Quantitative structure-activity relationship (QSAR) studies as strategic approach in drug discovery

Medicinal Chemistry Research

Volumn 23, Issue 12, 2014, Pages 4991-5007

  Patel, Harun M ^a   Noolvi, Malleshappa N ^b   Sharma, Poonam ^c   Jaiswal, Varun ^d   Bansal, Sumit ^c   Lohan, Sandeep ^c   Kumar, Suthar Sharad ^c   Abbot, Vikrant ^c   Dhiman, Saurabh ^c   Bhardwaj, Varun ^c  

^a R C PATEL INSTITUTE OF PHARMACEUTICAL EDUCATION AND RESEARCH   (India)

^b Shree Dhanvantary Pharmacy College   (India)

^c JAYPEE UNIVERSITY OF INFORMATION TECHNOLOGY   (India)

^d SHOOLINI UNIVERSITY   (India)

Author keywords

Drug design; Methodology; QSAR

Indexed keywords

EID: 84939885171     PISSN: 10542523     EISSN: 15548120     Source Type: Journal    
DOI: 10.1007/s00044-014-1072-3     Document Type: Article

References (102)

1. Ajmani S, Jadhav K, Kulkarni SA (2006) Three-dimensional QSAR using the k-nearest neighbor method and its interpretation. J Chem Inf Model 46:24-31
2. Akamatsu M (2002) Current state and perspectives of 3D-QSAR. Curr Top Med Chem 2:1381-1394
3. Albert A, Goldacre R, Phillips J (1948) The strength of heterocyclic bases. J Chem Soc 2:2240-2249
4. Albuquerque MG, Hopfinger AJ, Barreiro EJ, De-Alencastro RB (1998) Four-dimensional quantitative structure-activity relationship analysis of a series of interphenylene 7-oxabicycloheptane oxazole thromboxane A2 receptor antagonists. J Chem Inf Comput Sci 38:925-938
5. Albuquerque M, Brito M, Cunha E, Alencastro R, Antunes O, Castro H, Rodrigues C (2007) Multidimensional-QSAR: beyond the third-dimension in drug design. Curr Methods Med Chem Biol Phys 1:91-100
6. Aldenderfer MS, Blashfield RK (1984) A review of clustering methods. In: Aldenderfer MS, Blashfield RK (eds) Cluster analysis. SAGE Publications Ltd, London, pp 33-61
7. Andrade CH, Pasqualoto KFM, Ferreira EI, Hopfinger AJ (2009) Rational design and 3D-pharmacophore mapping of 5 thiourea-substituted alpha-thymidine analogues as mycobacterial TMPK inhibitors. J Chem Inf Model 49:1070-1078
8. Andricopulo AD, Salum LB, Abraham DJ (2009) Structure-based drug design strategies in medicinal chemistry. Curr Top Med Chem 9:771-790
9. Baskin II, Palyulin VA, Zefirov NS (2008) Neural networks in building QSAR models. Methods Mol Biol 458:137-158
10. Baxter AD, Lockey PM (2001) Hit to lead and lead to candidaté optimization using multi-parametric principles. Drug Discov World 2:9-15
11. Berk RA (2003a) Simple linear regression. Regression analysis: a constructive critique. SAGE Publications Ltd, London, pp 21-38
12. Berk RA (2003b) Some popular extensions of multiple regression. Regression analysis: a constructive critique. SAGE Publications Ltd, London, pp 125-150
13. Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov IN, Bourne PE (2000) The protein data bank. Nucleic Acids Res 28:235-242
14. Boyd MR, Paull KD (1995) Some practical considerations and applications of the National Cancer Institute in vitro anticancer drug discovery screen. Drug devel Res 34:91-109
15. Breu B, Silber K, Gohlke H (2007) Consensus adaptation of fields for molecular comparison (AFMoC) models incorporate ligand and receptor conformational variability into tailor-made scoring functions. J Chem Inf Model 47:2383-2400
16. Bruneau P, McElroy NR (2006) logD 7.4 modeling using Bayesian regularized neural networks. Assessment and correction of the errors of prediction. J Chem Inf Model 46:1379-1387
17. Collins FS, Patrinos A, Jordan E, Chakravati A, Gesteland R, Walters L (1998) New goals for the US human genome project: 1998-2003. Science 282:682-689
18. Colosi LM, Huang Q, Weber WJ Jr (2010) QSAR-assisted design of an environmental catalyst for enhanced estrogen remediation. Chemosphere 81:897-903
