In silico fragment-based drug design

Bibliography

• Roberts N, Martin J, Kinchington D, Rational design of peptide-based HIV proteinase inhibitors. Science 1990;248:358-61
   PubMed Web of Science ®Google Scholar
• Erickson J, Neidhart D, VanDrie J, Design, activity and 2.8 Å crystal structure of a C2 symmetric inhibitor complexed to HIV-1 protease. Science 1990;249:527-33
   PubMed Web of Science ®Google Scholar
• Hartman GD, Egbertson MS, Halczenko W, Non-peptide fibrinogen receptor antagonists. 1. Discovery and design of exosite inhibitors. J Med Chem 1992;35:4649-52
   Google Scholar
• Dorsey BD, Levin RB, McDaniel SL, L-735,524: the design of a potent and orally available HIV inhibitor. J Med Chem 1994;37:3443-51
   PubMed Web of Science ®Google Scholar
• Oprea TI, Matter H. Integrating virtual screening in lead discovery. Curr Opin Chem Biol 2004;8:349-58
   PubMed Web of Science ®Google Scholar
• Shoichet BK. Virtual screening of chemical libraries. Nature 2004;432:862-5
   PubMed Web of Science ®Google Scholar
• Nicholls A, McGaughey GB, Sheridan RP, Molecular shape and medicinal chemistry: a perspective. J Med Chem 2010;53:3862-86
   PubMed Web of Science ®Google Scholar
• Hardy LW, Malikayil A. The impact of structure-guided drug design on clinical agents. Curr Drug Discov 2003;3:15-20
   Google Scholar
• Perola E. An analysis of the binding efficiencies of drugs and their leads in successful drug discovery programs. J Med Chem 2010;53(7):2986-97
   PubMed Web of Science ®Google Scholar
• Anderson AC. The process of structure-based drug design. Chem Biol 2003;10:787-97
   PubMed Web of Science ®Google Scholar
• Jencks WP. On the attribution and additivity of binding energies. Proc Natl Acad Sci USA 1981;78:4046-50
   PubMed Web of Science ®Google Scholar
• Shuker SB, Hajduk PJ, Meadows RP, Fesik SW. Discovering high-affinity ligands for proteins: SAR by NMR. Science 1996;274(5292):1531-4
   PubMed Web of Science ®Google Scholar
• Jhoti H, Cleasby A, Verdonk M, Williams G. Fragment-based screening using X-ray crystallography and NMR spectroscopy. Curr Opin Chem Biol 2007;11:485-93
   PubMed Web of Science ®Google Scholar
• Swayze EE, Jefferson EA, Sannes-Lowery KA, SAR by MS: a ligand based technique for drug lead discovery against structured RNA targets. J Med Chem 2002;45:3816-19
   PubMed Web of Science ®Google Scholar
• Perspicace S, Banner D, Benz J, Fragment-based screening using surface plasmon resonance technology. J Biomol Screen 2009;14:337-49
   PubMed Web of Science ®Google Scholar
• Erlanson DA, Wells JA, Braisted AC. Tethering: fragment-based discovery. Annual Rev Biophys Biomol Struct 2004;33:199-223
   PubMedGoogle Scholar
• Matthews TP, Klair S, Burns S, Identification of inhibitors of checkpoint kinase 1 through template screening. J Med Chem 2009;52(15):4810-19
   PubMed Web of Science ®Google Scholar
• Ward WH, Holdgate GA. Isothermal titration calorimetry in drug discovery. Prog Med Chem 2001;38:309-76
   PubMedGoogle Scholar
• Hajduk PJ, Greer J. A decade of fragment-based drug design: strategic advances and lessons learned. Nat Rev Drug Discov 2007;6(3):211-19
   PubMed Web of Science ®Google Scholar
• Orita M, Warizaya M, Amano Y, Advances in fragment-based drug discovery platforms. Expert Opin Drug Discov 2009;4(11):1125-44
   PubMed Web of Science ®Google Scholar
• Congreve M, Chessari G, Tisi D, Woodhead AJ. Recent developments in fragment-based drug discovery. J Med Chem 2008;51(13):3662-80
   Google Scholar
• Alex AA, Flocco MM. Fragment-based drug discovery: what has it achieved so far? Curr Top Med Chem 2007;7(16):1544-67
