Fragment-based QSAR strategies in drug design

Bibliography

• Gershell LJ, Atkins JH. A brief history of novel drug discovery technologies. Nat Rev Drug Discov 2003;2:321-27
   PubMed Web of Science ®Google Scholar
• Rester U. From virtuality to reality–virtual screening in lead discovery and lead optimization: a medicinal chemistry perspective. Curr Opin Drug Discov Dev 2008;11:559-68
   PubMed Web of Science ®Google Scholar
• Guido RVC, Oliva G, Andricopulo AD. Virtual screening and its integration with modern drug design technologies. Curr Med Chem 2008;15:37-46
   PubMed Web of Science ®Google Scholar
• Hajduk PJ, Greer J. A decade of fragment-based drug design: strategic advances and lessons learned. Nat Rev Drug Discov 2007;6:211-9
   PubMed Web of Science ®Google Scholar
• Saxty G, Woodhead SJ, Berdini V, Identification of inhibitors of protein kinase B using fragment-based lead discovery. J Med Chem 2007;50:2293-6
   PubMed Web of Science ®Google Scholar
• Salum LB, Andricopulo AD. Fragment-based QSAR: perspectives in drug design. Mol Divers 2009;13:277-85
   PubMed Web of Science ®Google Scholar
• Andricopulo AD, Salum LB, Abraham DJ. Structure-based drug design strategies in medicinal chemistry. Curr Top Med Chem 2009;9:771-90
   PubMed Web of Science ®Google Scholar
• Salum LB, Polikarpov I, Andricopulo AD. Structural and chemical basis for enhanced affinity and potency for a series of estrogen receptor ligands: 2D and 3D QSAR studies. J Mol Graph Modell 2007;25:434-42
   Web of Science ®Google Scholar
• Moda TL, Montanari CA, Andricopulo AD. Hologram QSAR model for the prediction of human oral bioavailability. Bioorg Med Chem 2007;15:7738-45
   PubMed Web of Science ®Google Scholar
• Givehchi A, Bender A, Glen RC. Analysis of activity space by fragment fingerprints, 2D descriptors, and multitarget dependent transformation of 2D descriptors. J Chem Inf Model 2006;46:1078-83
   PubMed Web of Science ®Google Scholar
• Cavasotto CN, Orry AJ. Ligand docking and structure-based virtual screening in drug discovery. Curr Top Med Chem 2007;7:1006-14
   PubMed Web of Science ®Google Scholar
• Sutherland JJ, Higgs RE, Watson I, Vieth M. Chemical fragments as foundations for understanding target space and activity prediction. J Med Chem 2008;51:2689-700
   PubMed Web of Science ®Google Scholar
• Baskin I, Varnek A. Building a chemical space based on fragment descriptors. Comb Chem High Throughput Screen 2008;11:661-8
   PubMed Web of Science ®Google Scholar
• Deng Z, Chuaqui C, Singh J. Structural interaction fingerprint (SIFt): a novel method for analyzing three-dimensional protein-ligand binding interactions. J Med Chem 2004;47:337-44
   PubMed Web of Science ®Google Scholar
• Castilho MS, Guido RVC, Andricopulo AD. 2D Quantitative structure-activity relationship studies on a series of cholesteryl ester transfer protein inhibitors. Bioorg Med Chem 2007;15:6242-52
   PubMed Web of Science ®Google Scholar
• Arif SM, Holliday JD, Willett P. Analysis and use of fragment-occurrence data in similarity-based virtual screening. J Comput Aided Mol Des 2009;23:655-68
   PubMed Web of Science ®Google Scholar
• Devereux M, Popelier PL, McLay IM. Quantum Isostere Database: a web-based tool using quantum chemical topology to predict bioisosteric replacements for drug design. J Chem Inf Model 2009;49:1497-513
   PubMed Web of Science ®Google Scholar
• Wang J, Hou T. Drug and drug candidate building block analysis. J Chem Inf Model 2010;50:55-67
   PubMed Web of Science ®Google Scholar
• Jelfs S, Ertl P, Selzer P. Estimation of pKa for druglike compounds using semiempirical and information-based descriptors. J Chem Inf Model 2007;47:450-9
   PubMed Web of Science ®Google Scholar
• Salum LB, Dias LC, Andricopulo AD. Fragment-based QSAR and molecular modeling studies on a series of discodermolide analogs as microtubule-stabilizing anticancer agents. QSAR Comb Sci 2009;28:325-37
   Google Scholar
• Hecht D, Fogel GB. A novel in silico approach to drug discovery via computational intelligence. J Chem Inf Model 2009;49:1105-21
   PubMed Web of Science ®Google Scholar
• Pasha FA, Muddassar M, Srivastava AK, Cho SJ. In silico QSAR studies of anilinoquinolines as EGFR inhibitors. J Mol Model 2010;16:263-77
   PubMed Web of Science ®Google Scholar
• Andrade CH, Salum LB, Castilho MS, Fragment-based and classical quantitative structure-activity relationships for a series of hydrazides as antituberculosis agents. Mol Divers 2008;12:47-59
   PubMed Web of Science ®Google Scholar
• Japertas P, Didziapetris R, Petrauskas A. Fragmental methods in the design of new compounds. Applications of advanced algorithm builder. Quant Struct Act Relat 2002;21:23-37
   Google Scholar
• Nair PC, Sobhia ME. Fingerprint directed scaffold hopping for identification of CCR2 antagonists. J Chem Inf Model 2008;48:1891-902
   PubMed Web of Science ®Google Scholar
• Eckert H, Bajorath J. Molecular similarity analysis in virtual screening: foundations, limitations and novel approaches. Drug Discov Today 2007;12:225-33
   PubMed Web of Science ®Google Scholar
• Ahmed HE, Bajorath J. Methods for computer-aided chemical biology. Part 5: rationalizing the selectivity of cathepsin inhibitors on the basis of molecular fragments and topological feature distributions. Chem Biol Drug Des 2009;74:129-41
   PubMed Web of Science ®Google Scholar
• Ahmed HE, Geppert H, Stumpfe D, Methods for computer-aided chemical biology. Part 4: selectivity searching for ion channel ligands and mapping of molecular fragments as selectivity markers. Chem Biol Drug Des 2009;73:273-82
   PubMed Web of Science ®Google Scholar
• van deWaterbeemd H, Gifford E. ADMET in silico modelling: towards prediction paradise. Nat Rev Drug Discov 2003;2:192-204
   PubMed Web of Science ®Google Scholar
• Moda TL, Torres LG, Carrara AE, Andricopulo AD. PK/DB: database for pharmacokinetic properties and predictive in silico ADME models. Bioinformatics 2008;24:2270-1
   PubMed Web of Science ®Google Scholar