19. Datar PA, Khedkar SA, Malde AK, Coutinho EC (2006) Comparative residue interaction analysis (CoRIA): a 3D-QSAR approach to explore the binding contributions of active site residues with ligands. J Comput Aided Mol Des 20:343-360
20. Dhaked DK, Verma J, Saran A, Coutinho EC (2009) Exploring the binding of HIV-1 integrase inhibitors by comparative residue interaction analysis (CoRIA). J Mol Model 15:233-245
21. Dunn WJ III, Rogers D (1996) Genetic partial least squares in QSAR. In: Devillers J (ed) Genetic algorithms in molecular modeling. Academic Press, London, pp 109-130
22. Dunteman GH (1989a) Basic concepts of principal components analysis. In: Dunteman GH (ed) Principal components analysis. SAGE Publications Ltd, London, pp 15-22
23. Dunteman GH (1989b) Uses of principal components in regression analysis. In: Dunteman GH (ed) Principal components analysis. SAGE Publications Ltd., London, pp 65-74
24. Fells JI, Tsukahara R, Liu J, Tigyi G, Parrill AL (2010) 2D binary QSAR modeling of LPA3 receptor antagonism. J Mol Graph Model 28:828-833
25. Free SM Jr, Wilson JW (1964) A mathematical contribution to structure-activity studies. J Med Chem 7:395-399
26. Funar-Timofei S, Fabian WMF, Kurunczi L, Goodarzi M, Ali ST, Heyden YV (2012) Modelling heterocyclic azo dye affinities for cellulose fibres by computational approaches. Dyes Pigm 94:278-289
27. Gieleciak R, Polanski J (2007) Modeling robust QSAR. 2. Iterative variable elimination schemes for CoMSA: application for modeling benzoic acid pKa values. J Chem Inf Model 47:547-556
28. Guido RVC, Oliva G, Andricopulo AD (2008) Virtual screening and its integration with modern drug design technologies. Curr Med Chem 15:37-46
29. Hahn M (1995) Receptor surface models. 1. Definition and construction. J Med Chem 38:2080-2090
30. Hammett LP (1935) Some relations between reaction rates and equilibrium constants. Chem Rev 17:125-136
31. Hammett LP (1937) The effect of structure upon the reactions of organic compounds benzene derivatives. J Am Chem Soc 59:96-103
32. Hansch C (1969) Quantitative approach to biochemical structure-activity relationships. Acc Chem Res 2:232-239
33. Hansch C, Fujita T (1964) p-σ-π Analysis. A method for the correlation of biological activity and chemical structure. J Am Chem Soc 86:1616-1626
34. Hansch C, Gao H (1997) Comparative QSAR: radical reactions of benzene derivatives in chemistry and biology. Chem Rev 97:2995-3060
35. Hopfinger A (2001) 4D-QSAR package useŕs manual 3.0. The Chem21 Group Inc, Lake Forest
36. Hopfinger AJ, Tokarski JS (1997) Three-dimensional quantitative structure-activity relationship analysis. In: Charifson P (ed) Practical application of computer-aided drug design. Marcel Dekker, New York, pp 105-164
37. Hopfinger A, Wang S, Tokarski J, Jin B, Albuquerque M, Madhav P, Duraiswami C (1997) Construction of 3D-QSAR models using the 4D-QSAR analysis formalism. J Am Chem Soc 119:10509-10524
38. In Y, Chai HH, No KT (2005) A partition coefficient calculation method with the SFED model. J Chem Inf Model 45:254-263
39. Ivanciuc O, Ivanciuc T, Cabrol-Bass D (2000) 3D quantitative structure activity relationships with CoRSA. Comparative receptor surface analysis. Application to calcium channel agonists. Analysis 28:637-642
40. Jojart B, Martinek TA, Marki A (2005) The 3D structure of the binding pocket of the human oxytocin receptor for benzoxazine antagonists, determined by molecular docking, scoring functions and 3D-QSAR methods. J Comput Aided Mol Des 19:341-356
41. Jorgensen WL, Duffy EM (2002) Prediction of drug solubility from structure. Adv Drug Deliv Rev 54:355-366
42. Katritzky AR, Lobanov VS, Karelson M (1995) QSPR: the correlation and quantitative prediction of chemical and physical properties from structure. Chem Soc Rev 24:279-287