   PubMed Web of Science ®Google Scholar
• Chessari G, Woodhead AJ. From fragment to clinical candidate – a historical perspective. Drug Discov Today 2009;14(13/14):668-675
   PubMed Web of Science ®Google Scholar
• Davies AM, Keeling DJ, Steele J, Components of successful lead generation. Curr Top Med Chem 2005;5:421-39
   PubMed Web of Science ®Google Scholar
• Boehm H-J, Boehringer M, Bur D, Novel inhibitors of DNA gyrase: 3D structure based biased needle screening, hit validation by biophysical methods, and 3D guided optimization. A promising alternative to random screening. J Med Chem 2000;43:2664-74
   PubMed Web of Science ®Google Scholar
• Edwards PD, Albert JS, Sylvester M, Application of fragment-based lead generation to the discovery of novel, cyclic amidine beta secretase inhibitors with nanomolar potency, cellular activity, and high ligand efficiency. J Med Chem 2007;50:5912-25
   PubMed Web of Science ®Google Scholar
• Gribbon P, Sewing A. High-throughput drug discovery: what can we expect from HTS? Drug Discov Today 2005;10:17-22
   PubMed Web of Science ®Google Scholar
• Bohacek RS, McMartin C, Guida WC. The art and practice of structure-based drug design: a molecular modeling perspective. Med Res Rev 1996;16:3-50
   PubMed Web of Science ®Google Scholar
• Martin YC. Challenges and prospects for computational aids to molecular diversity. Prospec Drug Discov Des 1997;7-8:159-172
   Web of Science ®Google Scholar
• Hann MM, Leach AR, Harper G. Molecular complexity and its impact on the probability of finding leads for drug discovery. J Chem Inf Comput Sci 2001;41:856-64
   PubMedGoogle Scholar
• Fink T, Bruggesser H, Reymond JL. Virtual exploration of the small-molecule chemical universe below 160 Daltons. Angew Chem Int Ed Engl 2005;44:1504-8
   PubMed Web of Science ®Google Scholar
• Schuffenhauer A, Ruedisser S, Marzinzik A, Library design for fragment based screening. Curr Top Med Chem 2005;5:751-62
   PubMed Web of Science ®Google Scholar
• Pellechia M, Sem DS, Wuthrich K. NMR in drug discovery. Nature Rev Drug Discov 2002;1:211-19
   PubMed Web of Science ®Google Scholar
• Kuhn P, Wilson K, Patch MG, Stevens RC. The genesis of high-throughput structure-based drug discovery using protein crystallography. Curr Opin Chem Biol 2002;6:704-10
   PubMed Web of Science ®Google Scholar
• Blundel TL, Jhoti H, Abell C. High-throughput crystallography for lead discovery in drug design. Nat Rev Drug Discov 2002;1:45-54
   PubMed Web of Science ®Google Scholar
• Moore Jr WR. Maximizing discovery efficiency with a computationally driven fragment approach. Curr Opin Drug Discov Devel 2005;8(3):355-64
   PubMed Web of Science ®Google Scholar
• Vadja S, Guarnieri F. Characterization of protein–ligand interaction sites using experimental and computational methods. Curr Opin Drug Discov Devel 2006;9:354-62
   PubMed Web of Science ®Google Scholar
• Kunz ID, Chen K, Sharp KA, Kollman PA. The maximal affinity of ligands. Proc Natl Acad Sci USA 1999;96(18):9997-10002
   PubMed Web of Science ®Google Scholar
• Hopkins AL, Groom CR, Alex A. Ligand efficiency: a useful metric for lead selection. Drug Discov Today 2004;9(10):430-1
   PubMed Web of Science ®Google Scholar
• Abad-Zapatero C, Metz JM. Ligand efficiency indices as guideposts for drug discovery. Drug Discov Today 2005;10(7):464-9
   PubMed Web of Science ®Google Scholar
• Reynolds CH, Bembenek SD, Tounge BA. The role of molecular size in ligand efficiency. Bioorg Med Chem Lett 2007;17(15):4258-61
   PubMed Web of Science ®Google Scholar
