Contribution of 2D and 3D structural features of drug molecules in the prediction of drug profile matching

Journal of Chemical Information and Modeling

Volumn 52, Issue 7, 2012, Pages 1733-1744

  Peragovics, Ágnes ^a,b   Simon, Zoltán ^b   Brandhuber, Ildikó ^b   Jelinek, Balázs ^a,b   Hári, Péter ^b   Hetényi, Csaba ^a   Czobor, Pál ^c   Málnási Csizmadia, András ^a,b  

^a EÖTVÖS LORÁND UNIVERSITY   (Hungary)

^b Drugmotif Ltd   (Hungary)

^c SEMMELWEIS UNIVERSITY   (Hungary)

Author keywords

[No Author keywords available]

Indexed keywords

DIAGNOSIS; FORECASTING;

DRUG MOLECULES; FINGERPRINTING METHODS; FLEXIBLE DOCKING; INFORMATION CONTENTS; INTERACTION PATTERN; PREDICTIVE POWER; SMALL MOLECULES; STRUCTURAL FEATURE;

MOLECULES;

ARTICLE; CHEMISTRY; DRUG DESIGN; FORECASTING; MOLECULAR LIBRARY; MEDICINAL CHEMISTRY;

CHEMISTRY, PHARMACEUTICAL; DRUG DESIGN; FORECASTING; SMALL MOLECULE LIBRARIES;

MOLECULAR LIBRARY;

EID: 84864258396     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci3001056     Document Type: Article

References (29)

