DrugLogit: Logistic discrimination between drugs and nondrugs including disease-specificity by assigning probabilities based on molecular properties

Journal of Chemical Information and Modeling

Volumn 52, Issue 8, 2012, Pages 2165-2180

  García Sosa, Alfonso T ^a   Oja, Mare ^a   Hetényi, Csaba ^b   Maran, Uko ^a  

^a UNIVERSITY OF TARTU   (Estonia)

^b INSTITUTE OF EXPERIMENTAL MEDICINE   (Hungary)

Author keywords

[No Author keywords available]

Indexed keywords

BIOCHEMISTRY; LIBRARIES; LIGANDS; MOLECULAR BIOLOGY;

CLASSIFICATION FUNCTIONS; CONFIDENCE INTERVAL; MOLECULAR PROPERTIES; MULTIVARIATE LOGISTIC REGRESSIONS; ORAL BIOAVAILABILITIES; PHARMACOLOGICAL CHARACTERIZATION; STATISTICAL SIGNIFICANCE; STRUCTURE AND ACTIVITIES;

LOGISTIC REGRESSION;

DRUG; LIGAND;

ANTIBODY SPECIFICITY; ARTICLE; CHEMICAL STRUCTURE; CHEMISTRY; CLASSIFICATION; CONFORMATION; DISCRIMINANT ANALYSIS; DISEASES; DRUG DATABASE; HUMAN; MULTIVARIATE ANALYSIS; PROBABILITY; STATISTICAL MODEL;

DATABASES, PHARMACEUTICAL; DISCRIMINANT ANALYSIS; DISEASE; HUMANS; LIGANDS; LOGISTIC MODELS; MODELS, MOLECULAR; MOLECULAR CONFORMATION; MULTIVARIATE ANALYSIS; ORGAN SPECIFICITY; PHARMACEUTICAL PREPARATIONS; PROBABILITY;

EID: 84865457697     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci200587h     Document Type: Article

References (90)