• Reynolds CH, Tounge BA, Bembenek SD. Ligand binding efficiency: trends, physical basis, and implications. J Med Chem 2008;51(8):2432-8
   PubMed Web of Science ®Google Scholar
• Abad-Zapatero C. Ligand efficiency indices for effective drug discovery. Expert Opin Drug Discov 2007;2(4):469-88
   PubMed Web of Science ®Google Scholar
• Keseru GM, Makara GM. The influence of lead discovery strategies on the properties of drug candidates. Nat Rev Drug Discov 2009;8(3):203-12
   PubMed Web of Science ®Google Scholar
• Leeson PD, Springthorpe B. The influence of drug-like concepts on decision-making in medicinal chemistry. Nat Rev Drug Discov 2007;6:881-90
   PubMed Web of Science ®Google Scholar
• Freire E. Do enthalpy and entropy distinguish first in class from best in class? Drug Discov Today 2008;13(19/20):869-874
   PubMed Web of Science ®Google Scholar
• Pellecchia M. Fragment-based drug discovery takes a virtual turn. Nat Chem Biol 2009;5(5):274-5
   PubMed Web of Science ®Google Scholar
• Rees DC, Congreve M, Murray CW, Carr R. Fragment-based lead discovery. Nat Rev Drug Discov 2004;3:660-72
   PubMed Web of Science ®Google Scholar
• Fersht AR, Shi JP, Knill-Jones J Hydrogen bonding and biological specificity analysed by protein engineering. Nature 1985;314:235-8
   PubMed Web of Science ®Google Scholar
• Davis AM, Teague SJ, Kleywegt GJ. Applications and limitations of x-ray crystallographic data in structure-based ligand and drug design. Angew Chem Int Ed 2003;42:2718-38
   PubMed Web of Science ®Google Scholar
• Mountain V. Astex, Structural Genomix, and Syrrx. I can see clearly now: structural biology and drug discovery. Chem Biol 2003;10:95-8
   PubMedGoogle Scholar
• Sharf A, Jhoti H. High-throughput crystallography to enhance drug discovery. Curr Opin Chem Biol 2003;7:340-5
   PubMed Web of Science ®Google Scholar
• Protein Data Bank. Available from: http://www.rcsb.org/pdb
   Google Scholar
• Mattos C, Ringe D. Locating and characterizing binding sites on proteins. Nat Biotechnol 1996;14:595-9
   PubMed Web of Science ®Google Scholar
• Mattos C, Ringe D. Proteins in organic solvents. Curr Opin Struct Biol 2001;11:761-4
   PubMed Web of Science ®Google Scholar
• Sali A, Overington JP. Derivation of rules for comparative protein modeling from a database of protein structure alignments. Protein Sci 1994;3:1582-96
   PubMed Web of Science ®Google Scholar
• Sali A, Potterton L, Yuan F, Evaluation of comparative protein modeling by MODELLER. Proteins 1995;23:318-26
   PubMed Web of Science ®Google Scholar
• Cardozo T, Totrov MM, Abagyan RA. Homology modeling by the ICM method. Proteins 1995;23:403-14
   PubMed Web of Science ®Google Scholar
• Diller DJ, Li R. Kinases, homology models, and high throughput docking. J Med Chem 2003;46(22):4638-47
   PubMed Web of Science ®Google Scholar
• Hillisch A, Pineda LF, Hilgenfeld R. Utility of homology models in the drug discovery process. Drug Discov Today 2004;9(15):659-69
   PubMed Web of Science ®Google Scholar
• Lee T, Ma W, Zhang X, BCR-ABL alternative splicing as a common mechanism for imitanib resistance: evidence from molecular dynamics simulations. Mol Cancer Ther 2008;12:3834-41
   Google Scholar
• Subramanian J, Sharma S, B-Rao C. Modeling and selection of flexible proteins for structure-based drug design: backbone and side chain movements in p38 MAPK. Chem Med Chem 2008;3:336-44
   Google Scholar
• Kufareva I, Abagyan R. Type-II kinase inhibitor docking, screening, and profiling using modified structures of active kinase states. J Med Chem 2008;51(24):7921-32
   PubMed Web of Science ®Google Scholar
