Virtual screening: A fast tool for drug design

Scientia Pharmaceutica

Volumn 76, Issue 3, 2008, Pages 333-360

  Vyas, Vivek ^a   Jain, Anurekha ^a   Jain, Avijeet ^a   Gupta, Arun ^a  

^a UNIVERSITY INSTITUTE OF TECHNOLOGY   (India)

Author keywords

Docking; Drug design; Pharmacophore; Virtual screening

Indexed keywords

ALGORITHM; COMPUTER SIMULATION; DRUG BINDING; DRUG DESIGN; DRUG SCREENING; MOLECULAR DOCKING; PHARMACOPHORE; REVIEW; VIRTUAL REALITY;

EID: 52449099001     PISSN: 00368709     EISSN: 22180532     Source Type: Journal    
DOI: 10.3797/scipharm.0803-03     Document Type: Review

References (78)

1. Greer J, Erickson JW, Baldwin JJ, Varney MD. Application of the three-dimensional structures of protein target molecules in structure-based drug design. J Med Chem. 1994; 37:1035-1054. [doi:10.1021/jm00034a001]
2. Bohacek RS, McMartin C, Guida WC. The art and practice of structure-based drug design: A molecular modeling perspective. Med Res Rev. 1996; 16: 3-50. [doi:10.1002/(SICI)1098-1128(199601)16:1 <3::AID-MED1 >3.0.CO;2-6]
3. Shoichet BK, Bussiere DE. The Role of Macromolecular Crystallography and Structure for Drug Discovery: Advances and Caveats. Curr Opin Drug Discov Dev. 2000; 3: 408-422.
4. Wodak SJ, Janin J. Computer analysis of protein-protein interaction. J Mol Biol. 1978; 124:323-342. [doi:10.1016/0022-2836(78)90302-9]
5. Kuntz ID, Blany JM, Oatley SJ, Langridge R, Ferrin TE. A geometric approach to macromolecule-ligand interactions. J Mol Biol. 1982; 161: 269-288. [doi:10.1016/0022-2836(82)90153-X]
6. Mugge I, Enyedy I. Virtual Screening. In Burgers Medicinal chemistry and Drug discovery. 6 th ed Volume 1; Verginia : Wiley Interscience , 2003: 243-279. [doi:10.1002/0471266949.bmc006]
7. Shoichet BK. Virtual screening of chemical libraries. Nature. 2004; 432:862-865. [doi:10.1038/nature03197]
8. Tondi D, Slomczynska U, Costi MP, Watterson DM, Ghelli S, Shoichet BK. Structure based discovery and in-parrallel optimization of novel competitive inhibitors of thymidylate synthase. Chem Biol. 1999; 6: 319-331. [doi:10.1016/S1074-5521 (99)80077-5]
9. Burkhard P, Hommel U, Sanner, M Walkinshaw, MD. The discovery of steroids and other novel FKBP inhibitors using a molecular docking program. J Mol Biol.1999; 287: 853-858. [doi:10.1006/jmbi.1999.2621]
10. Schapira M, Raaka BM, Samuels HH, Abagyan R. Rational discovery of novel nuclear hormone receptor antagonists. Proc Natl Acad Sci USA. 2000; 97: 1008-1013. [doi:10.1073/pnas.97.3.1008]
11. Filikov AV, Mohan V, Vickers TA. Identification of Ligands for RNA Targets via Structure-Based Virtual Screening. J Comp Aid Mol Des. 2000; 14: 561-593. [doi:10.1023/A:1008121029716]
12. Perola E, Xu K, Kollmeyer TM, Kaufmann SH, Prendergast FG. Successful virtual screening of a chemical database for farnesyltransferase inhibitor leads. J Med Chem. 2000; 43: 401-408. [doi:10.1021/jm990408a]
13. Boehm HJ, Boehringer M, Bur D, Gmuender H, Huber W, Klaus W, Kostrewa D, Kuehne H, Luebbers T, Meunier-Keller N, Mueller F. Novel inhibitors of DNA gyrase: 3D structure based biased needle screening, hit validation by biophysical methods, and 3D guided optimization. A promising alternative to random screening. J Med Chem. 2000; 43: 2664-2674 [doi:10.1021/jm000017s]
14. Hopkins SC, Vale RD, Kuntz ID. Inhibitors of kinesin activity from structure-based computer screening. Biochemistry. 2000; 39: 2805-2814. [doi:10.1021/bi992474k]