1. Paolini, G. V.; Shapland, R. H.; van Hoorn, W. P.; Mason, J. S.; Hopkins, A. L. Global mapping of pharmacological space Nat. Biotechnol. 2006, 24, 805-815 (Pubitemid 44086621)
2. Yildirim, M. A.; Goh, K. I.; Cusick, M. E.; Barabasi, A. L.; Vidal, M. Drug-target network Nat. Biotechnol. 2007, 25, 1119-1126 (Pubitemid 47538114)
3. Hert, J.; Keiser, M. J.; Irwin, J. J.; Oprea, T. I.; Shoichet, B. Quantifying the relationships among drug classes J. Chem. Inf. Model. 2008, 48, 755-765 (Pubitemid 351757743)
4. Keiser, M. J.; Irwin, J. J.; Shoichet, B. K. The chemical basis of pharmacology Biochemistry 2010, 49, 10267-10276
5. García-Sosa, A. T.; Maran, U.; Hetényi, C. Molecular property filters describing pharmacokinetics and drug binding Curr. Med. Chem. 2012, 19, 1646-1662
6. Ursu, O.; Rayan, A.; Goldblum, A.; Oprea, T. I. Understanding drug-likeness Wiley Interdiscip. Rev.: Comput. Mol. Sci. 2011, 1, 760-781
7. Lipinski, C. A.; Lombardo, F.; Dominy, B. W.; Feeney, P. J. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings Adv. Drug Delivery Rev. 1997, 23, 3-25 (Pubitemid 27046991)
8. Ajay; Walters, W. P.; Murcko, M. A. Can we learn to distinguish between "drug-like" and "nondrug-like" molecules? J. Med. Chem. 1998, 41, 3314-3324 (Pubitemid 28406538)
9. Sadowski, J.; Kubinyi, H. A scoring scheme for discriminating between drugs and nondrugs J. Med. Chem. 1998, 41, 3325-3329 (Pubitemid 28406539)
10. Clark, D. E.; Pickett, S. D. Computational methods for the prediction of 'drug-likeness' Drug Discovery Today 2000, 5, 49-58
11. Ajay Predicting drug-likeness: Why and how? Curr. Top. Med. Chem. 2002, 2, 1273-1286
12. Muegge, I. Selection criteria for drug-like compounds Med. Res. Rev. 2003, 23, 302-321 (Pubitemid 36457537)
13. Oprea, T. I.; Davis, A. M.; Teague, S. J.; Leeson, P. D. Is there a difference between leads and drugs? A historical perspective J. Chem. Inf. Comput. Sci. 2001, 41, 1308-1315
14. Ritchie, T. J.; Macdonald, S. J. F. The impact of aromatic ring count on compound developability - Are too many rings a liability in drug design ? Drug Discovery Today 2009, 14, 1011-1020
15. Chen, H. M.; Yang, Y. D.; Engkvist, O. Molecular topology analysis of the differences between drugs, clinical candidate compounds, and bioactive molecules J. Chem. Inf. Model. 2010, 50, 2141-2150
16. Bemis, G. W.; Murcko, M. A. The properties of known drugs. 1. Molecular frameworks J. Med. Chem. 1996, 39, 2887-2893 (Pubitemid 26251026)
17. Yang, Y. D.; Chen, H. M.; Nilsson, I.; Muresan, S.; Engkvist, O. Investigation of the relationship between topology and selectivity for druglike molecules J. Med. Chem. 2010, 53, 7709-7714
18. Gillet, V. J.; Willett, P.; Bradshaw, J. Identification of biological activity profiles using substructural analysis and genetic algorithms J. Chem. Inf. Comput. Sci. 1998, 38, 165-179 (Pubitemid 128591234)
19. Gálvez, J.; de Julián-Ortiz, J. V.; García-Domenech, R. General topological patterns of known drugs J. Mol. Graphics Modell. 2001, 20, 84-94 (Pubitemid 32938280)
20. Ajay Predicting drug-likeness: Why and how? Curr. Top. Med. Chem. 2002, 2, 1273-1286
21. Batista, J.; Bajorath, J. Mining of randomly generated molecular fragment populations uncovers activity-specific fragment hierarchies J. Chem. Inf. Model. 2007, 47, 1405-1413 (Pubitemid 47210044)
22. Hu, Y.; Bajorath, J. Scaffold distributions in bioactive molecules, clinical trials, and drugs ChemMedChem 2010, 5, 187-190
23. Wang, J. M.; Hou, T. J. Drug and drug candidate building block analysis J. Chem. Inf. Model. 2010, 50, 55-67
24. Schneider, N.; Jäckels, C.; Andres, C.; Hutter, M. C. Gradual in silico filtering for druglike substances J. Chem. Inf. Model. 2008, 48, 613-628 (Pubitemid 351535429)
25. Brüstle, M.; Beck, B.; Schindler, T.; King, W.; Mitchell, T.; Clark, T. Descriptors, physical properties, and drug-likeness J. Med. Chem. 2002, 45, 3345-3355 (Pubitemid 34824024)