• Traxler P, Furet P, Mett H, Design and synthesis of novel tyrosine kinase inhibitors using a pharmacophore model of the ATP-binding site of the EGF-R. J Pharm Belg 1997;52:88-96
   PubMedGoogle Scholar
• Sudbeck EA, Liu XP, Narla RK, Structure-based design of specific inhibitors of Janus kinase 3 as apoptosis-inducing antileukemic agents. Clin Cancer Res 1999;5:1569-82
   PubMed Web of Science ®Google Scholar
• Vankayalapati H, Bearss DJ, Saldanha JW, Targeting aurora 2 kinase in oncogenesis: a structural bioinformatics approach to target validation and rational drug design. Mol Cancer Ther 2003;2:283-94
   PubMed Web of Science ®Google Scholar
• Hillisch A, Peters O, Kosemund D, Dissecting physiological roles of estrogen receptor alpha and beta with potent selective ligands from structure-based design. Mol Endocrinol 2004;18:1599-609
   PubMed Web of Science ®Google Scholar
• Nayeem A, Sitkoff D, Krystek Jr S. A comparative study of available software for high-accuracy homology modeling: from sequence alignments to structural models. Protein Sci 2006;15:808-24
   PubMed Web of Science ®Google Scholar
• Hansen RW. The pharmaceutical development process: estimates of current development costs and times and effects of regulatory changes. In: Chien RI, editor. Issues in pharmaceutical economics. Lexington Books, Lexington, MA; 1979. p. 151-87
   Google Scholar
• DiMasi JA, Hansen RW, Grabowski HG, Lasagna L. Cost of innovation in the pharmaceutical industry. J Health Econ 1991;10:107-42
   PubMed Web of Science ®Google Scholar
• DiMasi JA, Hansen RW, Grabowski HG. The price of innovation: new estimates of drug development costs. J Health Econ 2003;22:151-85
   PubMed Web of Science ®Google Scholar
• Aronovitz LG, Redican-Bigott G, Hormozi S, New drug development: science, business, regulatory, and intellectual property issues cited as hampering drug development efforts. Report GAO-07-49; 2006
   Google Scholar
• Lipinski CA, Lombardo F, Dominy BW, Feeney PJ. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev 1997;23:3-25
   Web of Science ®Google Scholar
• Veber DF, Johnson SR, Cheng HY, Molecular properties that influence the oral bioavailability of drug candidates. J Med Chem 2002;45:2615-23
   PubMed Web of Science ®Google Scholar
• Congreve M, Carr R, Murray C, Jhoti H. A “rule of three” for fragment-based lead discovery? Drug Discov Today 2003;8:876-7
   PubMed Web of Science ®Google Scholar
• Lepre CA. Library design for NMR-based screening. Drug Discov Today 2001;6:133-40
   PubMed Web of Science ®Google Scholar
• Jacoby E, Davies J, Blommers MJJ. Design of small molecule libraries for NMR screening and other applications in drug discovery. Curr Top Med Chem 2003;3:11-23
   PubMed Web of Science ®Google Scholar
• Comprehensive Medicinal Chemistry. Available from Elsevier B.V., Amsterdam, Netherlands; 2006
   Google Scholar
• MDL Drug Data Report. Available from Symyx Technologies Inc., San Ramon, CA, USA; 2010
   Google Scholar
• World Drug Index. Available from Thomson Reuters, New York, NY, USA; 2010
   Google Scholar
• Siegal G, Eiso AB, Schultz J. Integration of fragment screening and library design. Drug Discov Today 2007;12(23/24):1032-1039
   PubMed Web of Science ®Google Scholar
• Vieth M, Siegel MG, Higgs RE, Characteristic physical properties and structural fragments of marketed oral drugs. J Med Chem 2004;47:224-32
   PubMed Web of Science ®Google Scholar
• Lepre CA, Moore JM, Peng JW. Theory and applications of NMR-based screening in pharmaceutical research. Chem Rev 2004;104:3641-76
   PubMed Web of Science ®Google Scholar
• Lewell XQ, Judd DB, Watson SP, Hann MM. 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
