Template CoMFA generates single 3D-QSAR models that, for twelve of twelve biological targets, predict all ChEMBL-tabulated affinities

PLoS ONE

Volumn 10, Issue 6, 2015, Pages

  Cramer, Richard D ^a  

^a CERTARA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

4 AMINOBUTYRIC ACID A RECEPTOR; BETA SECRETASE; BLOOD CLOTTING FACTOR 10A; CARBONATE DEHYDRATASE II; CHECKPOINT KINASE 2; CYCLIN DEPENDENT KINASE 1; CYCLOOXYGENASE 2; CYTOCHROME P450 3A4; DOPAMINE 2 RECEPTOR; HORMONE RECEPTOR; POTASSIUM CHANNEL HERG; PROTEIN TYROSINE PHOSPHATASE 1B; ENZYME INHIBITOR; LIGAND; MEMBRANE PROTEIN; MOLECULAR LIBRARY;

ARTICLE; BINDING AFFINITY; COMPARATIVE MOLECULAR FIELD ANALYSIS; COMPUTER AIDED DESIGN; COMPUTER PREDICTION; CONTROLLED STUDY; LIGAND BINDING; MATHEMATICAL MODEL; MEASUREMENT ACCURACY; METHODOLOGY; NULL HYPOTHESIS; PROTEIN BINDING; PROTEIN PROTEIN INTERACTION; PROTEIN TARGETING; QUANTITATIVE STRUCTURE ACTIVITY RELATION; RECEPTOR AFFINITY; X RAY CRYSTALLOGRAPHY; AGONISTS; AMINO ACID SEQUENCE; ANTAGONISTS AND INHIBITORS; CHEMISTRY; MOLECULAR GENETICS; MOLECULAR LIBRARY; PHARMACOLOGY; SOFTWARE;

AMINO ACID SEQUENCE; ENZYME INHIBITORS; LIGANDS; MEMBRANE PROTEINS; MOLECULAR SEQUENCE DATA; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; SMALL MOLECULE LIBRARIES; SOFTWARE;

EID: 84935518395     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0129307     Document Type: Article

References (32)