26. Lee, M. L.; Schneider, G. Scaffold architecture and pharmacophoric properties of natural products and trade drugs: Application in the design of natural product-based combinatorial libraries J. Comb. Chem. 2001, 3, 284-289 (Pubitemid 33616450)
27. Wenlock, M. C.; Austin, R. P.; Barton, P.; Davis, A. M.; Leeson, P. D. A comparison of physicochemical properties of development and marketed oral drugs J. Med. Chem. 2003, 46, 1250-1256 (Pubitemid 36428230)
28. Leeson, P. D.; Springthorpe, B. The influence of drug-like concepts on decision-making in medicinal chemistry Nat. Rev. Drug Discovery 2007, 6, 881-890 (Pubitemid 350042396)
29. Tyrchan, C.; Blomberg, N.; Engkvist, O.; Kogej, T.; Muresan, S. Physicochemical property profiles of marketed drugs, clinical candidates, and bioactive compounds Bioorg, Med. Chem. Lett. 2009, 19, 6943-6947
30. Oprea, T. I.; Gottfries, J. Chemography: The art of navigating chemical space J. Comb. Chem. 2001, 3, 137-166
31. Abad-Zapatero, C.; Perisic, O.; Wass, J.; Bento, A. P.; Overington, J.; Al-Lazikani, B.; Johnson, M. E. Ligand efficiency indices for an effective mapping of chemico-biological space: the concept of an atlas-like representation Drug Discovery Today 2010, 15, 804-811
32. Dobson, C. M. Chemical space and biology Nature 2004, 432, 824-828 (Pubitemid 40037137)
33. Vieth, M.; Sutherland, J. J. Dependence of molecular properties on proteomic family for marketed oral drugs J. Med. Chem. 2006, 49, 3451-3453 (Pubitemid 43902452)
34. Hopkins, A. L.; Paolini, G. V. Chemogenomics in Drug Discovery - The Druggable Genome and Target Class Properties. In Comprehensive Medicinal Chemistry II, 4 (Computer-Assisted Drug Design); Mason, J. S., Ed.; Elsevier: Amsterdam, The Netherlands, 2007; pp 421-433.
35. Mestres, J.; Martín-Couce, L.; Gregori-Puigjané, E.; Cases, M.; Boyer, S. Ligand-based approach to in silico pharmacology: Nuclear receptor profiling J. Chem. Inf. Model. 2006, 46, 2725-2736 (Pubitemid 46008141)
36. Sutherland, J. J.; Higgs, R. E.; Watson, I.; Vieth, M. Chemical fragments as foundations for understanding target space and activity prediction J. Med. Chem. 2008, 51, 2689-2700 (Pubitemid 351620791)
37. Sprous, D. G.; Palmer, K.; Swanson, J. T.; Lawless, M. QSAR in the pharmaceutical research setting: QSAR models for broad, large problems Curr. Top. Med. Chem. 2010, 10, 619-637
38. Jacob, L.; Hoffman, B.; Stoven, V.; Vert, J. P. Virtual screening of GPCRs: An in silico chemogenomics approach BMC Bioinformatics 2008, 9, 363
39. Strömbergsson, H.; Kleywegt, G. J. A chemogenomics view on protein-ligand spaces BMC Bioinformatics 2009, 10 (suppl 6) S13
40. Byvatov, E.; Fechner, U.; Sadowski, J.; Schneider, G. Comparison of support vector machine and artificial neural network systems for drug/nondrug classification J. Chem. Inf. Comput. Sci. 2003, 43, 1882-1889
41. Savchuk, N. P.; Balakin, K. V.; Tkachenko, S. E. Exploring the chemogenomic knowledge space with annotated chemical libraries Curr. Opin. Chem. Biol. 2004, 8, 412-417 (Pubitemid 38993735)
42. Kuhn, M.; Campillos, M.; González, P.; Jensen, L. J.; Bork, P. Large-scale prediction of drug-target relationships FEBS Lett. 2008, 582, 1283-1290
43. Bender, A.; Young, D. W.; Jenkins, J. L.; Serrano, M.; Mikhailov, D.; Clemons, P. A.; Davies, J. W. Chemogenomic data analysis: Prediction of small-molecule targets and the advent of biological fingerprint Comb. Chem. High Throughput Screening 2007, 10, 719-731 (Pubitemid 350099316)
44. Young, D. W.; Bender, A.; Hoyt, J.; McWhinnie, E.; Chirn, G. W.; Tao, C. Y.; Tallarico, J. A.; Labow, M.; Jenkins, J. L.; Mitchison, T. J.; Feng, Y. Integrating high-content screening and ligand-target prediction to identify mechanism of action Nat. Chem. Biol. 2008, 4, 59-68 (Pubitemid 350273652)
45. Nidhi; Glick, M.; Davies, J. W.; Jenkins, J. L. Prediction of biological targets for compounds using multiple-category Bayesian models trained on chemogenomics databases J. Chem. Inf. Model. 2006, 46, 1124-1133 (Pubitemid 43999157)
