Shape and pharmacophore-based virtual screening to identify potential cytochrome P450 sterol 14α-demethylase inhibitors

References

• Fridkin SK, Jarvis WR. Epidemiology of nosocomial fungal infections. Clin Microbiol Rev 1996;9:499–511
   PubMed Web of Science ®Google Scholar
• Strushkevich N, Usanov SA, Park HW. Structural basis of human CYP51 inhibition by antifungal azoles. J Mol Biol 2010;397:1067–78
   PubMed Web of Science ®Google Scholar
• Aoyama Y. Recent progress in the CYP51 research focusing on its unique evolutionary and functional characteristics as a diversozyme P450. Front Biosci 2005;10:1546–57
   Google Scholar
• Lepesheva GI, Waterman MR. Sterol 14alpha-demethylase cytochrome P450 (CYP51), a P450 in all biological kingdoms. Biochim Biophys Acta 2007;1770:467–77
   PubMed Web of Science ®Google Scholar
• Sangshetti JN, Lokwani DK, Sarkate AP, Shinde DB. Synthesis, antifungal activity, and docking study of some new 1,2,4-triazole analogs. Chem Biol Drug Des 2011;78:800–9
   PubMed Web of Science ®Google Scholar
• Podust LM, Yermalitskaya LV, Lepesheva GI, et al. Estriol bound and ligand-free structures of sterol 14alpha-demethylase. Structure 2004;12:1937–45
   PubMed Web of Science ®Google Scholar
• Lepesheva GI, Waterman MR. Structural basis for conservation in the CYP51 family. Biochim Biophys Acta 2011;1814:88–93
   PubMed Web of Science ®Google Scholar
• Podust LM, Poulos TL, Waterman MR. Crystal structure of cytochrome P450 14alpha -sterol demethylase (CYP51) from Mycobacterium tuberculosis in complex with azole inhibitors. Proc Natl Acad Sci USA 2001;98:3068–73
   PubMed Web of Science ®Google Scholar
• Craven RJ, Mallory JC, Hand RA. Regulation of iron homeostasis mediated by the heme-binding protein Dap1 (damage resistance protein 1) via the P450 protein Erg11/Cyp51. J Biol Chem 2007;282:36543–51
   PubMed Web of Science ®Google Scholar
• Chai X, Zhang J, Hu H, et al. Design, synthesis, and biological evaluation of novel triazole derivatives as inhibitors of cytochrome P450 14alpha-demethylase. Eur J Med Chem 2009;44:1913–20
   Google Scholar
• Chai X, Zhang J, Cao Y, et al. New azoles with antifungal activity: design, synthesis, and molecular docking. Bioorg Med Chem Lett 2011;21:686–9
   Google Scholar
• Kumar N, Hendriks BS, Janes KA, et al. Applying computational modeling to drug discovery and development. Drug Discov Today 2006;11:806–11
   PubMed Web of Science ®Google Scholar
• Dror O, Shulman-Peleg A, Nussinov R, Wolfson HJ. Predicting molecular interactions in silico: I. A guide to pharmacophore identification and its applications to drug design. Curr Med Chem 2004;11:71–90
   PubMed Web of Science ®Google Scholar
• Schneidman-Duhovny D, Nussinov R, Wolfson HJ. Predicting molecular interactions in silico: II. Protein-protein and protein-drug docking. Curr Med Chem 2004;11:91–107
   PubMed Web of Science ®Google Scholar
• Geppert H, Vogt M, Bajorath J. Current trends in ligand-based virtual screening: molecular representations, data mining methods, new application areas, and performance evaluation. J Chem Inf Model 2010;50:205–16
   PubMed Web of Science ®Google Scholar
• Leach AR, Shoichet BK, Peishoff CE. Prediction of protein-ligand interactions. Docking and scoring: successes and gaps. J Med Chem 2006;49:5851–5
   PubMed Web of Science ®Google Scholar
• Sousa SF, Fernandes PA, Ramos MJ. Protein-ligand docking: current status and future challenges. Proteins 2006;65:15–26
   PubMed Web of Science ®Google Scholar
• Dixon JS, Blaney JM. Docking: predicting the structure and binding affinity of ligand-receptor complexes. In: Martin YC, Willet P, eds. Designing bioactive molecules: three-dimensional techniques and applications. Washington, DC: American Chemical Society; 1998:175–98
   Google Scholar
• Karplus M, McCammon JA. Molecular dynamics simulations of biomolecules. Nat Struct Biol 2002;9:646–52
   PubMedGoogle Scholar
• Norberg J, Nilsson L. Advances in biomolecular simulations: methodology and recent applications. Q Rev Biophys 2003;36:257–306
   PubMed Web of Science ®Google Scholar
• Schames JR, Henchman RH, Siegel JS, et al. Discovery of a novel binding trench in HIV integrase. J Med Chem 2004;47:1879–81
   PubMed Web of Science ®Google Scholar
• Huo S, Wang J, Cieplak P, et al. Molecular dynamics and free energy analyses of cathepsin D-inhibitor interactions: insight into structure-based ligand design. J Med Chem 2002;45:1412–19
   PubMed Web of Science ®Google Scholar
• Rush 3rd TS, Grant JA, Mosyak L, Nicholls A. A shape-based 3-D scaffold hopping method and its application to a bacterial protein-protein interaction. J Med Chem 2005;48:1489–95
   PubMed Web of Science ®Google Scholar