15. Aronov AM, Munagala NR, Ortiz de Montellano PR, Kuntz ID, Wang CC. Rational Design of Selective Submicromolar Inhibitors of Tritrichomonas foetus Hypoxanthine-Guanine-Xanthine Phosphoribosyltransferase. Biochemistry. 2000; 39: 4684-4689. [doi:10.1021/bi992555g]
16. Baxter CA, Murray CW, Waszkowycz B. New Approach to Molecular Docking and Its Application to Virtual Screening of Chemical Databases. J Chem Inf Comput Sci. 2000; 40: 254-262. [doi:10.1021/ci990440d]
17. Walters WP, Ajay A, Murcko MA. Recognizing molecules with drug-like properties. Curr Opin Chem Biol.1999; 3: 384-387. [doi:10.1016/S1367-5931(99) 80058-1]
18. Walters WP, Murcko MA. Library filtering systems and prediction of drug-like properties. In Virtual Screening for Bioactive Molecules. Wiley-VCH, 2000: 10: 15-32. [doi:10.1002/9783527613083.ch2]
19. Clark DE, Pickett SD. Computational Methods for the Prediction of Drug-Likeness. Drug Discov Today. 2000; 5: 49-58. [doi:10.1016/S1359-6446(99) 01451-8]
20. Podlogar BL, Muegge I, Brice LJ. Computational methods to estimate drug development parameters. Curr Opin Drug Discov Dev. 2001; 4: 102-109.
21. Hann M, Hudson B, Lewell X, Lifely R, Miller L, Ramsden N. Strategic pooling of compounds for high-throughput screening. J Chem Inf Comput Sci. 1999; 39: 897-903. [doi:10.1021/ci990423o]
22. Muegge I, Heald, SL, Brittelli D. Simple Selection Criteria for Drug-like Chemical Matter. J Med Chem. 2001; 44: 1841-1846. [doi:10.1021/jm015507e]
23. Ajay A, Walters WP, Murcko MA. Can we learn to distinguish between "drug-like" and "nondrug-like" molecules? J Med Chem. 1998; 27: 3314-3324. [doi:10.1021/jm970666c]
24. Van Drie JH, Weininger D, Martin YC. ALADDIN: an integrated tool for computer-assisted molecular design and pharmacophore recognition from geometric, steric, and substructure searching of three-dimensional molecular structures. J Comput-Aided Mol Des. 1989; 3: 225-251. [doi:10.1007/BF01533070]
25. Walters WP, Stahl MT, Murcko MA. Virtual screening: an overview. Drug Discov Today. 1998; 3: 160-178. [doi:10.1016/S1359-6446(97)01163-X]
26. Ehrlich P. Present status of chemotherapy. Ber Dtsch Chem Ges. 1909; 42: 17-47 [doi:10.1002/cber.19090420105]
27. Gund P. Three-dimensional Pharmacophoric Pattern Searching. Prog Mol Subcell Biol. 1977; 11: 117-143.
28. Marshall GR, Barry CD, Bosshard HE, Dammkoehler RA, Dunn DA. The Conformational Parameter in Drug Design: The Active Analog Approach. Computer-Assisted Drug Design American Chemical Society: Washington D. C., 1979; Vol. ACS Symposium II2.
29. Sufrin JR, Dunn DA, Marshall GR. Steric mapping of the L-methionine binding site of ATP:L-methionine S-adenosyltransferase. Mol Pharmacol. 1981; 19: 307-313.
30. Barnard JM. Substructure searching methods: Old and new. J Chem Infor Compt Sci. 1993; 33: 532-538. [doi:10.1021/ci00014a001]
31. Enyedy IJ, Wang J, Zaman WA, Johnson KM, Wang S. Discovery of substituted 3, 4-Diphenyl-thiazoles as a novel class of monoamine transporter inhibitors through 3-D pharmacophore search using a new pharmacophore model derived from mazindol. Bioorg Med Chem Lett. 2002; 12: 1775-1778. [doi:10.1016/S0960-894X(02) 00243-3]
32. Downs GM, Willett P. Similarity searching in databases of chemical structures. In Lipkowitz KB Boyd DB. Reviews in Computational Chemistry 1 edn Volume 7 New York VCH Publishers, Inc 1996: 1-66.
33. Willett P, Barnard JM, Downs GM. Chemical similarity searching. J Chem Inf Comput Sci. 1998; 38: 983-996. [doi:10.1021/ci9800211]