46. Azzaoui, K.; Hamon, J.; Faller, B.; Whitebread, S.; Jacoby, E.; Bender, A.; Jenkins, J. L.; Urban, L. Modeling promiscuity based on in vitro safety pharmacology profiling data ChemMedChem 2007, 2, 874-880
47. Gregori-Puigjané, E.; Mestres, J. Coverage and bias in chemical library design Curr. Opin. Chem. Biol. 2008, 12, 359-365
48. 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, 197-206 (Pubitemid 46227119)
49. Keiser, M. J.; Setola, V.; Irwin, J. J.; Laggner, C.; Abbas, A. I.; Hufeisen, S. J.; Jensen, N. H.; Kuijer, M. B.; Matos, R. C.; Tran, T. B.; Whaley, R.; Glennon, R. A.; Hert, J.; Thomas, K. L.; Edwards, D. D.; Shoichet, B. K.; Roth, B. L. Predicting new molecular targets for known drugs Nature 2009, 462, 175-181
50. Cases, M.; Mestres, J. A chemogenomic approach to drug discovery: Focus on cardiovascular diseases Drug Discovery Today 2009, 14, 479-485
51. Gregori-Puigjané, E.; Mestres, J. A ligand-based approach to mining the chemogenomic space of drugs Comb. Chem. High Throughput Screening 2008, 11, 669-676
52. Campillos, M.; Kuhn, M.; Gavin, A.-C.; Jensen, L. J.; Bork, P. Drug target identification using side-effect similarity Science 2008, 321, 262-266
53. Oprea, T. I.; Bauman, J. E.; Bologa, C. G.; Buranda, T.; Chigaev, A.; Edwards, B. S.; Jarvik, J. W.; Gresham, H. D.; Haynes, M. K.; Hjelle, B.; Hromas, R.; Hudson, L.; Mackenzie, D. A.; Muller, C. Y.; Reed, J. C.; Simons, P. C.; Smagley, Y.; Strouse, J.; Surviladze, Z.; Thompson, T.; Ursu, O.; Waller, A.; Wandinger-Ness, A.; Winter, S. S.; Wu, Y.; Young, S. M.; Larson, R. S.; Willman, C.; Sklar, L. A. Drug repurposing from an academic perspective Drug Discovery Today: Ther. Strategies 2011, 8, 61-69
54. Taboureau, O.; Nielsen, S. K.; Adouze, K.; Weinhold, N.; Edsgärd, D.; Roque, F. S.; Kouskoumvekaki, I.; Bora, A.; Curpan, R.; Jensen, T. S.; Brunak, S.; Oprea, T. I. ChemProt: A disease chemical biology database Nucleic Acids Res. 2011, 39, D367-D372
55. Walters, W. P.; Green, J.; Weiss, J. R.; Murcko, M. A. What do medicinal chemists actually make? A 50-year retrospective J. Med. Chem. 2011, 54, 6405-6416
56. Curtis, C. The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups Nature 2012, 10.1038/nature10983
57. Agresti, A. An introduction to Categorical Data Analysis. In Wiley Series in Probability and Statistics: Applied Probability and Statistics. Wiley: New York, 1996.
58. Kokko, H. In Modelling for Field Biologists and Other Interesting People. Cambridge University Press: Cambridge, UK, 2007.
59. García-Sosa, A. T.; Mancera, R. L.; Dean, P. M. WaterScore: A novel method for distinguishing between bound and displaceable water molecules in the crystal structure of the binding site of protein-ligand complexes J. Mol. Model. 2003, 9, 172-182 (Pubitemid 37240075)
60. Givechi, A.; Schneider, G. Impact of descriptor scaling on the classification of drugs and nondrugs with artificial neural networks J. Mol. Model. 2004, 10, 204-211 (Pubitemid 38821256)
61. Schmidtke, P.; Barril, X. Understanding and predicting druggablity. A high-throughput method for detection of binding sites J. Med. Chem. 2010, 53, 5858-5867
62. García-Sosa, A. T.; Oja, M.; Hetényi, C.; Maran, U. Disease-specific differentiation between drugs and non-drugs using principal component analysis of their molecular descriptor space Mol. Inf. 2012, 31, 369-383
63. Kirkpatrick, P. Medicinal chemistry: Shades of chemical beauty Nat. Rev. Drug Discovery 2012, 11, 107-107
64. Bickerton, G. R.; Paolini, G. V.; Besnard, J.; Muresan, S.; Hopkins, A. L. Quantifying the chemical beauty of drugs Nat. Chem. 2012, 4, 90-95
65. Wang, R.; Fang, X.; Lu, Y.; Wang, S. The PDBbind database: Collection of binding affinities for protein-ligand complexes with known three-dimensional structures J. Med. Chem. 2004, 47, 2977-2980 (Pubitemid 38702694)
66. Ababou, A.; Ladbury, J. E. Survey of the year 2005: Literature on applications of isothermal titration calorimetry J. Mol. Recognit. 2007, 20, 4-14 (Pubitemid 46160155)
67. Zhang, J.-W; Aizawa, M.; Amari, S.; Iwasawa, Y.; Nakano, T.; Nakata, K. Development of KiBank, a database supporting structure-based drug design Comput. Biol. Chem. 2004, 28, 401-407