• Oyarzabal J, Howe T, Alcazar J, et al. Novel approach for chemotype hopping based on annotated databases of chemically feasible fragments and a prospective case study: new melanin concentrating hormone antagonists. J Med Chem 2009;52:2076–89
   Google Scholar
• Kirchmair J, Distinto S, Markt P, et al. How to optimize shape-based virtual screening: choosing the right query and including chemical information. J Chem Inf Model 2009;49:678–92
   PubMed Web of Science ®Google Scholar
• Noha SM, Atanasov AG, Schuster D, et al. Discovery of a novel IKK-beta inhibitor by ligand-based virtual screening techniques. Bioorg Med Chem Lett 2011;21:577–83
   Google Scholar
• McGaughey GB, Sheridan RP, Bayly CI, et al. Comparison of topological, shape, and docking methods in virtual screening. J Chem Inf Model 2007;47:1504–19
   PubMed Web of Science ®Google Scholar
• Sastry GM, Dixon SL, Sherman W. Rapid shape-based ligand alignment and virtual screening method based on atom/feature-pair similarities and volume overlap scoring. J Chem Inf Model 2011;51:2455–66
   PubMed Web of Science ®Google Scholar
• Sheehan DJ, Hitchcock CA, Sibley CM. Current and emerging azole antifungal agents. Clin Microbiol Rev 1999;12:40–79
   PubMed Web of Science ®Google Scholar
• Girmenia C. New generation azole antifungals in clinical investigation. Expert Opin Investig Drugs 2009;18:1279–95
   PubMed Web of Science ®Google Scholar
• Phase, version 3.4, Schrödinger, LLC, New York, NY, 2012
   Google Scholar
• LigPrep, version 2.5, Schrödinger, LLC, New York, NY, 2012
   Google Scholar
• Jorgensen WL, Maxwell DS, Tirado-Rives J. Development and testing of the OPLS all-atom force field on conformational energetics and properties of organic liquids. J Am Chem Soc 1996;118:11225–36
   Web of Science ®Google Scholar
• Kaminski GA, Friesner RA, Tirado-Rives J, Jorgensen WL. Evaluation and reparametrization of the OPLS-AA force field for proteins via comparison with accurate quantum chemical calculations on peptides. J Phys Chem B 2001;105:6474–87
   Web of Science ®Google Scholar
• Dixon SL, Smondyrev AM, Knoll EH, et al. PHASE: a new engine for pharmacophore perception, 3D QSAR model development, and 3D database screening: 1. Methodology and preliminary results. J Comput Aided Mol Des 2006;20:647–71
   PubMed Web of Science ®Google Scholar
• Dixon SL, Smondyrev AM, Rao SN. PHASE: a novel approach to pharmacophore modeling and 3D database searching. Chem Biol Drug Des 2006;67:370–2
   PubMed Web of Science ®Google Scholar
• Reddy KK, Singh SK, Dessalew N, et al. Pharmacophore modelling and atom-based 3D-QSAR studies on N-methyl pyrimidones as HIV-1 integrase inhibitors. J Enzyme Inhib Med Chem 2012;27:339–47
   PubMed Web of Science ®Google Scholar
• Halgren TA, Murphy RB, Friesner RA, et al. Glide: a new approach for rapid, accurate docking and scoring. 2. Enrichment factors in database screening. J Med Chem 2004;47:1750–9
   PubMed Web of Science ®Google Scholar
• Friesner RA, Murphy RB, Repasky MP, et al. Extra precision glide: docking and scoring incorporating a model of hydrophobic enclosure for protein-ligand complexes. J Med Chem 2006;49:6177–96
   PubMed Web of Science ®Google Scholar
• Berman HM, Westbrook J, Feng Z, et al. The protein data bank. Nucleic Acids Res 2000;28:235–42
   PubMed Web of Science ®Google Scholar
• Schrödinger Suite 2012 Protein Preparation Wizard; Epik version 2.3, Schrödinger, LLC, New York, NY, 2012; Impact version 5.8, Schrödinger, LLC, New York, NY, 2012; Prime version 3.1, Schrödinger, LLC, New York, NY, 2012
   Google Scholar
• Friesner RA, Banks JL, Murphy RB, et al. Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. J Med Chem 2004;47:1739–49
   PubMed Web of Science ®Google Scholar
• Shelley JC, Cholleti A, Frye LL, et al. Epik: a software program for pK(a) prediction and protonation state generation for drug-like molecules. J Comput Aided Mol Des 2007;21:681–91
   PubMed Web of Science ®Google Scholar
• Desmond Molecular Dynamics System, version 3.1, D.E. Shaw Research, New York, NY, 2012; Maestro-Desmond Interoperability Tools, version 3.1, Schrödinger, New York, NY, 2012
   Google Scholar
• Shivakumar D, Williams J, Wu Y, et al. Prediction of absolute solvation free energies using molecular dynamics free energy perturbation and the OPLS force field. J Chem Theory Comput 2010;6:1509–19
   PubMed Web of Science ®Google Scholar
• Guo Z, Mohanty U, Noehre J, et al. Probing the alpha-helical structural stability of stapled p53 peptides: molecular dynamics simulations and analysis. Chem Biol Drug Des 2010;75:348–59
   PubMed Web of Science ®Google Scholar
• QikProp, version 3.5, Schrödinger, LLC, New York, NY, 2012
   Google Scholar
• Thakur VV, Kim JT, Hamilton AD, et al. Optimization of pyrimidinyl- and triazinyl-amines as non-nucleoside inhibitors of HIV-1 reverse transcriptase. Bioorg Med Chem Lett 2006;16:5664–7
   Google Scholar