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Current Topics in Medicinal Chemistry


ISSN (Print): 1568-0266
ISSN (Online): 1873-4294

Review Article

Virtual Screening Techniques in Drug Discovery: Review and Recent Applications

Author(s): Sheisi F.L. da Silva Rocha, Carolina G. Olanda, Harold H. Fokoue and Carlos M.R. Sant'Anna*

Volume 19, Issue 19, 2019

Page: [1751 - 1767] Pages: 17

DOI: 10.2174/1568026619666190816101948

Price: $65


The discovery of bioactive molecules is an expensive and time-consuming process and new strategies are continuously searched for in order to optimize this process. Virtual Screening (VS) is one of the recent strategies that has been explored for the identification of candidate bioactive molecules. The number of new techniques and software that can be applied in this strategy has grown considerably in recent years, so, before their use, it is necessary to understand the basics an also the limitations behind each one to get the most out of them. It is also necessary to assess the real contributions of this strategy so that more significant progress can be made in the future. In this context, this review aims to discuss some important points related to VS, including the use of virtual ligand and biotarget libraries, structurebased and ligand-based VS techniques, as well as to present recent cases where this strategy was successfully applied.

Keywords: Ligand based virtual screening, Structure based virtual screening, Virtual libraries, Drug design, Database filtering, Model validation.

Graphical Abstract
Mignani, S.; Huber, S.; Tomás, H.; Rodrigues, J.; Majoral, J.P. Why and how have drug discovery strategies in pharma changed? What are the new mindsets? Drug Discov. Today, 2016, 21(2), 239-249.
[] [PMID: 26376356]
Paul, S.M.; Mytelka, D.S.; Dunwiddie, C.T.; Persinger, C.C.; Munos, B.H.; Lindborg, S.R.; Schacht, A.L. How to improve R&D productivity: the pharmaceutical industry’s grand challenge. Nat. Rev. Drug Discov., 2010, 9(3), 203-214.
[] [PMID: 20168317]
Morgan, S.; Grootendorst, P.; Lexchin, J.; Cunningham, C.; Greyson, D. The cost of drug development: a systematic review. Health Policy, 2011, 100(1), 4-17.
[] [PMID: 21256615]
Lavecchia, A.; Di Giovanni, C. Virtual screening strategies in drug discovery: a critical review. Curr. Med. Chem., 2013, 20(23), 2839-2860.
[] [PMID: 23651302]
Schneider, G. Virtual screening: an endless staircase? Nat. Rev. Drug Discov., 2010, 9(4), 273-276.
[] [PMID: 20357802]
Rodrigues, R.P.; Mantoani, S.P.; de Almeida, J.R.; Pinsetta, F.R.; Semighini, E.P.; da Silva, V.B.; da Silva, C.H.T. Estratégias de triagem virtual no planejamento de fármacos. Revista Virtual de Química, 2012, 4, 739-776.
Brown, D.; Superti-Furga, G. Rediscovering the sweet spot in drug discovery. Drug Discov. Today, 2003, 8(23), 1067-1077.
[] [PMID: 14693466]
Bunnage, M.E.; Gilbert, A.M.; Jones, L.H.; Hett, E.C. Know your target, know your molecule. Nat. Chem. Biol., 2015, 11(6), 368-372.
[] [PMID: 25978985]
Cheng, A.C.; Coleman, R.G.; Smyth, K.T.; Cao, Q.; Soulard, P.; Caffrey, D.R.; Salzberg, A.C.; Huang, E.S. Structure-based maximal affinity model predicts small-molecule druggability. Nat. Biotechnol., 2007, 25(1), 71-75.
[] [PMID: 17211405]
Kitchen, D.B.; Decornez, H.; Furr, J.R.; Bajorath, J. Docking and scoring in virtual screening for drug discovery: methods and applications. Nat. Rev. Drug Discov., 2004, 3(11), 935-949.
[] [PMID: 15520816]
Kooistra, A.J.; Vischer, H.F.; McNaught-Flores, D.; Leurs, R.; de Esch, I.J.; de Graaf, C. Function-specific virtual screening for GPCR ligands using a combined scoring method. Sci. Rep., 2016, 6, 28288.
[] [PMID: 27339552]
Eckert, H.; Vogt, I.; Bajorath, J. Mapping algorithms for molecular similarity analysis and ligand-based virtual screening: design of DynaMAD and comparison with MAD and DMC. J. Chem. Inf. Model., 2006, 46(4), 1623-1634.
[] [PMID: 16859294]
Muegge, I.; Mukherjee, P. An overview of molecular fingerprint similarity search in virtual screening. Expert Opin. Drug Discov., 2016, 11(2), 137-148.
[] [PMID: 26558489]
Cereto-Massagué, A.; Ojeda, M.J.; Valls, C.; Mulero, M.; Garcia-Vallvé, S.; Pujadas, G. Molecular fingerprint similarity search in virtual screening. Methods, 2015, 71, 58-63.
[] [PMID: 25132639]
Cerqueira, N.M.; Sousa, S.F.; Fernandes, P.A.; Ramos, M.J. Virtual screening of compound libraries. Methods Mol. Biol., 2009, 572, 57-70.
[] [PMID: 20694685]
Danishuddin, M.; Khan, A.U. Structure based virtual screening to discover putative drug candidates: necessary considerations and successful case studies. Methods, 2015, 71, 135-145.
[] [PMID: 25448480]
Fradera, X.; Babaoglu, K. Overview of methods and strategies for conducting virtual small molecule screening. Curr. Protoc. Chem. Biol., 2017, 9(3), 196-212.
[] [PMID: 28910858]
Irwin, J.J.; Shoichet, B.K. Docking Screens for Novel Ligands Conferring New Biology. J. Med. Chem., 2016, 59(9), 4103-4120.