1. Ripphausen, P.; Nisius, B.; Peltason, L.; Bajorath, J. Quo vadis, virtual screening? A comprehensive survey of prospective applications J. Med. Chem. 2010, 53, 8461-8467
2. Eckert, H.; Bajorath, J. Molecular similarity analysis in virtual screening: foundations, limitations and novel approaches Drug Discovery Today 2007, 12, 225-233
3. Willett, P. Chemical similarity searching J. Chem. Inf. Comput. Sci. 1998, 38, 983-996 (Pubitemid 128591261)
4. Willett, P. Similarity-based virtual screening using 2D fingerprints Drug Discovery Today 2006, 11, 1046-1053 (Pubitemid 44792477)
5. Nettles, J. H.; Jenkins, J. L.; Bender, A.; Deng, Z.; Davies, J. W.; Glick, M. Bridging chemical and biological space: "target fishing" using 2D and 3D molecular descriptors J. Med. Chem. 2006, 49, 6802-6810 (Pubitemid 44749747)
6. Venkatraman, V.; Perez-Nueno, V. I.; Mavridis, L.; Ritchie, D. W. Comprehensive comparison of ligand-based virtual screening tools against the DUD data set reveals limitations of current 3D methods J. Chem. Inf. Model. 2010, 50, 2079-2093
7. Briem, H.; Lessel, U. F. In vitro and in silico affinity fingerprints: Finding similarities beyond structural classes Perspect. Drug Discovery Des. 2000, 20, 231-244
8. Kauvar, L. M.; Higgins, D. L.; Villar, H. O.; Sportsman, J. R.; Engqvist-Goldstein, A.; Bukar, R.; Bauer, K. E.; Dilley, H.; Rocke, D. M. Predicting ligand binding to proteins by affinity fingerprinting Chem. Biol. 1995, 2, 107-118
9. Kauvar, L. M.; Villar, H. O.; Sportsman, J. R.; Higgins, D. L.; Schmidt, D. E., Jr. Protein affinity map of chemical space J. Chromatogr., B: Biomed. Sci. Appl. 1998, 715, 93-102 (Pubitemid 28403602)
10. Bender, A.; Jenkins, J. L.; Glick, M.; Deng, Z.; Nettles, J. H.; Davies, J. W. "Bayes affinity fingerprints" improve retrieval rates in virtual screening and define orthogonal bioactivity space: When are multitarget drugs a feasible concept? J. Chem. Inf. Model. 2006, 46, 2445-2456 (Pubitemid 46008117)
11. Bender, A.; Scheiber, J.; Glick, M.; Davies, J. W.; Azzaoui, K.; Hamon, J.; Urban, L.; Whitebread, S.; Jenkins, J. L. Analysis of pharmacology data and the prediction of adverse drug reactions and off-target effects from chemical structure ChemMedChem. 2007, 2, 861-873
12. Briem, H.; Kuntz, I. D. Molecular similarity based on DOCK-generated fingerprints J. Med. Chem. 1996, 39, 3401-3408 (Pubitemid 26322866)
13. Lessel, U. F.; Briem, H. Flexsim-X: A method for the detection of molecules with similar biological activity J. Chem. Inf. Comput. Sci. 2000, 40, 246-253
14. Fukunishi, Y.; Hojo, S.; Nakamura, H. An efficient in silico screening method based on the protein-compound affinity matrix and its application to the design of a focused library for cytochrome P450 (CYP) ligands J. Chem. Inf. Model. 2006, 46, 2610-2622 (Pubitemid 46008132)
15. Fukunishi, Y.; Mikami, Y.; Takedomi, K.; Yamanouchi, M.; Shima, H.; Nakamura, H. Classification of chemical compounds by protein-compound docking for use in designing a focused library J. Med. Chem. 2006, 49, 523-533 (Pubitemid 43157486)
16. Simon, Z.; Peragovics, A.; Vigh-Smeller, M.; Csukly, G.; Tombor, L.; Yang, Z.; Zahoranszky-Kohalmi, G.; Vegner, L.; Jelinek, B.; Hari, P.; Hetenyi, C.; Bitter, I.; Czobor, P.; Malnasi-Csizmadia, A. Drug effect prediction by polypharmacology-based interaction profiling J. Chem. Inf. Model. 2012, 52, 134-145
17. Simon, Z.; Vigh-Smeller, M.; Peragovics, A.; Csukly, G.; Zahoranszky-Kohalmi, G.; Rauscher, A. A.; Jelinek, B.; Hari, P.; Bitter, I.; Malnasi-Csizmadia, A.; Czobor, P. Relating the shape of protein binding sites to binding affinity profiles: is there an association? BMC Struct. Biol. 2010, 10, 32
18. Hetenyi, C.; Maran, U.; Karelson, M. A comprehensive docking study on the selectivity of binding of aromatic compounds to proteins J. Chem. Inf. Comput. Sci. 2003, 43, 1576-1583
19. Jiang, X.; Kumar, K.; Hu, X.; Wallqvist, A.; Reifman, J. DOVIS 2.0: an efficient and easy to use parallel virtual screening tool based on AutoDock 4.0 Chem. Cent. J. 2008, 2, 18
20. Huey, R.; Morris, G. M.; Olson, A. J.; Goodsell, D. S. A semiempirical free energy force field with charge-based desolvation J. Comput. Chem. 2007, 28, 1145-1152 (Pubitemid 46506716)
21. Wang, R.; Lai, L.; Wang, S. Further development and validation of empirical scoring functions for structure-based binding affinity prediction J. Comput.-Aided. Mol. Des. 2002, 16, 11-26 (Pubitemid 34855041)
22. 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, 2534-2547 (Pubitemid 40520517)
23. Chang, M. W.; Ayeni, C.; Breuer, S.; Torbett, B. E. Virtual screening for HIV protease inhibitors: A comparison of AutoDock 4 and Vina PLoS One. 2010, 5, e11955
24. 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, 488-508 (Pubitemid 46615951)
25. Schuffenhauer, A.; Floersheim, P.; Acklin, P.; Jacoby, E. Similarity metrics for ligands reflecting the similarity of the target proteins J. Chem. Inf. Comput. Sci. 2003, 43, 391-405
26. Xue, L.; Stahura, F. L.; Godden, J. W.; Bajorath, J. Fingerprint scaling increases the probability of identifying molecules with similar activity in virtual screening calculations J. Chem. Inf. Comput. Sci. 2001, 41, 746-753
27. Brown, R. D.; Martin, Y. C. The information content of 2D and 3D structural descriptors relevant to ligand-receptor binding J. Chem. Inf. Comput. Sci. 1997, 37, 1-9 (Pubitemid 127601574)
28. Roy, K.; Roy, P. P. Comparative QSAR studies of CYP1A2 inhibitor flavonoids using 2D and 3D descriptors Chem. Biol. Drug Des. 2008, 72, 370-382
29. Koutsoukas, A.; Simms, B.; Kirchmair, J.; Bond, P. J.; Whitmore, A. V.; Zimmer, S.; Young, M. P.; Jenkins, J. L.; Glick, M.; Glen, R. C.; Bender, A. From in silico target prediction to multi-target drug design: current databases, methods and applications J. Proteomics. 2011, 74, 2554-2574