• Schneider G, Bohm H-J. Virtual screening and fast automated docking methods. Drug Disc Today 2002;7(1):64-70
   PubMed Web of Science ®Google Scholar
• Jorgensen WL. The many roles of computation in drug discovery. Science 2004;303:1813-18
   PubMed Web of Science ®Google Scholar
• Schneider G, Fechner U. Computer-based de novo design of drug-like molecules. Nat Rev Drug Discov 2004;4:649-63
   Web of Science ®Google Scholar
• Zoete V, Grosdidier A, Michielin O. Docking, virtual high throughput screening and in silico fragment-based drug design. J Cell Mol Med 2009;13(2):238-48
   PubMed Web of Science ®Google Scholar
• Tembe BL, McCammon JA. Ligand-receptor interactions. Comput Chem 1984;8:281-3
   Google Scholar
• Gilson GL, Given JA, Bush BL, McCammon JA. The statistical-thermodynamic basis for computation of binding affinities: a critical review. Biophys J 1997;72:1047-69
   PubMed Web of Science ®Google Scholar
• Jorgensen WL. Free energy calculations. A breakthrough for modeling organic chemistry in solution. Acc Chem Res 1989;22:184-9
   Web of Science ®Google Scholar
• Kollman PA. Free energy calculations: applications to chemical and biochemical phenomena. Chem Rev 1993;93:2395-417
   Web of Science ®Google Scholar
• Aqvist J, Medina C, Samuelsson JE. A new method for predicting binding affinity in computer-aided drug design. Protein Eng 1994;7:385-91
   PubMedGoogle Scholar
• Wang J, Morin P, Wang W, Kollman PA. Use of MM-PBSA in reproducing the binding free energies to HIV-1 RT of TIBO derivatives and predicting the binding mode to HIV-1 RT of Efavirenz by docking and MM-PBSA. J Am Chem Soc 2001;123:5221-30
   PubMed Web of Science ®Google Scholar
• Chang C-E, Gilson MK. Free energy, entropy, and induced fit in host-guest recognition: calculations with second-generation mining minima algorithm. J Am Chem Soc 2004;126:13156-64
   PubMed Web of Science ®Google Scholar
• Weis A, Katebzadeh K, Soderhjelm P, Ligand affinities predicted with the MM/PBSA method: dependence on the simulation method and the force field. J Med Chem 2006;49:6596-606
   PubMed Web of Science ®Google Scholar
• Guarnieri F. Computational protein probing to identify binding sites. US6735530; 2004
   Google Scholar
• Clark M, Guarnieri F, Shkurko I, Wiseman J. Grand canonical monte carlo simulation of ligand-protein binding. J Chem Inf Model 2006;46:231-42
   PubMed Web of Science ®Google Scholar
• Clark M, Meshkat S, Wiseman JS. Grand canonical free-energy calculations of protein-ligand binding. J Chem Inf Model 2009;49:934-43
   PubMed Web of Science ®Google Scholar
• Guarnieri F, Mezei M. Simulated annealing of chemical potential: a general procedure for locating bound waters. Application to the study of the differential hydration propensities of the major and minor grooves of DNA. J Am Chem Soc 1996;118:8493-4
   Web of Science ®Google Scholar
• Clark M, Meshkat S, Talbot GT, Fragment-based computation of binding free energy by systematic sampling. J Chem Inf Model 2009;49:1901-13
   PubMed Web of Science ®Google Scholar
• Nishibata Y, Itai A. Automatic creation of drug candidate structures based on receptor structure. Starting point for artificial lead generation. Tetrahedron 1991;47:8985-90
   Web of Science ®Google Scholar
• Miranker A, Karplus M. Functionality maps of binding sites: a multiple copy simultaneous search method. Proteins 1991;11:29-34
   PubMed Web of Science ®Google Scholar
• Eisen MB, Wiley DC, Karplus M, Hubbard RE. HOOK: a program for finding novel molecular architectures that satisfy the chemical and steric requirements of a macromolecule binding site. Proteins 1994;19:199-221