[] [PMID: 26913380]
Lionta, E.; Spyrou, G.; Vassilatis, D.K.; Cournia, Z. Structure-based virtual screening for drug discovery: principles, applications and recent advances. Curr. Top. Med. Chem., 2014, 14(16), 1923-1938.
[] [PMID: 25262799]
Seifert, M.H.J.; Lang, M. Essential factors for successful virtual screening. Mini Rev. Med. Chem., 2008, 8(1), 63-72.
[] [PMID: 18220986]
Wang, J.; Ge, Y.; Xie, X.Q. Development and testing of druglike screening libraries. J. Chem. Inf. Model., 2019, 59(1), 53-65.
[] [PMID: 30563329]
Bohacek, R.S.; McMartin, C.; Guida, W.C. The art and practice of structure-based drug design: a molecular modeling perspective. Med. Res. Rev., 1996, 16(1), 3-50.
[<3:AID-MED1>3.0.CO;2-6] [PMID: 8788213]
Ertl, P. Cheminformatics analysis of organic substituents: identification of the most common substituents, calculation of substituent properties, and automatic identification of drug-like bioisosteric groups. J. Chem. Inf. Comput. Sci., 2003, 43(2), 374-380.
[] [PMID: 12653499]
Lewell, X.Q.; Judd, D.B.; Watson, S.P.; Hann, M.M. RECAP--retrosynthetic combinatorial analysis procedure: a powerful new technique for identifying privileged molecular fragments with useful applications in combinatorial chemistry. J. Chem. Inf. Comput. Sci., 1998, 38(3), 511-522.
[] [PMID: 9611787]
Ogata, K.; Isomura, T.; Yamashita, H.; Kubodera, H. A quantitative approach to the estimation of chemical space from a given geometry by the combination of atomic species. QSAR Comb. Sci., 2007, 26, 596-607.
Walters, W.P. Virtual chemical libraries. J. Med. Chem., 2019, 62(3), 1116-1124.
[] [PMID: 30148631]
Brown, R.D.; Hassan, M.; Waldman, M. Combinatorial library design for diversity, cost efficiency, and drug-like character. J. Mol. Graph. Model., 2000, 18(4-5), 427-437, 537.
[] [PMID: 11143560]
Braga, R.C.; Alves, V.M.; Silva, A.C.; Nascimento, M.N.; Silva, F.C.; Liao, L.M.; Andrade, C.H. Virtual screening strategies in medicinal chemistry: the state of the art and current challenges. Curr. Top. Med. Chem., 2014, 14(16), 1899-1912.
[] [PMID: 25262801]
Singh, M.; Tam, B.; Akabayov, B. NMR-fragment based virtual screening: A brief overview. Molecules, 2018, 23(2)E233
[] [PMID: 29370102]
Hall, R.J.; Mortenson, P.N.; Murray, C.W. Efficient exploration of chemical space by fragment-based screening. Prog. Biophys. Mol. Biol., 2014, 116(2-3), 82-91.
[] [PMID: 25268064]
Huggins, D.J.; Venkitaraman, A.R.; Spring, D.R. Rational methods for the selection of diverse screening compounds. ACS Chem. Biol., 2011, 6(3), 208-217.
[] [PMID: 21261294]
Gaulton, A.; Hersey, A.; Nowotka, M.; Bento, A.P.; Chambers, J.; Mendez, D.; Mutowo, P.; Atkinson, F.; Bellis, L.J.; Cibrián-Uhalte, E.; Davies, M.; Dedman, N.; Karlsson, A.; Magariños, M.P.; Overington, J.P.; Papadatos, G.; Smit, I.; Leach, A.R. The ChEMBL database in 2017. Nucleic Acids Res., 2017, 45(D1), D945-D954.
[] [PMID: 27899562]
Chen, J.H.; Linstead, E.; Swamidass, S.J.; Wang, D.; Baldi, P. ChemDB update--full-text search and virtual chemical space. Bioinformatics, 2007, 23(17), 2348-2351.
[] [PMID: 17599932]
Williams, A.J. A perspective of publicly accessible/open-access chemistry databases. Drug Discov. Today, 2008, 13(11-12), 495-501.
[] [PMID: 18549975]
Williams, A.J.; Tkachenko, V.; Golotvin, S.; Kidd, R.; McCann, G. ChemSpider-building a foundation for the semantic web by hosting a crowd sourced databasing platform for chemistry. J. Cheminform., 2010, 2, O16.
Rognan, D.; Bonnet, P. Chemical databases and virtual screening. Med. Sci. (Paris), 2014, 30(12), 1152-1160.
[] [PMID: 25537046]
Wishart, D.S.; Feunang, Y.D.; Guo, A.C.; Lo, E.J.; Marcu, A.; Grant, J.R.; Sajed, T.; Johnson, D.; Li, C.; Sayeeda, Z.; Assempour, N.; Iynkkaran, I.; Liu, Y.; Maciejewski, A.; Gale, N.; Wilson, A.; Chin, L.; Cummings, R.; Le, D.; Pon, A.; Knox, C.; Wilson, M. DrugBank 5.0: a major update to the DrugBank database for 2018. Nucleic Acids Res., 2018, 46(D1), D1074-D1082.
[] [PMID: 29126136]
Ruddigkeit, L.; van Deursen, R.; Blum, L.C.; Reymond, J.L. Enumeration of 166 billion organic small molecules in the chemical universe database GDB-17. J. Chem. Inf. Model., 2012, 52(11), 2864-2875.
[] [PMID: 23088335]
Ye, H.; Ye, L.; Kang, H.; Zhang, D.; Tao, L.; Tang, K.; Liu, X.; Zhu, R.; Liu, Q.; Chen, Y.Z.; Li, Y.; Cao, Z. HIT: linking herbal active ingredients to targets. Nucleic Acids Res., 2011, 39(Database issue), D1055-D1059.