34. Hoffman BT, Kopajtic T, Katz JL, Newman AH. 2D QSAR Modeling and Preliminary Database Searching for Dopamine Transporter Inhibitors Using Genetic Algorithm Variable Selection of Molconn Z Descriptors. J Med Chem. 2000; 43: 4151-4159. [doi:10.1021/jm990472s]
35. Wang S, Sakamuri S, Enyedy IJ, Kozikowski AP, Deschaux O, Bandyopadhyay BC, Telia SR, Zaman WA, Johnson KM. Discovery of a novel dopamine transporter inhibitor, 4-hydroxy-1-methyl-4-(4-methylphenyl)-3-piperidyl 4-methylphenyl ketone, as a potential cocaine antagonist through 3D-database pharmacophore searching. Molecular modeling, structure-activity relationships, and behavioral pharmacological studies. J Med Chem. 2000; 43: 351-360. [doi:10.1021/jm990516x]
36. Guner OF. Pharmacophore Perception, Development, and Use in Drug Design. International University Line, La Jolla, CA, 2000.
37. Wang R, Gao Y, Lai L. LigBuilder: A Multiple-Purpose Program for Structure-Based Drug Design. J Mol Model. 2000; 6: 498-516. [doi:10.1007/ S0089400060498]
38. Haraki KS, Sheridan RP, Venkataraghavan R, Dunn, DA, McCulloch R. Looking for Pharmacophores in 3-D Databases: Does Conformational Searching Improve the Yield of Actives? Tetrahedron Comput Methodol. 1990; 3: 565-573. [doi:10.1016/0898-5529(90)90159-6]
39. Clark DE, Willett P, Kenny PW. Pharmacophoric Pattern Matching in Files of Three-Dimensional Chemical Structures: Implementation of Flexible Searching. J Mol Graphics. 1993; 11: 146-156. [doi:10.1016/0263-7855(93)80066-Z]
40. Blaney JM, Dixon JS. A good ligand is bard to find: automated. docking methods. Perspect Drug Discov Des. 1993; 1: 301-319. [doi:10.1007/BF02174531]
41. 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: 727-748. [doi:10.1006/jmbi.1996.0897]
42. Wang R, Liu L, Lai L, Tang Y. SCORE: A New Empirical Method for Estimating the Binding Affinity of a Protein-Ligand Complex. J Mol Model.1998; 4: 379-394. [doi:10.1007/S008940050096]
43. Walters WP, Stahl MT, Murcko MA. Virtual screening: an overview. Drug Discov Today. 1998; 3: 160-178. [doi:10.1016/S1359-6446(97)01163-X]
44. Leach AR, Hann MM. The in silica world of virtual libraries. Drug Discov Today 2000; 5: 326-336. [doi:10.1016/S1359-6446(00)01516-6]
45. Lewis RA, Pickett SD, Clark DE. Computer-aided molecular diversity analysis and combinatorial library design. Rev Comput Chem. 2000; 16: 1-51. [doi:10.1002/9780470125939.ch1]
46. Goshe AK, Crippen GM. Quantitative Structure-Activity Relationship by Distance Geometry: Quinazolines as Dihydrofolate Reductase Inhibitors. J Med Chem. 1982; 25: 892-899. [doi:10.1021/jm00350a003]
47. Karplus M, McCammon JA. Dynamics of proteins: elements and function. Annu Rev Biochem. 1983; 52: 263-300. [doi:10.1146/annurev.bi.52.070183.001403]
48. Abagyan R, Totrov M. High-throughput docking for lead generation Curr Opin Chem Biol. 2001; 4: 375-382. [doi:10.1016/S1367-5931 (00)00217-9]
49. Knegtel RM, Kuntz ID, Oshiro.CM. Molecular docking to ensembles of protein structures. J Mol Biol. 1997; 266: 424-440. [doi:10.1006/jmbi.1996.0776]
50. Osterberg F, Morris GM, Sanner MF, Olson AJ, Goodsell DS. Automated docking to multiple target structures: incorporation of protein mobility and structural water heterogeneity in AutoDock. Proteins. 2001; 46: 34-40. [doi:10.1002/prot.10028]
51. Pang YP, Kozikowski AP. Prediction of the binding sites of Huperzine A in acetylcholinesterase by docking studies. J Comput-Aided Mol Des. 1994; 8: 662-669. [doi:10.1007/BF00124014]