43. Kennedy T (1997) Managing the drug discovery/development interface. Drug Discov Today 2:436-444
44. Khedkar SA, Malde AK, Coutinho EC (2007) Design of inhibitors of the MurF enzyme of Streptococcus pneumoniae using docking, 3DQSAR, and de novo design. J Chem Inf Model 47:1839-1846
45. Kim KH (1995) Comparative molecular field analysis (CoMFA). In: Dean PM (ed) Molecular similarity in drug design. Blackie academic and professional, Glasgow, pp 291-331
46. Koo HM, Monks A, Mikheev A, Rubinstein LV, Gray-Goodrich M, McWilliams MJ, Alvord WG, Oie HK, Gazdar AF, Paull KD, Zarbl H, Vande-Woude GF (1996) Enhanced sensitivity to 1-beta-D-arabinofuranosylcytosine and topoisomerase II inhibitors in tumor cell lines harboring activated RAS oncogenes. Cancer Res 56:5211-5216
47. Korhonen SP, Tuppurainen K, Laatikainen R, Perakyla M (2003) FLUFF-BALL, a template-based grid-independent superposition and QSAR technique: validation using a benchmark steroid data set. J Chem Inf Comput Sci 43:1780-1793
48. Kotani T, Higashiura K (2004) Comparative molecular active site analysis (CoMASA). 1. An approach to rapid evaluation of 3D QSAR. J Med Chem 47:2732-2742
49. Krasowski MD, Hong X, Hopfinger AJ, Harrison NL (2002) 4D-QSAR analysis of a set of propofol analogues: mapping binding sites for an anesthetic phenol on the GABA (A) receptor. J Med Chem 45:3210-3221
50. Kubinyi H (1976) Quantitative structure-activity relationships. IV. Non-linear dependence of biological activity on hydrophobic character: a new model. Arzneimittelforschung 26:1991-1997
51. Kubinyi H (2004) 2D QSAR models: Hansch and Free-Wilson analyses. In: Bultinck P, Winter HD, Langenaeker W, Tollenaere JP (eds) Computational medicinal chemistry for drug discovery. Marcel Dekker, New York, pp 539-570
52. Labute P (1999) Binary QSAR: a new method for the determination of quantitative structure activity relationships. Pac Symp Biocomput 1999:444-455
53. Lee PH, Ayyampalayam SN, Carreira LA, Shalaeva M, Bhattachar S, Coselmon R, Poole S, Gifford E, Lombardo F (2007) In silico prediction of ionization constants of drugs. Mol Pharm 4:498-512
54. Lee AC, Yu JY, Crippen GM (2008) pKa prediction of monoprotic small molecules the SMARTS way. J Chem Inf Model 48:2042-2053
55. Liu HY, Liu SS, Qin LT, Mo LY (2009) CoMFA and CoMSIA analysis of 2,4-thiazolidinediones derivatives as aldose reductase inhibitors. J Mol Model 15:837-845
56. Liu J, Li Y, Zhang S, Xiao Z, Ai C (2011a) Studies of new fused benzazepine as selective dopamine D3 receptor antagonists using 3D-QSAR, molecular docking and molecular dynamics. Int J Mol Sci 12:1196-1221
57. Liu J, Zhang H, Xiao Z, Wang F, Wang X, Wang Y (2011b) Combined 3D-QSAR, molecular docking and molecular dynamics study on derivatives of peptide epoxyketone and tyropeptin-boronic acid as inhibitors against the β5 subunit of human 20S proteasome. Int J Mol Sci 12:1807-1835
58. Lombardino JG, Lowe JA (2004) The role of the medicinal chemist in drug discovery-then and now. Nat Rev Drug Discov 3:853-862
59. Lowe EW Jr, Ferrebee A, Rodriguez AL, Jeffrey-Connc P, Meiler J (2010) 3D-QSAR CoMFA study of benzoxazepine derivatives as mGluR5 positive allosteric modulators. Bioorg Med Chem Lett 20:5922-5924
60. Luo X, Shu S, Wang Y, Liu J, Yang W, Lin Z (2012) 3D-QSAR studies of dihydropyrazole and dihydropyrrole derivatives as inhibitors of human mitotic kinesin Eg5 based on molecular docking. Molecules 17:2015-2029
61. Magdziarz T, Lozowicka B, Gieleciak R, Bak A, Polanski J, Chilmonczyk Z (2006) 3D QSAR study of hypolipidemic asarones by comparative molecular surface analysis. Bioorg Med Chem 14:1630-1643
62. Magdziarz T, Mazur P, Polanski J (2009) Receptor independent and receptor dependent CoMSA modeling with IVE-PLS: application to CBG benchmark steroids and reductase activators. J Mol Model 15:41-51
