The quest for novel chemical matter and the contribution of computer-aided de novo design

Bibliography

• Perola E. An analysis of the binding efficiencies of drugs and their leads in successful drug discovery programs. J Med Chem 2010;53:2986-97
   PubMed Web of Science ®Google Scholar
• Walters WP, Namchuk M. Designing screens: how to make your hits a hit. Nat Rev Drug Discov 2003;2:259-66
   PubMed Web of Science ®Google Scholar
• Congreve M, Chessari G, Tisi G, Recent developments in fragment-based drug discovery. J Med Chem 2008;51:3661-80
   PubMed Web of Science ®Google Scholar
• Bleicher KH, Bohm H-J, Muller K, Hit and lead generation: beyond high throughput screening. Nat Rev Drug Discov 2003;2:369-78
   PubMed Web of Science ®Google Scholar
• Schneider G, Fechner U. Computer-based de novo design of drug-like molecules. Nat Rev Drug Discov 2005;4:649-63
   PubMed Web of Science ®Google Scholar
• Baber JC, Feher M. Predicting synthetic accessibility: application in drug discovery and development. Mini Rev Med Chem 2004;4:681-92
   PubMed Web of Science ®Google Scholar
• Loving K, Alberts I, Sherman W. Computational approaches for fragment-based and de novo design. Curr Top Med Chem 2010;10:14-32
   PubMed Web of Science ®Google Scholar
• Mauser H, Stahl M. Chemical fragment spaces for de novo design. J Chem Inf Model 2007;47:318-24
   PubMed Web of Science ®Google Scholar
• Degen J, Wegscheid-Gerlach C, Zaliani A, On the art of compiling and using ‘drug-like’ chemical fragment spaces. ChemMedChem 2008;3:1503-7
   PubMed Web of Science ®Google Scholar
• Lewell XQ, Judd DB, Watson SP, Recap retrosynthetic combinatorial analysis procedure, a powerful new technique for identifying privileged molecular fragments with useful applications in combinatorial chemistry. J Chem Inf Comput Sci 1998;38:511-22
   PubMedGoogle Scholar
• Patel H, Bodkin MJ, Chen B, Knowledge-based approach to de novo design using reaction vectors. J Chem Inf Model 2009;49:1163-84
   PubMed Web of Science ®Google Scholar
• Hiss JA, Hartenfeller M, Schneider G. Concepts and applications of “natural computing” techniques in de novo drug and peptide design. Curr Pharm Des 2010;16:1656-65
   PubMed Web of Science ®Google Scholar
• Gohlke H, Klebe G. Approaches to the description and prediction of the binding affinity of small-molecules ligands to macromolecular receptors. Angew Chem Int Ed 2002;41:2644-76
   PubMed Web of Science ®Google Scholar
• Stahura FL, Bajorath J. New methodologies for ligand-based virtual screening. Curr Pharm Des 2005;11:1189-202
   PubMed Web of Science ®Google Scholar
• Erickson JA, Mader MM, Watson IA, Structure-guided expansion of kinase fragment libraries driven by support vector machine models. Biochimica et Biophysica Acta 2010;1804:642-52
   PubMed Web of Science ®Google Scholar
• Gasteiger J, Ihlefnfeldt WD. Computer-assisted planning of organic syntheses: the second generation of programs. Angew Chem Int Ed Eng 1996;34:2613-33
   Web of Science ®Google Scholar
• Gillet VJ, Myatt G, Zsoldos Z, SPROUT, HIPPo and CAESA: tools for de novo structure generation and estimation of synthetic accessibility. Perspect Drug Disc Design 1995;3:34-50
   Google Scholar
• Ertl P, Schuffenhauer A. Estimation of synthetic accessibility score of drug-like molecules based on molecular complexity and fragment contributions. J Cheminformatics 2009;1:8
   PubMed Web of Science ®Google Scholar
• Dey F, Caflisch A. Fragment-based de novo design by multiobjective evolutionary optimization. J Chem Inf Model 2008;48:679-90
   PubMed Web of Science ®Google Scholar
• Nicolaou C, Apostolakis J, Pattichis CS. De novo drug design using multiobjective evolutionary graphs. J Chem Inf Model 2009;49:295-307
   PubMed Web of Science ®Google Scholar
• Mauser H, Guba W. Recent developments in de novo design and scaffold hopping. Curr Opin Drug Discov Devel 2008;11:365-74
   PubMed Web of Science ®Google Scholar
• Damewood Jr JR, Lerman CL, Masek BB. NovoFLAP: a ligand-based de novo design approach for the generation of medicinally relevant ideas. J Chem Inf Model 2010;50:1296-303
   PubMed Web of Science ®Google Scholar
• Zaliani A, Boda K, Seidel T, Second-generation de novo design: a view from a medicinal chemist perspective. J Comput Aided Mol Des 2009;23:593-602
   PubMed Web of Science ®Google Scholar
• Alig L, Alsenz J, Andjelkovic M, Benzodioxoles: novel cannabinoid-1 receptor inverse agonists for the treatment of obesity. J Med Chem 2008;51:2115-27
   PubMed Web of Science ®Google Scholar
• Proschak E, Sander K, Zettl H, From molecular shape to potent bioactive agents II: fragment-based de novo design. ChemMedChem 2009;4:45-8
   PubMed Web of Science ®Google Scholar
• Lo HY, Bentzien J, White A, 2-Aminobenzimidazoles as potent ITK antagonists: de novo design of a pyrrole system targeting additional hydrogen bonding interaction. Tetrahedron Lett 2008;49:7337-40
   Web of Science ®Google Scholar
• Li W-W, Chen J-J, Zeng R-L, Taking quinazoline as a general support-nog to design potent and selective kinase inhibitors: application to FMS-like tyrosine kinase 3. ChemMedChem 2010;5:513-16
   PubMed Web of Science ®Google Scholar
• Park H, Bahn YJ, Ryu SE. Structure-based de novo design and biochemical evaluation of novel cdc25 phosphatase inhibitors. Bioorg Med Chem Lett 2009;19:4330-4
   PubMed Web of Science ®Google Scholar
• Guo C, Hou X, Dong L, Structure-based design of novel human Pin1 inhibitors. Bioorg Med Chem Lett 2009;19:5613-16
   PubMed Web of Science ®Google Scholar
• Wang R, Gao Y, Lai L. LigBuilder: a multi-purpose program for structure-based drug design. J Mol Model 2000;6:498-516
   Web of Science ®Google Scholar
• Perot S, Sperandio O, Miteva MA, Druggable pockets and binding site centric chemical space: a paradigm shift in drug discovery. Drug Discov Today 2010;15:656-67
   PubMed Web of Science ®Google Scholar
• Hartenfeller M, Proschak E, Schuller A, Concept of combinatorial de novo design of drug-like molecules by particle swarm optimization. Chem Biol Drug Des 2008;72:16-26
   PubMed Web of Science ®Google Scholar
• Huang Q, Li L-N, Yang S-Y. PHDD: a new pharmacophore-based de novo design method of drug-like molecules combined with assessment of synthetic accessibility. J Mol Graphics Model 2010;28:775-87
   PubMed Web of Science ®Google Scholar
• Pfeffer P, Fober T, Hullermeier E, GARLig: a fully automated tool for subset selection of large fragment spaces via a self-adaptative genetic algorithm. J Chem Inf Model 2010;50:1644-59
   PubMed Web of Science ®Google Scholar