52. Bold G, Altmann KH, Bruggen J, Frei J, Lang M, Manley PW, Traxler P, Wietfeld B, Buchdunger E, Cozens R, Ferrari S, Furet P, Hofmann F, Martiny-Baron, G, Mestan J, Rosel J, Sills M, Stover D, Acemoglu F, Boss E, Emmenegger R, Lasser L, Masso E, Roth R, Schlachter C, Vetterli W, Wyss D, Wood JM. New Anilinophthalazines as Potent and Orally Well Absorbed Inhibitors of the VEGF Receptor Tyrosine Kinases Useful as Antagonists of Tumor-Driven Angiogenesis. J Med Chem. 2000; 43: 2310-2323. [doi:10.1021/jm9909443]
53. Carlson HA, Masukawa KM, McCammon JA. Method for Including the Dynamic Fluctuations of a Protein in Computer-aided Drug Design. J Phys Chem. 1999; 110: 1856-1872. [doi:10.1063/1.477873]
54. Bouzida D, Rejto PA, Arthurs S, Colson AB, Freer ST, Gehlhaar DK, Larson V, Luty BA, Rose PW, Verkhivker GM. Computer simulations of ligand-protein binding with ensembles of protein conformations: A Monte Carlo study of HIV-1 protease binding energy landscapes. Int J Quantum Chem. 1999; 72: 73-84. [doi:10.1002/(SICI)1097-461X(1999)72:1<73::AID-QUA7>3.0.CO;2-O]
55. Broughton HB. A method for including protein flexibility in protein-ligand docking: improving tools for database mining and virtual screening. J Mol Graph Model. 2000; 18: 247-257. [doi:10.1016/S1093-3263(00) 00036-X]
56. Carlson HA, McCammon JA. Accommodating protein flexibility in computational drug design. Mol Pharmacol. 2000; 57: 213-218.
57. Friesner RA, Banks JL, Murphy RB, Halgren TA, Klicic JJ, I Mainz DT, Repasky MP, Knoll EH, Shelley M, Perry JK, Shaw DE, Francis P, Shenkin PS. Glide: A New Approach for Rapid, Accurate Docking and Scoring. 1. Method and Assessment of Docking Accuracy. J Med Chem. 47; 2004: 1739-1749. [doi:10.1021/jm0306430]
58. Kroemer RT, Vulpetti A, McDonald JJ, Rohrer DC, Trosset JY, Giordanetto F, Cotesta S, McMartin C, Kihlen M, Pieter FW, Stouten PF. Interactions-Based Accuracy Classification (IBAC) versus Crystal Structure Deviations. J Chem Inf Comput Sci. 2004; 44: 871-881. [doi:10.1021/ci049970m]
59. McMartin C, Bohacek RS. QXP: powerful, rapid computer algorithms for structure-based drug design. J Comput-Aided Mol Des. 1997; 11: 333-334. [doi:10.1023/A: 1007907728892]
60. Kubinyi H. Molecular field analysis. In 3D QSAR in drug design: Theory, methods and. Applications. ESCOM, Leiden, the Netherlands 1993: 443-485.
61. Sippl W. Receptor-based 3DQSAR analysis of estrogen receptor ligands merging the accuracy of receptor-based alignments with the computational efficiency of ligand-based methods. J Comput-Aided Mol Des. 2000; 14: 559-572. [doi:10.1023/A:1008115913787]
62. Sippl W and Holtje HD. Structure-based 3D-QSAR - merging the accuracy of structure-based alignments with the computational efficiency of ligand-based methods. J Mol Struct (Theochem). 2000; 503: 31-50. [doi:10.1016/S0166-1280(99) 00361-9]
63. Vieth M, Cummins DJ. DoMCoSAR: a novel approach for establishing the docking mode that is consistent with the structure-activity relationship. Application to HIV-1 protease inhibitors and VEGF receptor tyrosine kinase inhibitors. J Med Chem. 2000; 43: 3020-3032. [doi:10.1021/jm990609e]
64. Wojciechowski M, Skolnick J. Docking of small ligands to low-resolution and. theoretically predicted receptor structures. J Comp Chem. 2002; 23: 189-197. [doi:10.1002/jcc.1165]
65. Moro S, Li AH, Jacobson KA. Molecular Modeling Studies of Human A3 Adenosine Antagonists: Structural Homology and Receptor Docking. J Chem Inf Comput Sci. 1998; 38: 1239-1248. [doi:10.1021/ci980080e]