63. Manly CJ, Louise-May S, Hammer JD (2001) The impact of informatics and computational chemistry on synthesis and screening. Drug Discov Today 6:1101-1110
64. Matyus P, Borosy AP (1998) Three dimensional structure-activity relationships. Acta Pharm Hung 68:33-38
65. Mills EJ (1884) On melting point and boiling point as related to composition. Philos Mag 17:173-187
66. Muller G (2003) Medicinal chemistry of target family-directed masterkeys. Drug Discov Today 8:681-691
67. Murugesan V, Prabhakar YS, Katti SB (2009) CoMFA and CoMSIA studies on thiazolidin-4-one as anti-HIV-1 agents. J Mol Graph Model 27:735-743
68. Nakao K, Fujikawa M, Shimizu R, Akamatsu M (2009) QSAR application for the prediction of compound permeability with in silico descriptors in practical use. J Comput Aided Mol Des 23:309-319
69. Natesan S, Wang T, Lukacova V, Bartus V, Khandelwal A, Subramaniam R, Balaz S (2012) Cellular quantitative structure-activity relationship (Cell-QSAR): conceptual dissection of receptor binding and intracellular disposition in antifilarial activities of selwood antimycins. J Med Chem 55:3699-3712
70. Noolvi MN, Patel HM, Bhardwaj V (2010) 2D QSAR studies on a series of 4-anilino quinazoline derivatives as tyrosine kinase (EGFR) inhibitor: an approach to design anticancer agents. Dig J Nanomater Bios 5:387-401
71. Noolvi MN, Patel HM, Bhardwaj V (2011) A comparative QSAR analysis of quinazoline analogues as tyrosine kinase (erbB-2) inhibitors. Med Chem 7:200-212
72. Norinder U, Bergstrom CAS (2006) Prediction of ADMET properties. ChemMedChem 1:920-937
73. Oprea TI (2004) 3D QSAR modeling in drug design. In: Bultinck P, Winter HD, Langenaeker W, Tollenaere JP (eds) Computational medicinal chemistry for drug discovery. Marcel Dekker, New York, pp 571-616
74. Palmer DS, ÓBoyle NM, Glen RC, Mitchell JBO (2007) Random forest models to predict aqueous solubility. J Chem Inf Model 47:150-158
75. Paull KD, Shoemaker RH, Hodes L, Monks A, Scudiero DA, Rubinstein L, Plowman J, Boyd MR (1989) Display and analysis of patterns of differential activity of drugs against human tumor cell lines: development of mean graph and COMPARE algorithm. J Natl Cancer Inst 81:1088-1092
76. Polanski J, Walczak B (2000) The comparative molecular surface analysis (COMSA): a novel tool for molecular design. Comput Chem 24:615-625
77. Polanski J, Gieleciak R, Bak A (2002) The comparative molecular surface analysis (COMSA) a nongrid 3D QSAR method by a coupled neural network and PLS system: predicting pK(a) values of benzoic and alkanoic acids. J Chem Inf Comput Sci 42:184-191
78. Robinson DD, Winn PJ, Lyne PD, Richards WG (1999) Self-organizing molecular field analysis: a tool for structure-activity studies. J Med Chem 42:573-583
79. Rogers D, Hopfinger AJ (1994) Application of genetic function approximation to quantitative structure-activity relationships and quantitative structure-property relationships. J Chem Inf Comput Sci 34:854-866
80. Salum LB, Andricopulo AD (2009) Fragment-based QSAR: perspectives in drug design. Mol Divers 13:277-285
81. Santos-Filho OA, Hopfinger AJ, Cherkasov A, De-Alencastro RB (2009) The receptor-dependent QSAR paradigm: an overview of the current state of the art. Med Chem 5:359-366
82. Stewart L, Clark R, Behnke C (2002) High-throughput crystallization and structure determination in drug discovery. Drug Discov Today 7:187-196
83. Taft RW (1952) Polar and steric substituent constants for aliphatic and o-benzoate groups from rates of esterification and hydrolysis of esters 1. J Am Chem Soc 74:3120-3128