[] [PMID: 21097881]
Weidlich, I.E.; Dexheimer, T.S.; Marchand, C.; Antony, S.; Pommier, Y.; Nicklaus, M.C. Virtual screening using ligand-based pharmacophores for inhibitors of human tyrosyl-DNA phospodiesterase (hTdp1). Bioorg. Med. Chem., 2010, 18(6), 2347-2355.
[] [PMID: 30025429]
Kanehisa, M.; Goto, S.; Sato, Y.; Furumichi, M.; Tanabe, M. KEGG for integration and interpretation of large-scale molecular data sets. Nucleic Acids Res., 2012, 40(Database issue), D109-D114.
[] [PMID: 22080510]
Thota, S.; Rodrigues, D.A.; Pinheiro, P.S.M.; Lima, L.M.; Fraga, C.A.M.; Barreiro, E.J. N-Acylhydrazones as drugs. Bioorg. Med. Chem. Lett., 2018, 28(17), 2797-2806.
[] [PMID: 30006065]
Fraga, C.A.; Barreiro, E.J. Medicinal chemistry of N-acylhydrazones: new lead-compounds of analgesic, antiinflammatory and antithrombotic drugs. Curr. Med. Chem., 2006, 13(2), 167-198.
[] [PMID: 16472212]
Kawabata, T.; Sugihara, Y.; Fukunishi, Y.; Nakamura, H. Ligand- Box: A database for 3D structures of chemical compounds. Biophysics (Nagoya-Shi), 2013, 9, 113-121.
[] [PMID: 27493549]
von Grotthuss, M.; Koczyk, G.; Pas, J.; Wyrwicz, L.S.; Rychlewski, L. Ligand.Info small-molecule Meta-Database. Comb. Chem. High Throughput Screen., 2004, 7(8), 757-761.
[] [PMID: 15578937]
Danishuddin, M.; Khan, A.U. Structure based virtual screening to discover putative drug candidates: necessary considerations and successful case studies. Methods, 2015, 71, 135-145.
[] [PMID: 25448480]
Kumar Mishra, S.; Kumar, A. NALDB: nucleic acid ligand database for small molecules targeting nucleic acid. Database (Oxford), 2016, 2016baw002
[] [PMID: 26896846]
Voigt, J.H.; Bienfait, B.; Wang, S.; Nicklaus, M.C. Comparison of the NCI open database with seven large chemical structural databases. J. Chem. Inf. Comput. Sci., 2001, 41(3), 702-712.
[] [PMID: 11410049]
Pilon, A.C.; Valli, M.; Dametto, A.C.; Pinto, M.E.F.; Freire, R.T.; Castro-Gamboa, I.; Andricopulo, A.D.; Bolzani, V.S. NuBBEDB: an updated database to uncover chemical and biological information from Brazilian biodiversity. Sci. Rep., 2017, 7(1), 7215.
[] [PMID: 28775335]
Berman, H.M.; Westbrook, J.; Feng, Z.; Gilliland, G.; Bhat, T.N.; Weissig, H.; Shindyalov, I.N.; Bourne, P.E. The protein data bank. Nucleic Acids Res., 2000, 28(1), 235-242.
[] [PMID: 10592235]
Wang, R.; Fang, X.; Lu, Y.; Yang, C.Y.; Wang, S. The PDBbind database: methodologies and updates. J. Med. Chem., 2005, 48(12), 4111-4119.
[] [PMID: 15943484]
Gao, Z.; Li, H.; Zhang, H.; Liu, X.; Kang, L.; Luo, X.; Zhu, W.; Chen, K.; Wang, X.; Jiang, H. PDTD: a web-accessible protein database for drug target identification. BMC Bioinformatics, 2008, 9, 104.
[] [PMID: 18282303]
Kim, S.; Chen, J.; Cheng, T.; Gindulyte, A.; He, J.; He, S.; Li, Q.; Shoemaker, B.A.; Thiessen, P.A.; Yu, B.; Zaslavsky, L.; Zhang, J.; Bolton, E.E. PubChem 2019 update: improved access to chemical data. Nucleic Acids Res., 2019, 47(D1), D1102-D1109.
[] [PMID: 30371825]
Kim, S.; Thiessen, P.A.; Bolton, E.E.; Chen, J.; Fu, G.; Gindulyte, A.; Han, L.; He, J.; He, S.; Shoemaker, B.A.; Wang, J.; Yu, B.; Zhang, J.; Bryant, S.H. PubChem substance and compound databases. Nucleic Acids Res., 2016, 44(D1), D1202-D1213.
[] [PMID: 26400175]
Kim, S. Getting the most out of PubChem for virtual screening. Expert Opin. Drug Discov., 2016, 11(9), 843-855.
[] [PMID: 27454129]
Wang, Y.; Bryant, S.H.; Cheng, T.; Wang, J.; Gindulyte, A.; Shoemaker, B.A.; Thiessen, P.A.; He, S.; Zhang, J. PubChem BioAssay: 2017 update. Nucleic Acids Res., 2017, 45(D1), D955-D963.
[] [PMID: 27899599]
Hähnke, V.D.; Kim, S.; Bolton, E.E. PubChem chemical structure standardization. J. Cheminform., 2018, 10(1), 36.
[] [PMID: 30097821]
Kellenberger, E.; Muller, P.; Schalon, C.; Bret, G.; Foata, N.; Rognan, D. sc-PDB: an annotated database of druggable binding sites from the Protein Data Bank. J. Chem. Inf. Model., 2006, 46(2), 717-727.
[] [PMID: 16563002]
Chevillard, F.; Kolb, P. SCUBIDOO: a large yet screenable and easily searchable database of computationally created chemical compounds optimized toward high likelihood of synthetic tractability. J. Chem. Inf. Model., 2015, 55(9), 1824-1835.