68. Wishart, D. S.; Knox, C.; Guo, A. C.; Shrivastava, S.; Hassanali, M.; Stothard, P.; Chang, Z.; Woolsey, J. DrugBank: A comprehensive resource for in silico drug discovery and exploration. Nucleic Acids Res. 2006, 34, D668-D672 Sp. Iss. SI.
69. National Institute of Mental Health (NIMH) Psychoactive Drug Screening Program. PDSP Ki Database. http://pdsp.med.unc.edu/pdspImg.php (accessed December 5, 2010).
70. Shanghai Institute of Organic Chemistry. PDBbind database. http://www.pdbbind-cn.org/ (accessed December 5, 2010).
71. Wang, R.; Gao, Y.; Lai, L. Calculating partition coefficient by atom-additive method Perspect. Drug. Discovery 2000, 19, 47-66
72. Marvin Beans, version 5.3.8; ChemAxon: Budapest, Hungary, 2010. http://www.chemaxon.com
73. Kuntz, I. D.; Chen, K.; Sharp, K. A.; Kollman, P. A. The maximal affinity of ligands Proc. Natl. Acad. Sci. U.S.A. 1999, 96, 9997-10002 (Pubitemid 29422500)
74. Hopkins, A. L.; Groom, C. R. Ligand efficiency: A useful metric for lead selection Drug Discovery Today 2004, 9, 430-431 (Pubitemid 38510559)
75. García-Sosa, A. T.; Hetényi, C.; Maran, U. Drug efficiency indices for improvement of molecular docking scoring functions J. Comput. Chem. 2010, 31, 174-184
76. García-Sosa, A. T.; Sild, S.; Takkis, K.; Maran, U. Combined approach using ligand efficiency, cross-docking, and antitarget hits for wild-type and drug-resistant Y181C HIV-1 reverse transcriptase J. Chem. Inf. Model. 2011, 51, 2595-2611
77. Hetényi, C; Maran, U.; García-Sosa, A. T.; Karelson, M. Structure-based calculation of drug efficiency indices Bioinformatics 2007, 23, 2678-2685 (Pubitemid 350048331)
78. García-Sosa, A. T.; Sild, S.; Maran, U. Docking and virtual screening using distributed grid technology QSAR Comb. Sci. 2009, 28, 815-821
79. García-Sosa, A. T.; Sild, S.; Maran, U. Design of multi-binding-site inhibitors, ligand efficiency, and consensus screening of avian influenza H5N1 wild-type neuraminidase and of the oseltamivir-resistant H274Y variant J. Chem. Inf. Model. 2008, 48, 2074-2080
80. R Development Core Team. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria. http://www.R-project.org. (accessed January 1, 2011).
81. UCLA: Academic Technology Services, Statistical Consulting Group. R: Logit Regression. http://www.ats.ucla.edu/stat/r/dae/logit.htm (accessed April 12, 2011).
82. Mathews, B. W. Comparison of the predicted and observed secondary structure of T4 phage lysozyme Biochim. Biophys. Acta 1975, 405, 442-451
83. Swamidass, S. J.; Azencott, C.-A.; Daily, K.; Baldi, P. A CROC stronger than ROC: Measuring, visualizing, and optimizing early retrieval Bioinformatics 2010, 26, 1348-1356
84. Grace Development Team. Grace. http://plasma-gate.weizmann.ac.il/Grace/ (accessed January 1, 2011).
85. Veber, D. F.; Johnson, S. R.; Cheng, H.-Y.; Smith, B. R.; Ward, K. W.; Kopple, K. D. Molecular properties that influence the oral bioavailability of drug candidates J. Med. Chem. 2002, 45, 2615-2623 (Pubitemid 34595232)
86. Kelder, J.; Grootenhuis, P. D. J.; Bayada, D. M.; Delbressine, L. P. C.; Ploemen, J.-P. Polar molecular surface area as a dominating determinant for oral absorption and brain penetration of drugs Pharm. Res. 1999, 16 (10) 1514-1519 (Pubitemid 29510546)
87. Karelson, M. In Molecular Descriptors in QSAR/QSPR. 1 st ed.; Wiley Interscience: New York, 2000.
88. Todeschini, R; Consonni, V. In Molecular Descriptors for Chemoinformatics; Mannhold, R.; Kubinyi, H.; Folkers, G., Eds.; Series: Methods and Principles in Medicinal Chemistry; Wiley-VCH: Weinheim, Germany, 2009.
89. UBM Canon. PharmaLive.com.MedAdNews 200-World'sBest-Selling Medicines, MedAdNews, July (2007. http://www.pharmalive.com/magazines/medad/?date=07%2F2007 (accessed January 1, 2011).
90. García-Sosa, A. T.; Mancera, R. L. Free energy calculations of mutations involving a tightly bound water molecule and ligand substitutions in a ligand-protein complex Mol. Inf. 2010) 29, 589-600