   PubMed Web of Science ®Google Scholar
• Pearlman DA, Murcko MA. CONCERTS: dynamic connection of fragments as an approach to de novo ligand design. J Med Chem 1996;39:1651-63
   PubMed Web of Science ®Google Scholar
• Boehm H-J. The computer program LUDI: a new simple method for the de-novo design of enzyme inhibitors. J Comp Aided Mol Des 1992;6:61-78
   PubMed Web of Science ®Google Scholar
• Clark DE, Frenkel D, Levy SA, PRO-LIGAND: an approach to denovo molecular design. 1. Application to the design of organic molecules. J Comput Aided Mol Des 1995;9:13-32
   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
• DeWitte RS, Shakhnovich EI. SMoG de novo design method based on simple, fast, and accurate free energy estimates. 1. Methodology and supporting evidence. J Am Chem Soc 1996;118:11733-44
   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
• Moitessier N, Englebienne P, Lee D, Towards the development of universal, fast and highly accurate docking/scoring methods: a long way to go. Br J Pharmacol 2008;153:S7-26
   PubMed Web of Science ®Google Scholar
• Kunz ID, Blaney JM, Oatley SJ, A geometric approach to macromolecule-ligand interactions. J Mol Biol 1982;161:269-88
   PubMed Web of Science ®Google Scholar
• Honma T. Recent advances in de novo design strategy for practical lead identification. Med Res Rev 2003;23(5):606-32
   PubMed Web of Science ®Google Scholar
• Warren GL, Andrews CW, Capelli A-M, A critical assessment of docking programs and scoring functions. J Med Chem 2006;49:5912-31
   PubMed Web of Science ®Google Scholar
• Hopkins AL, Groom CR. The druggable genome. Nat Rev Drug Discov 2002;1:727-30
   PubMed Web of Science ®Google Scholar
• Fauman EB, Hopkins AL, Groom CR. Structural bioinformatics in drug discovery. In: Weissig H, Bourne P, editors. Structural bioinformatics. Wiley-Liss, Hoboken, NJ; 2003. p. 477-98
   Google Scholar
• Hajduk PJ, Huth JR, Tse C. Predicting protein druggability. Drug Discov Today 2005;10(23/24):1675-1682
   PubMed Web of Science ®Google Scholar
• Halgren TA. Identifying and characterizing binding sites and assessing druggability. J Chem Inf Model 2009;49(2):377-89
   PubMed Web of Science ®Google Scholar
• Hajduk PJ, Huth JR, Fesik SW. Druggability indices for protein targets derived from NMR-based screening data. J Med Chem 2005;48:2518-25
   PubMed Web of Science ®Google Scholar
• Cheng AC, Coleman RG, Smyth KT, Structure-based maximal affinity model predicts small-molecule druggability. Nat Biotechnol 2007;25(1):71-5
   PubMed Web of Science ®Google Scholar
• Schmidtke P, Barril X. Understanding and predicting druggability. A high-throughput method for detection of drug binding sites. J Med Chem 2010;53(15):5858-67
   PubMed Web of Science ®Google Scholar
• Landon MR, Lancia DR, Yu J, Identification of hot spots within druggable binding regions by computational solvent mapping of proteins. J Med Chem 2007;50:1231-40
   PubMed Web of Science ®Google Scholar
• Landon MR, Lieberman RL, Hoang QQ, Detection of ligand binding hot spots on protein surfaces via fragment-based methods: application to DJ-1 and glucocerebrosidase. J Comput Aided Mol Des 2009;23:491-500
   PubMed Web of Science ®Google Scholar
• Seco J, Luque FJ, Barril X. Binding site detection and druggability index from first principles. J Med Chem 2009;52:2363-71
   PubMed Web of Science ®Google Scholar
• Available Chemicals Directory. Available from Symyx Technology Inc., San Romon, CA, USA; 2010
   Google Scholar