[] [PMID: 26282054]
Günther, S.; Kuhn, M.; Dunkel, M.; Campillos, M.; Senger, C.; Petsalaki, E.; Ahmed, J.; Urdiales, E.G.; Gewiess, A.; Jensen, L.J.; Schneider, R.; Skoblo, R.; Russell, R.B.; Bourne, P.E.; Bork, P.; Preissner, R. SuperTarget and Matador: resources for exploring drug-target relationships. Nucleic Acids Res., 2008, 36(Database issue), D919-D922.
[PMID: 17942422]
Banerjee, P.; Erehman, J.; Gohlke, B.O.; Wilhelm, T.; Preissner, R.; Dunkel, M. Super Natural II--a database of natural products. Nucleic Acids Res., 2015, 43(Database issue), D935-D939.
[] [PMID: 25300487]
Siramshetty, V.B.; Eckert, O.A.; Gohlke, B.O.; Goede, A.; Chen, Q.; Devarakonda, P.; Preissner, S.; Preissner, R. SuperDRUG2: a one stop resource for approved/marketed drugs. Nucleic Acids Res., 2018, 46(D1), D1137-D1143.
[] [PMID: 29140469]
Papadatos, G.; Davies, M.; Dedman, N.; Chambers, J.; Gaulton, A.; Siddle, J.; Koks, R.; Irvine, S.A.; Pettersson, J.; Goncharoff, N.; Hersey, A.; Overington, J.P. SureChEMBL: a large-scale, chemically annotated patent document database. Nucleic Acids Res., 2016, 44(D1), D1220-D1228.
[] [PMID: 26582922]
Yang, H.; Qin, C.; Li, Y.H.; Tao, L.; Zhou, J.; Yu, C.Y.; Xu, F.; Chen, Z.; Zhu, F.; Chen, Y.Z. Therapeutic target database update 2016: enriched resource for bench to clinical drug target and targeted pathway information. Nucleic Acids Res., 2016, 44(D1), D1069-D1074.
[] [PMID: 26578601]
Good, A.C.; Oprea, T.I. Optimization of CAMD techniques 3. Virtual screening enrichment studies: a help or hindrance in tool selection? J. Comput. Aided Mol. Des., 2008, 22(3-4), 169-178.
[] [PMID: 18188508]
Sterling, T.; Irwin, J.J. ZINC 15–ligand discovery for everyone. J. Chem. Inf. Model., 2015, 55(11), 2324-2337.
[] [PMID: 26479676]
Huang, H.; Zhang, G.; Zhou, Y.; Lin, C.; Chen, S.; Lin, Y.; Mai, S.; Huang, Z. Reverse screening methods to search for the protein targets of chemopreventive compounds. Front Chem., 2018, 6, 138.
[] [PMID: 29868550]
da Matta, C.B.; de Queiroz, A.C.; Santos, M.S.; Alexandre-Moreira, M.S.; Gonçalves, V.T. Del Cistia, Cde.N.; Sant’Anna, C.M.R.; DaCosta, J.B.N. Novel dialkylphosphorylhydrazones: Synthesis, leishmanicidal evaluation and theoretical investigation of the proposed mechanism of action. Eur. J. Med. Chem., 2015, 101, 1-12.
[] [PMID: 26107111]
van de Waterbeemd, H.; Gifford, E. ADMET in silico modelling: towards prediction paradise? Nat. Rev. Drug Discov., 2003, 2(3), 192-204.
[] [PMID: 12612645]
Lipinski, C.A. Drug-like properties and the causes of poor solubility and poor permeability. J. Pharmacol. Toxicol. Methods, 2000, 44(1), 235-249.
[] [PMID: 11274893]
Teague, S.J.; Davis, A.M.; Leeson, P.D.; Oprea, T. The Design of Leadlike Combinatorial Libraries. Angew. Chem. Int. Ed. Engl., 1999, 38(24), 3743-3748.
[<3743:AID-ANIE3743>3.0.CO;2-U] [PMID: 10649345]
Congreve, M.; Carr, R.; Murray, C.; Jhoti, H.A. ‘rule of three’ for fragment-based lead discovery? Drug Discov. Today, 2003, 8(19), 876-877.
[] [PMID: 14554012]
Hughes, J.D.; Blagg, J.; Price, D.A.; Bailey, S.; Decrescenzo, G.A.; Devraj, R.V.; Ellsworth, E.; Fobian, Y.M.; Gibbs, M.E.; Gilles, R.W.; Greene, N.; Huang, E.; Krieger-Burke, T.; Loesel, J.; Wager, T.; Whiteley, L.; Zhang, Y.; Zhang, Y. Physiochemical drug properties associated with in vivo toxicological outcomes. Bioorg. Med. Chem. Lett., 2008, 18(17), 4872-4875.
[] [PMID: 18691886]
Ursu, O.; Rayan, A.; Goldblum, A.; Oprea, T.I. Understanding drug-likeness. WIREs Comput. Mol. Sci., 2011, 1, 760-781.
Hann, M.M.; Oprea, T.I. Pursuing the leadlikeness concept in pharmaceutical research. Curr. Opin. Chem. Biol., 2004, 8(3), 255-263.
[] [PMID: 15183323]
Bolhassani, A. Target molecules and delivery vehicles for anti-HIV drugs in vitro and in vivo. Curr. Pharm. Des., 2018, 24(29), 3393-3401.
[] [PMID: 29886823]
Kumar, B.V.; Sriram, D.; Yogeeswari, P. Editorial: recent trends in library design and virtual screening in medicinal chemistry and drug discovery. Curr. Top. Med. Chem., 2014, 14(16), 1865-1865.
[] [PMID: 25262807]
Whitty, A. Growing PAINS in academic drug discovery. Future Med. Chem., 2011, 3(7), 797-801.
[] [PMID: 21644825]
Baell, J.B.; Holloway, G.A. New substructure filters for removal of pan assay interference compounds (PAINS) from screening libraries and for their exclusion in bioassays. J. Med. Chem., 2010, 53(7), 2719-2740.
