798. https://doi.org/10.1039/c2ob06816h
    78. Pierfranco Ioan, Alessia Ciogli, Francesco Sirci, Roberta Budriesi, Barbara Cosimelli, Marco Pierini, Elda Severi, Alberto Chiarini, Gabriele Cruciani, Francesco Gasparrini, Domenico Spinelli, Emanuele Carosati. Absolute configuration and biological profile of two thiazinooxadiazol-3-ones with L-type calcium channel activity: a study of the structural effects. Organic & Biomolecular Chemistry 2012, 10 (45) , 8994. https://doi.org/10.1039/c2ob25946j
    79. Lorraine Marsh, . Prediction of Ligand Binding Using an Approach Designed to Accommodate Diversity in Protein-Ligand Interactions. PLoS ONE 2011, 6 (8) , e23215. https://doi.org/10.1371/journal.pone.0023215
    80. Gonzalo Cerruela García, Irene Luque Ruiz, Miguel Ángel Gómez-Nieto. Prediction of Drug Activity Using Molecular Fragments-Based Representation and RFE Support Vector Machine Algorithm. 2011, 396-405. https://doi.org/10.1007/978-3-642-21827-9_41
    81. Simon Cross, Gabriele Cruciani. Grid-derived structure-based 3D pharmacophores and their performance compared to docking. Drug Discovery Today: Technologies 2010, 7 (4) , e213-e219. https://doi.org/10.1016/j.ddtec.2010.09.002
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