84. Thipnate P, Liu J, Hannongbua S, Hopfinger AJ (2009) 3D pharmacophore mapping using 4D QSAR analysis for the cytotoxicity of lamellarins against human hormone-dependent T47D breast cancer cells. J Chem Inf Model 49:2312-2322
85. Tian Y, Xu J, Li Z, Zhu Z, Zhang J, Wu S (2011) Combined 3D-QSAR and docking modelling study on indolocarbazole series compounds as Tie-2 inhibitors. Int J Mol Sci 12:5080-5097
86. Ul-Haq Z, Wadood A, Uddin R (2009) CoMFA and CoMSIA 3D-QSAR analysis on hydroxamic acid derivatives as urease inhibitors. J Enzy Inhib Med Chem 24:272-278
87. Van Daele I, Munier-Lehmann H, Froeyen M, Balzarini J, Van Calenbergh S (2007) Rational design of 5-thiourea-substituted alpha-thymidine analogues as thymidine monophosphate kinase inhibitors capable of inhibiting mycobacterial growth. J Med Chem 50:5281-5292
88. Verma J, Khedkar VM, Prabhu AS, Khedkar SA, Malde AK, Coutinho EC (2008) A comprehensive analysis of the thermodynamic events involved in ligand-receptor binding using CoRIA and its variants. J Comput Aided Mol Des 22:91-104
89. VLifeMDS 3.0 (2007) Molecular design suite developed by VLife Sciences Technologies Pvt Ltd. VLife Sciences Technologies Pvt Ltd., Pune
90. Walczak B, Massart DL (2000) Local modeling with radial basis function networks. Chemom Intell Lab Syst 50:179-198
91. Walpole CS, Wrigglesworth R, Bevan S, Campbell EA, Dray A, James IF, Masdin KJ, Perkins MN, Winter J (1993) Analogues of capsaicin with agonist activity as novel analgesic agents; structure-activity studies 3. The hydrophobic side-chain "C-region". J Med Chem 36:2381-2389
92. Wang J, Krudy G, Hou T, Zhang W, Holland G, Xu X (2007) Development of reliable aqueous solubility models and their application in drug like analysis. J Chem Inf Model 47:1395-1404
93. Weinstein JN, Myers T, Buolamwini J, Raghavan K, Van Osdol W, Licht J, Viswanadhan VN, Kohn KW, Rubinstein LV, Koutsoukos AD, Monks A, Scudiero DA, Anderson NL, Zaharevitz D, Chabner BA, Grever MR, Paull KD (1994) Predictive statistics and artificial intelligence in the US National Cancer Institutés drug discovery program for cancer and AIDS. Stem Cells 12:13-22
94. Wise M, Cramer RD, Smith D, Exman I (1983) Progress in three-dimensional drug design: the use of real time colour graphics and computer postulation of bioactive molecules in DYLOMMS. In: Dearden J (ed) Quantitative approaches to drug design. Elsevier, Amsterdam, pp 145-146
95. Wold S, Johansson E, Cocchi M (1993) PLS: partial least squares projections to latent structures. In: Kubinyi H (ed) 3D QSAR in drug design: theory, methods and applications. ESCOM Science Publishers, Leiden, pp 523-550
96. Yadav DK, Meena A, Srivastava A, Chanda D, Khan F, Chattopadhyay SK (2010) Development of QSAR model for immunomodulatory activity of natural coumarinolignoids. Drug Des Devel Ther 4:173-186
97. Yang S, Chang S, Chen H, Chen CY (2011) Identification of potent EGFR inhibitors from TCM Database@Taiwan. PLoS Comput Biol 7:e1002189
98. Zhang B, Li Y, Zhang H, Ai C (2010) 3D-QSAR and molecular docking studies on derivatives of MK-0457, GSK1070916 and SNS-314 as inhibitors against Aurora B Kinase. Int J Mol Sci 11:4326-4347
99. Zhao H (2007) Scaffold selection and scaffold hopping in lead generation: a medicinal chemistry perspective. Drug Discov Today 12:149-155
100. Zhao YH, Abraham MH, Ibrahim A, Fish PV, Cole S, Lewis ML, De Groot MJ, Reynolds DP (2007) Predicting penetration across the blood-brain barrier from simple descriptors and fragmentation schemes. J Chem Inf Model 47:170-175
101. Zhou P, Tong J, Tian F, Li Z (2006) A novel comparative molecule/pseudo receptor interaction analysis. Chin Sci Bull 51:1824-1829
102. Zhu YQ, Lei M, Lu AJ, Zhao X, Yin XJ, Gao QZ (2009) 3D-QSAR studies of boron-containing dipeptides as proteasome inhibitors with CoMFA and CoMSIA methods. Eur J Med Chem 44:1486-1499