[] [PMID: 20131845]
Xu, X.; Huang, M.; Zou, X. Docking-based inverse virtual screening: methods, applications, and challenges. Biophys. Rep., 2018, 4(1), 1-16.
[] [PMID: 29577065]
Banegas-Luna, A-J.; Cerón-Carrasco, J.P.; Pérez-Sánchez, H. A review of ligand-based virtual screening web tools and screening algorithms in large molecular databases in the age of big data. Future Med. Chem., 2018, 10(22), 2641-2658.
[] [PMID: 30499744]
Drwal, M.N.; Griffith, R. Combination of ligand- and structure-based methods in virtual screening. Drug Discov. Today. Technol., 2013, 10(3), e395-e401.
[] [PMID: 24050136]
Chen, Z.; Tian, G.; Wang, Z.; Jiang, H.; Shen, J.; Zhu, W. Multiple pharmacophore models combined with molecular docking: a reliable way for efficiently identifying novel PDE4 inhibitors with high structural diversity. J. Chem. Inf. Model., 2010, 50(4), 615-625.
[] [PMID: 20353193]
Fu, Y.; Sun, Y.N.; Yi, K.H.; Li, M.Q.; Cao, H.F.; Li, J.Z.; Ye, F. Combination of virtual screening protocol by in silico toward the discovery of novel 4-hydroxyphenylpyruvate dioxygenase inhibitors. Front Chem., 2018, 6, 14.
[] [PMID: 29468151]
Neves, B.J.; Braga, R.C.; Melo-Filho, C.C.; Moreira-Filho, J.T.; Muratov, E.N.; Andrade, C.H. QSAR-based virtual screening: advances and applications in drug discovery. Front. Pharmacol., 2018, 9, 1275.
[] [PMID: 30524275]
Maggiora, G.; Vogt, M.; Stumpfe, D.; Bajorath, J. Molecular similarity in medicinal chemistry. J. Med. Chem., 2014, 57(8), 3186-3204.
[] [PMID: 24151987]
Glem, R.C.; Bender, A.; Arnby, C.H.; Carlsson, L.; Boyer, S.; Smith, J. Circular fingerprints: flexible molecular descriptors with applications from physical chemistry to ADME. IDrugs, 2006, 9(3), 199-204.
[PMID: 16523386]
Duan, J.; Dixon, S.L.; Lowrie, J.F.; Sherman, W. Analysis and comparison of 2D fingerprints: insights into database screening performance using eight fingerprint methods. J. Mol. Graph. Model., 2010, 29(2), 157-170.
[] [PMID: 20579912]
Bender, A.; Mussa, H.Y.; Gill, G.S.; Glen, R.C. Molecular surface point environments for virtual screening and the elucidation of binding patterns (MOLPRINT 3D). J. Med. Chem., 2004, 47(26), 6569-6583.
[] [PMID: 15588092]
Berrhail, F.; Belhadef, H.; Hentabli, H.; Saeed, F. In: Molecular similarity searching with different similarity coefficients and different molecular descriptors. International conference of reliable information and communication technology. Universiti Technologi Malaysia, Johor, Malaysia2017, pp. 39-47.
Vuorinen, A.; Schuster, D. Methods for generating and applying pharmacophore models as virtual screening filters and for bioactivity profiling. Methods, 2015, 71, 113-134.
[] [PMID: 25461773]
Wermuth, C.G.; Ganellin, C.R.; Lindberg, P.; Mitscher, L.A. Glossary of terms used in medicinal chemistry (IUPAC Recommendations 1998). Pure Appl. Chem., 1998, 70, 1129-1143.
Güner, O.F.; Bowen, J.P. Setting the record straight: the origin of the pharmacophore concept. J. Chem. Inf. Model., 2014, 54(5), 1269-1283.
[] [PMID: 24745881]
Qing, X-Y.; Lee, S.; Raeymaecker, J.; Tame, J.R.H.; Zhang, K.Y.J.; Voet, A. Pharmacophore modeling: Advances, Limitations, and current utility in drug discovery. J. Rec. Lig. Chan. Res., 2014, 7, 81-92.
Kaserer, T.; Beck, K.R.; Akram, M.; Odermatt, A.; Schuster, D. Pharmacophore models and pharmacophore-based virtual screening: concepts and applications exemplified on hydroxysteroid dehydrogenases. Molecules, 2015, 20(12), 22799-22832.
[] [PMID: 26703541]
Scior, T.; Bender, A.; Tresadern, G.; Medina-Franco, J.L.; Martínez-Mayorga, K.; Langer, T.; Cuanalo-Contreras, K.; Agrafiotis, D.K. Recognizing pitfalls in virtual screening: a critical review. J. Chem. Inf. Model., 2012, 52(4), 867-881.
[] [PMID: 22435959]
Wolber, G.; Langer, T. LigandScout: 3-D pharmacophores derived from protein-bound ligands and their use as virtual screening filters. J. Chem. Inf. Model., 2005, 45(1), 160-169.
[] [PMID: 15667141]
Mysinger, M.M.; Carchia, M.; Irwin, J.J.; Shoichet, B.K. Directory of useful decoys, enhanced (DUD-E): better ligands and decoys for better benchmarking. J. Med. Chem., 2012, 55(14), 6582-6594.
[] [PMID: 22716043]
Vuorinen, A.; Nashev, L.G.; Odermatt, A.; Rollinger, J.M.; Schuster, D. Pharmacophore model refinement for 11β-hydroxysteroid dehydrogenase inhibitors: search for modulators of intracellular glucocorticoid concentrations. Mol. Inform., 2014, 33(1), 15-25.
[] [PMID: 27485195]
Yao, T.T.; Xie, J.F.; Liu, X.G.; Cheng, J.L.; Zhu, C.Y.; Zhao, J.H.; Dong, X.W. Integration of pharmacophore mapping and molecular docking in sequential virtual screening: towards the discovery of novel JAK2 inhibitors. RSC Advances, 2017, 7, 10353-10360.