1. Besnard J, Ruda GF, Setola V, Abecassis K, Rodriguiz R, Huang X-P, et al. Automated design of ligands to polypharmacological profiles. Nature 2012; 492:215-220 doi: 10.1038/nature11691 PMID: 23235874
2. Lounkine E, Keiser MJ, Whitebread S, Mikhailov D, Hamon J, Jenkins J, et al. Large-scale prediction and testing of drug activity on side-effect targets. Nature 2013; 486:361-367
3. Stouch TR. The errors of our ways: taking account of error in computer-aided drug design to build confidence intervals for our next 25 years. J Comp-Aided Mol Des. 2012; 26:125-134 doi: 10.1007/s10822-012-9541-6 PMID: 22246296
4. Warren GL, Andrews CW, Capelli A-M, Head MS. A Critical Assessment of Docking Programs and Scoring Functions. J Med Chem. 2006; 49:5912-5931 PMID: 17004707
5. Cherkasov A, Muratov RN, Fourches D, Varnek A, Baskin II, Cronin M, et al. QSAR Modeling: Where Have You Been? Where Are You Going To? J Med Chem. 2014; 57: 4977-5010 doi: 10.1021/jm4004285 PMID: 24351051
6. Bender A, Glen RC. Molecular similarity: a key technique in molecular informatics. Org Biomol Chem. 2004; 2:3204-3218 PMID: 15534697
7. Hert I, Irwin JJ, Keiser MJ,Shoichet BK. Quantifying biogenic bias in screening libraries. Nature Chem Biol. 2009; 5:479-483 doi: 10.1038/nchembio.180 PMID: 19483698
8. Kubinyi H. 3D Qsar in Drug Design: Volume 1: Theory Methods and Applications. Vol. 1. Springer, 1993
9. Oprea TI, Waller C. Theoretical and Practical Aspects of Three-Dimensional Quantitative Structure-Activity Relationships. In: Lipkowitz KB, Boyd DB, editors. Reviews in Computational Chemistry, Volume 11, Wiley-VCH, 2007
10. Cramer RD, Patterson DE, Bunce J. Comparative Molecular Field Analysis (CoMFA). 1. Effect of Shape on Binding of Steroids to Carrier Proteins. J Am Chem Soc. 1988; 110:5939-5967
11. Cramer RD, Clark RD, Patterson DE, Ferguson AM. Bioisosterism as a molecular diversity descriptor: steric fields of single topomeric conformers. J Med Chem. 1996; 39:3060-3069 PMID: 8759627
12. Cramer RD. Topomer CoMFA: A Design Methodology for Rapid Lead Optimization. J Med Chem. 2003; 46:374-389 PMID: 12540237
13. Cramer RD, Wendt B. Template CoMFA: The 3D-QSAR Grail? J Chem Inf Model. 2014; 54:660-671 doi: 10.1021/ci400696v PMID: 24437630
14. Jilek R, Cramer RD. Topomers: A Validated Protocol for their Self-Consistent Generation. J Chem Inf Model. 2004; 44:1221-1227
15. Cramer RD. Template CoMFA applied to 114 Biological Targets. J Chem Inf Model. 2014; 57:2147-2156
16. Wendt B, Cramer RD. Challenging the Gold Standard for 3D-QSAR: Template CoMFA versus X-ray Alignment. J. Comp-Aided Mol Des. 2014; 28:803-824 doi: 10.1007/s10822-014-9761-z PMID: 24934658
17. https://www.ebi.ac.uk/chembl/
18. http://www.bindingdb.org/validation-sets/index.jsp
19. SYBYL-X 2.2 2014. Certara, St. Louis. http://www.certara.com/products/molmod/sybyl-x. Enquiries may be directed to Brian.Masek@certara.com.
20. Jain AN. Ligand-Based Structural Hypotheses for Virtual Screenin. J Med Chem. 2004; 47:947-961 PMID: 14761196
21. Jain AN. Surflex: Fully Automatic Flexible Molecular Docking using a Molecular Similarity-Based Search Engine. J Med Chem. 2003; 46:499-511 PMID: 12570372
22. Rusinko A, et al. CONCORD, A Program for the Rapid Generation of High Quality Approximate 3-dimensional Molecular Structures. 1988. Tripos Associates, St. Louis
23. Hopkins AL, Keseru GM, Leeson PD, Rees DC, Reynolds CH. The role of ligand efficiency metrics inn drug discovery. Nature Rev Drug Disc. 2014; 13:105-121 doi: 10.1038/nrd4163 PMID: 24481311
24. Bender A, Glen RC. A Discussion of Measures of Enrichment in Virtual Screening: Comparing the Information Content of Descriptors with Increasing Levels of Sophistication. J Chem Inf Model. 2000; 45:1369-1375
25. Willett P. Similarity-based virtual screening using 2D fingerprints. Drug Disc Today. 2007; 11:1046-1053
26. Keiser MJ, Roth BL, Armbruster BN, Ernsberger P, Shoichet BK. Relating protein pharmacology by ligand chemistry. Nature Biotech. 2007; 25:197-206
27. Boulesteix AL, Strimmer A. Partial least squares: a versatile tool for the analysis of high-dimensional genomic data. Brief Bioinform. 2007; 8:32-44 PMID: 16772269
28. Golbraikh A, Tropsha A. Beware of q2!. J Mol Graph Model. 2002;269-276 PMID: 11858635
29. Clark RD, Fox PC. Statistical variation in progressive scrambling. J Comp-Aided Mol Des. 2004; 18:563-576
30. Motlaw HJ, Wrabi JL, Hilser V.The ensemble nature of allostery. Nature 2014; 508:331-336 doi: 10.1038/nature13001 PMID: 24740064
31. Cramer RD. Rethinking 3D-QSAR. J Comp-Aided Mol Des. 2011; 25:197-201.
32. Clark M, Cramer R. The Probability of Chance Correlation Using Partial Least Squares (PLS). Quant Struct-Act Relat. 1993, 1:269-278