66. Kearsley SK, Smith GM. An Alternative Method for the Alignment of Molecular Structures: Maximizing Electrostatic and Steric Overlap. Tetrahedron Comput Methdodol. 1990; 3: 615-633. [doi:10.1016/0898-5529(90)90162-2]
67. Evers A, Klabunde T. Structure-based drug discovery using GPCR homology modeling: successful virtual screening for antagonists of the alpha1A adrenergic receptor. J Med Chem. 2005; 48: 1088-1097. [doi:10.1021/jm0491804]
68. Cummings MD, DesJarlais RL, Gibbs AC, Mohan V, Jaeger EP. Docking to five proteins of a compound set seeded with known actives using DOCK, DOCKVISION, GLIDE, and GOLD suggests that GLIDE and GOLD in general identify the most reasonable binding modes for known active compounds. J Med Chem. 2005; 48: 962-976. [doi:10.1021/jm049798d]
69. Mozziconacci JC, Arnoult E, Bernard P, Do QT, Marot C, Morin-Allory L. Optimization and validation of a docking-scoring protocol; application to virtual screening for COX-2 inhibitors. J Med Chem. 2005; 48: 1055-1068. [doi:10.1021/jm049332v]
70. Evers A, Klabunde T. Structure-based drug discovery using GPCR homology modeling: successful virtual screening for antagonists of the alpha1A adrenergic receptor. J Med Chem. 2005; 48: 1088-1097. [doi:10.1021/jm0491804]
71. Duart MJ, Anton-Fos GM, Aleman PA, Gay-Roig JB, Gonzalez-Rosende ME, Galvez J, Garcia-Domenech R. New Potential Antihistaminic Compounds. Virtual Combinatorial Chemistry, Computational Screening, Real Synthesis, and Pharmacological Evaluation. J Med Chem. 2005; 48: 1260-1264. [doi:10.1021/jm040877z]
72. Zhao L, Brinton RD. Structure-Based Virtual Screening for Plant-Based ERβ-Selective Ligands as Potential Preventative Therapy against Age-Related Neurodegenerative Diseases. J Med Chem. 2005; 48: 3463-3466. [doi:10.1021/jm0490538]
73. Sciabola S, Carosati E, Baroni M, Mannhold R. Comparison of Ligand-Based and Structure-Based 3D-QSAR Approaches: A Case Study on (Aryl-) Bridged 2-Aminobenzonitriles Inhibiting HIV-1 Reverse Transcriptase. J Med Chem. 2005; 48: 3756-3767. [doi:10.1021/jm049162m]
74. Polgar T, Keseru GM. Virtual Screening for β-Secretase (BACE1) Inhibitors Reveals the Importance of Protonation States at Asp32 and Asp228. J Med Chem. 2005; 48: 3749-3755. [doi:10.1021/jm049133b]
75. Scarsi M, Podvinec M, A Roth, Hug H, Kersten S, Albrecht H, Schwede T, Meyer UA, Biozentrum CR. Sulfonylureas and Glinides Exhibit PPAR{gamma} Activity: A Combined Virtual Screening and Biological Assay Approach. Mol Pharmacol. 2006: 69: 170-178. [doi:10.1124/mol.106.024596]
76. Szewczuk LM, Saldanha SA, Ganguly S, Bowers EM, Javoroncov M, Karanam B, Culhane JC, Holbert MA, Klein DC, Abagyan R, Cole PA. De novo discovery of serotonin N-acetyltransferase inhibitors: J Med Chem. 2007; 50: 5330-5338. [doi:10.1021/jm0706463]
77. Cavasotto CN, Orry AJ, Murgolo NJ, Czarniecki MF, Kocsi SA, Hawes BE, O'Neill KA, Hine H, Burton MS, Voigt JH, Abagyan RA, Bayne ML, Monsma FJ Jr. Discovery of novel chemotypes to a G-protein-coupled receptor through ligand-steered homology modeling and structure-based virtual screening. J Med Chem. 2008; 51: 581-588. [doi:10.1021/jm070759m]
78. Cheng JF, Zapf J, Takedomi K, Fukushima C, Ogiku T, Zhang SH, Yang G, Sakurai N, Barbosa M, Jack R, Xu K. Combination of Virtual Screening and High Throughput Gene Profiling for Identification of Novel Liver X Receptor Modulators. J Med Chem. 2008; 51: 2057-2061. [doi:10.1021/jm7011326]