Mirza, S.B.; Lee, R.C.H.; Chu, J.J.H.; Salmas, R.E.; Mavromoustakos, T.; Durdagi, S. Discovery of selective dengue virus inhibitors using combination of molecular fingerprint-based virtual screening protocols, structure-based pharmacophore model development, molecular dynamics simulations and in vitro studies. J. Mol. Graph. Model., 2018, 79, 88-102.
[] [PMID: 29156382]
Danishuddin; Khan, A.U. Descriptors and their selection methods in QSAR analysis: paradigm for drug design. Drug Discov. Today, 2016, 21(8), 1291-1302.
[] [PMID: 27326911]
Guido, C.A.; Cortona, P.; Mennucci, B.; Adamo, C. On the metric of charge transfer molecular excitations: a simple chemical descriptor. J. Chem. Theory Comput., 2013, 9(7), 3118-3126.
[] [PMID: 26583991]
Lima, A.N.; Philot, E.A.; Trossini, G.H.G.; Scott, L.P.B.; Maltarollo, V.G.; Honorio, K.M. Use of machine learning approaches for novel drug discovery. Expert Opin. Drug Discov., 2016, 11(3), 225-239.
[] [PMID: 26814169]
Zakharov, A.V.; Peach, M.L.; Sitzmann, M.; Nicklaus, M.C. QSAR modeling of imbalanced high-throughput screening data in PubChem. J. Chem. Inf. Model., 2014, 54(3), 705-712.
[] [PMID: 24524735]
Fourches, D.; Muratov, E.; Tropsha, A. Trust, but verify: on the importance of chemical structure curation in cheminformatics and QSAR modeling research. J. Chem. Inf. Model., 2010, 50(7), 1189-1204.
[] [PMID: 20572635]
Fourches, D.; Muratov, E.; Tropsha, A. Curation of chemogenomics data. Nat. Chem. Biol., 2015, 11(8), 535-535.
[] [PMID: 26196763]
Fourches, D.; Muratov, E.; Tropsha, A. Trust, but verify II: a practical guide to chemogenomics data curation. J. Chem. Inf. Model., 2016, 56(7), 1243-1252.
[] [PMID: 27280890]
Cherkasov, A.; Muratov, E.N.; Fourches, D.; Varnek, A.; Baskin, I.I.; Cronin, M.; Dearden, J.; Gramatica, P.; Martin, Y.C.; Todeschini, R.; Consonni, V.; Kuz’min, V.E.; Cramer, R.; Benigni, R.; Yang, C.; Rathman, J.; Terfloth, L.; Gasteiger, J.; Richard, A.; Tropsha, A. QSAR modeling: where have you been? Where are you going to? J. Med. Chem., 2014, 57(12), 4977-5010.
[] [PMID: 24351051]
Nikolic, K.; Mavridis, L.; Djikic, T.; Vucicevic, J.; Agbaba, D.; Yelekci, K.; Mitchell, J.B. Drug design for CNS diseases: polypharmacological profiling of compounds using cheminformatic, 3D-QSAR and virtual screening methodologies. Front. Neurosci., 2016, 10, 265.
[] [PMID: 27375423]
Gertrudes, J.C.; Maltarollo, V.G.; Silva, R.A.; Oliveira, P.R.; Honório, K.M.; da Silva, A.B.F. Machine learning techniques and drug design. Curr. Med. Chem., 2012, 19(25), 4289-4297.
[] [PMID: 22830342]
Cummings, M.D.; Gibbs, A.C.; DesJarlais, R.L. Processing of small molecule databases for automated docking. Med. Chem., 2007, 3(1), 107-113.
[] [PMID: 17266630]
Khan, F.I.; Wei, D-Q.; Gu, K-R.; Hassan, M.I.; Tabrez, S. Current updates on computer aided protein modeling and designing. Int. J. Biol. Macromol., 2016, 85, 48-62.
[] [PMID: 26730484]
Takeda-Shitaka, M.; Takaya, D.; Chiba, C.; Tanaka, H.; Umeyama, H. Protein structure prediction in structure based drug design. Curr. Med. Chem., 2004, 11(5), 551-558.
[] [PMID: 15032603]
Ngan, C.H.; Bohnuud, T.; Mottarella, S.E.; Beglov, D.; Villar, E.A.; Hall, D.R.; Kozakov, D.; Vajda, S. FTMAP: extended protein mapping with user-selected probe molecules. Nucleic Acids Res., 2012, 40(Web Server issue), W271-5.
[] [PMID: 22589414]
Seco, J.; Luque, F.J.; Barril, X. Binding site detection and druggability index from first principles. J. Med. Chem., 2009, 52(8), 2363-2371.
[] [PMID: 19296650]
Raman, E.P.; Yu, W.; Guvench, O.; Mackerell, A.D. Reproducing crystal binding modes of ligand functional groups using Site-Identification by Ligand Competitive Saturation (SILCS) simulations. J. Chem. Inf. Model., 2011, 51(4), 877-896.
[] [PMID: 21456594]
Abel, R.; Young, T.; Farid, R.; Berne, B.J.; Friesner, R.A. Role of the active-site solvent in the thermodynamics of factor Xa ligand binding. J. Am. Chem. Soc., 2008, 130(9), 2817-2831.
[] [PMID: 18266362]
Kuntz, I.D.; Blaney, J.M.; Oatley, S.J.; Langridge, R.; Ferrin, T.E. A geometric approach to macromolecule-ligand interactions. J. Mol. Biol., 1982, 161(2), 269-288.
[] [PMID: 7154081]
Chaudhary, K.K.; Mishra, N. A Review on molecular docking: novel tool for drug discovery. JSM Chem., 2016, 4, 1029-1032.
Hetényi, C.; van der Spoel, D. Efficient docking of peptides to proteins without prior knowledge of the binding site. Protein Sci., 2002, 11(7), 1729-1737.
[] [PMID: 12070326]
Hetényi, C.; van der Spoel, D. Blind docking of drug-sized compounds to proteins with up to a thousand residues. FEBS Lett., 2006, 580(5), 1447-1450.
[] [PMID: 16460734]
Goodsell, D.S.; Morris, G.M.; Olson, A.J. Automated docking of flexible ligands: applications of AutoDock. J. Mol. Recognit., 1996, 9(1), 1-5.
[<1:AID-JMR241>3.0.CO;2-6] [PMID: 8723313]
Grosdidier, A.; Zoete, V.; Michielin, O. SwissDock, a protein-small molecule docking web service based on EADock DSS. Nucleic Acids Res., 2011, 39(Web Server issue), W270-277.
[] [PMID: 21624888]
Pagadala, N.S.; Syed, K.; Tuszynski, J. Software for molecular docking: a review. Biophys. Rev., 2017, 9(2), 91-102.
[] [PMID: 28510083]
Cheng, T.; Li, Q.; Zhou, Z.; Wang, Y.; Bryant, S.H. Structure-based virtual screening for drug discovery: a problem-centric review. AAPS J., 2012, 14(1), 133-141.
[] [PMID: 22281989]
Dias, R.; de Azevedo, W.F., Jr Molecular docking algorithms. Curr. Drug Targets, 2008, 9(12), 1040-1047.
[] [PMID: 19128213]
Jones, G.; Willett, P.; Glen, R.C.; Leach, A.R.; Taylor, R. Development and validation of a genetic algorithm for flexible docking. J. Mol. Biol., 1997, 267(3), 727-748.
[] [PMID: 9126849]
Ewing, T.J.A.; Makino, S.; Skillman, A.G.; Kuntz, I.D.J. DOCK 4.0: search strategies for automated molecular docking of flexible molecule databases. J. Comput. Aided Mol. Des., 2001, 15(5), 411-428.
[] [PMID: 11394736]
Jain, A.N. Surflex: fully automatic flexible molecular docking using a molecular similarity-based search engine. J. Med. Chem., 2003, 46(4), 499-511.
[] [PMID: 12570372]
Kramer, B.; Rarey, M.; Lengauer, T. Evaluation of the FLEXX incremental construction algorithm for protein-ligand docking. Proteins, 1999, 37(2), 228-241.
[<228:AID-PROT8>3.0.CO;2-8] [PMID: 10584068]
Chen, R.; Li, L.; Weng, Z. ZDOCK: an initial-stage protein-docking algorithm. Proteins, 2003, 52(1), 80-87.
[] [PMID: 12784371]
Pang, Y.P.; Kozikowski, A.P. Prediction of the binding site of 1-benzyl-4-[(5,6-dimethoxy-1-indanon-2-yl)methyl]piperidine in acetylcholinesterase by docking studies with the SYSDOC program. J. Comput. Aided Mol. Des., 1994, 8(6), 683-693.
[] [PMID: 7738604]
Pierce, B.; Tong, W.; Weng, Z. M-ZDOCK: a grid-based approach for Cn symmetric multimer docking. Bioinformatics, 2005, 21(8), 1472-1478.
[] [PMID: 15613396]
Liu, M.; Wang, S. MCDOCK: a Monte Carlo simulation approach to the molecular docking problem. J. Comput. Aided Mol. Des., 1999, 13(5), 435-451.
[] [PMID: 10483527]
Waszkowycz, B. Towards improving compound selection in structure-based virtual screening. Drug Discov. Today, 2008, 13(5-6), 219-226.
[] [PMID: 18342797]
Veerasamy, R.; Rajak, H.; Jain, A.; Sivadasan, S.; Varghese, C.P.; Agrawal, R.K. Validation of QSAR models - strategies and importance. Int. J. Drug Des. Disc., 2011, 2, 511-519.
Triballeau, N.; Acher, F.; Brabet, I.; Pin, J-P.; Bertrand, H.O. Virtual screening workflow development guided by the “receiver operating characteristic” curve approach. Application to high-throughput docking on metabotropic glutamate receptor subtype 4. J. Med. Chem., 2005, 48(7), 2534-2547.
[] [PMID: 15801843]
McClish, D.K. Analyzing a portion of the ROC curve. Med. Decis. Making, 1989, 9(3), 190-195.
[] [PMID: 2668680]
Truchon, J.F.; Bayly, C.I. Evaluating virtual screening methods: good and bad metrics for the “early recognition” problem. J. Chem. Inf. Model., 2007, 47(2), 488-508.
[] [PMID: 17288412]
Sheridan, R.P.; Singh, S.B.; Fluder, E.M.; Kearsley, S.K. Protocols for bridging the peptide to nonpeptide gap in topological similarity searches. J. Chem. Inf. Comput. Sci., 2001, 41(5), 1395-1406.
[] [PMID: 11604041]
Empereur-Mot, C.; Guillemain, H.; Latouche, A.; Zagury, J-F.; Viallon, V.; Montes, M. Predictiveness curves in virtual screening. J. Cheminform., 2015, 7, 52.
[] [PMID: 26539250]
Giangreco, I.; Cosgrove, D.A.; Packer, M.J. An extensive and diverse set of molecular overlays for the validation of pharmacophore programs. J. Chem. Inf. Model., 2013, 53(4), 852-866.
[] [PMID: 23565904]
Melo-Filho, C.C.; Braga, R.C.; Muratov, E.N.; Franco, C.H.; Moraes, C.B.; Freitas-Junior, L.H.; Andrade, C.H. Discovery of new potent hits against intracellular Trypanosoma cruzi by QSAR-based virtual screening. Eur. J. Med. Chem., 2019, 163, 649-659.
[] [PMID: 30562700]
Riniker, S.; Landrum, G.A. Open-source platform to benchmark fingerprints for ligand-based virtual screening. J. Cheminform., 2013, 5(1), 26.
[] [PMID: 23721588]
Thorne, N.; Auld, D.S.; Inglese, J. Apparent activity in high-throughput screening: origins of compound-dependent assay interference. Curr. Opin. Chem. Biol., 2010, 14(3), 315-324.
[] [PMID: 20417149]
Moser, D.; Achenbach, J.; Klingler, F.M. Estel la, B.; Hahn, S.; Proschak, E. Evaluation of structure-derived pharmacophore of soluble epoxide hydrolase inhibitors by virtual screening. Bioorg. Med. Chem. Lett., 2012, 22(21), 6762-6765.
[] [PMID: 23017883]
Moser, D.; Wisniewska, J.M.; Hahn, S.; Achenbach, J.; Buscató, El.; Klingler, F.M.; Hofmann, B.; Steinhilber, D.; Proschak, E. Dual-target virtual screening by pharmacophore elucidation and molecular shape filtering. ACS Med. Chem. Lett., 2012, 3(2), 155-158.
[] [PMID: 24900445]
Waltenberger, B.; Garscha, U.; Temml, V.; Liers, J.; Werz, O.; Schuster, D.; Stuppner, H. Discovery of potent soluble epoxide hydrolase (sEH) inhibitors by pharmacophore-based virtual screening. J. Chem. Inf. Model., 2016, 56(4), 747-762.
[] [PMID: 26882208]
Luo, M.; Wang, X.S.; Tropsha, A. Comparative Analysis of QSAR-based vs. Chemical Similarity Based Predictors of GPCRs Binding Affinity. Mol. Inform., 2016, 35(1), 36-41.
[] [PMID: 27491652]
Zheng, W.; Tropsha, A. Novel variable selection quantitative structure--property relationship approach based on the k-nearest-neighbor principle. J. Chem. Inf. Comput. Sci., 2000, 40(1), 185-194.
[] [PMID: 10661566]
Lagunin, A.; Stepanchikova, A.; Filimonov, D.; Poroikov, V. PASS: prediction of activity spectra for biologically active substances. Bioinformatics, 2000, 16(8), 747-748.
[] [PMID: 11099264]
Keiser, M.J.; Roth, B.L.; Armbruster, B.N.; Ernsberger, P.; Irwin, J.J.; Shoichet, B.K. Relating protein pharmacology by ligand chemistry. Nat. Biotechnol., 2007, 25(2), 197-206.
[] [PMID: 17287757]
Warszycki, D.; Rueda, M.; Mordalski, S.; Kristiansen, K.; Satała, G.; Rataj, K.; Chilmonczyk, Z.; Sylte, I.; Abagyan, R.; Bojarski, A.J. From homology models to a set of predictive binding pockets-a 5-HT1A receptor case study. J. Chem. Inf. Model., 2017, 57(2), 311-321.
[] [PMID: 28055203]
Rueda, M.; Totrov, M.; Abagyan, R. ALiBERO: evolving a team of complementary pocket conformations rather than a single leader. J. Chem. Inf. Model., 2012, 52(10), 2705-2714.
[] [PMID: 22947092]
Liu, S.; Alnammi, M.; Ericksen, S.S.; Voter, A.F.; Ananiev, G.E.; Keck, J.L.; Hoffmann, F.M.; Wildman, S.A.; Gitter, A. practical model selection for prospective virtual screening. J. Chem. Inf. Model., 2019, 59(1), 282-293.
[] [PMID: 30500183]
Damm-Ganamet, K.L.; Arora, N.; Becart, S.; Edwards, J.P.; Lebsack, A.D.; McAllister, H.M.; Nelen, M.I.; Rao, N.L.; Westover, L.; Wiener, J.J.M.; Mirzadegan, T. Accelerating lead identification by high throughput virtual screening: prospective case studies from the pharmaceutical industry. J. Chem. Inf. Model., 2019, 59(5), 2046-2062.
[] [PMID: 30817167]
Jacobson, M.P.; Friesner, R.A.; Xiang, Z.; Honig, B. On the role of the crystal environment in determining protein side-chain conformations. J. Mol. Biol., 2002, 320(3), 597-608.
[] [PMID: 12096912]
Jacobson, M.P.; Pincus, D.L.; Rapp, C.S.; Day, T.J.; Honig, B.; Shaw, D.E.; Friesner, R.A. A hierarchical approach to all-atom protein loop prediction. Proteins, 2004, 55(2), 351-367.
[] [PMID: 15048827]
Lyu, J.; Wang, S.; Balius, T.E.; Singh, I.; Levit, A.; Moroz, Y.S.; O’Meara, M.J.; Che, T.; Algaa, E.; Tolmachova, K.; Tolmachev, A.A.; Shoichet, B.K.; Roth, B.L.; Irwin, J.J. Ultra-large library docking for discovering new chemotypes. Nature, 2019, 566(7743), 224-229.
[] [PMID: 30728502]
Coleman, R.G.; Carchia, M.; Sterling, T.; Irwin, J.J.; Shoichet, B.K. Ligand pose and orientational sampling in molecular docking. PLoS One, 2013, 8(10)e75992
[] [PMID: 24098414]
Jansen, J.M.; Cornell, W.; Tseng, Y.J.; Amaro, R.E. Teach-Discover-Treat (TDT): collaborative computational drug discovery for neglected diseases. J. Mol. Graph. Model., 2012, 38, 360-362.
[] [PMID: 23085175]
Riniker, S.; Landrum, G.A.; Montanari, F.; Villalba, S.D.; Maier, J.; Jansen, J.M.; Walters, W.P.; Shelat, A.A. Virtual-screening workflow tutorials and prospective results from the Teach-Discover-Treat competition 2014 against malaria. F1000 Res., 2017, 6, 1136.
[] [PMID: 28928948]

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