• Bohm H-J, Banner DW, Weber L. Combinatorial docking and combinatorial chemistry: design of potent non-peptide thrombin inhibitors. J Comput Aided Mol Des 1999;13:51-6
   PubMed Web of Science ®Google Scholar
• Rummey C, Nordhoff S, Thiemann M, Metz G. In silico fragment-based discovery of DPP-IV S1 pocket binders. Bioorg Med Chem Lett 2006;16:1405-9
   PubMed Web of Science ®Google Scholar
• Nordhoff S, Cerezo-Galvez S, Feurer A, The reversed binding of beta-phenethylamine inhibitors of DPP-IV: X-ray structures and properties of novel fragment and elaborated inhibitors. Bioorg Med Chem Lett 2006;16:1744-8
   PubMed Web of Science ®Google Scholar
• Warner SL, Bashyam S, Vankayalapati H, Identification of a lead small-molecule inhibitor of the aurora kinases using a structure-assisted, fragment-based approach. Mol Cancer Ther 2006;5:1764-73
   PubMed Web of Science ®Google Scholar
• Regan J, Bretflelder S, Cirillo P, Pyrazole urea-based inhibitors of p38 MAP kinase: from lead compound to clinical candidate. J Med Chem 2002;45:2994-3008
   PubMed Web of Science ®Google Scholar
• Liu B. A potent and selective p38 allosteric inhibitor: virtual fragment-based design, synthesis and biological study. Presentation. ACS Meeting; Washington DC; 29 August 2009
   Google Scholar
• Chen Y, Shoichet BK. Molecular docking and ligand specificity in fragment-based inhibitor discovery. Nat Chem Biol 2009;5(5):358-64
   PubMed Web of Science ®Google Scholar
• ZINC small molecule database. Available from: http://zinc.docking.org
   Google Scholar
• Sandor M, Kiss R, Keseru GM. Virtual fragment docking by Glide: a validation study on 190 protein-fragment complexes. J Chem Inf Model 2010;50(6):1165-72
   PubMed Web of Science ®Google Scholar
• McDaughey GM, Culberson JC, Feuston BP, Scoring of KDR kinase inhibitors: using interaction energy as a guide for ranking. Mol Divers 2006;10:341-7
   PubMed Web of Science ®Google Scholar
• Young T, Abel R, Kim B, Motifs for molecular recognition exploiting hydrophobic enclosure in protein-ligand binding. Proc Nat Acad Sci 2007;104(3):808-13
   PubMed Web of Science ®Google Scholar
• Robinson DD, Sherman W, Farid R. Understanding kinase selectivity through energetic analysis of binding site waters. Chem Med Chem 2010;5:618-27
   Google Scholar
• Sherman W, Day T, Jacobson MP, Novel procedure for modeling ligand/receptor induced fit effects. J Med Chem 2006;49:534-53
   PubMed Web of Science ®Google Scholar
• Beier C, Zacharias M. Tackling the challenges posed by target flexibility in drug design. Expert Opin Drug Discov 2010;5(4):347-59
   PubMed Web of Science ®Google Scholar
• Orozco M, Luque FJ. Theoretical methods for the description of the solvent effect in biomolecular systems. Chem Rev 2000;100(11):4187-225
   PubMed Web of Science ®Google Scholar
• Jones S, Thornton JM. Principles of protein-protein interactions. Proc Natl Acad Sci USA 1996;93:13-20
   PubMed Web of Science ®Google Scholar
• Fry D, Vassilev L. Targeting protein-protein interactions for cancer therapy. J Mol Med 2005;83:955-63
   PubMed Web of Science ®Google Scholar
• Hopkins AL, Groom CR. The druggable genome. Nat Rev Drug Discov 2002;1:727-30
   PubMed Web of Science ®Google Scholar
• Wells JA, McClendon CL. Reaching for high-hanging fruit in drug discovery at protein-protein interfaces. Nature 2007;450:1001-9
   PubMed Web of Science ®Google Scholar
• Fry DC. Drug-like inhibitors of protein-protein interactions: a structural examination of effective protein mimicry. Curr Prot Pept Sci 2008;9:240-7
   PubMed Web of Science ®Google Scholar
• Zinzalla G, Thurston DE. Targeting protein-protein interactions for therapeutic intervention: a challenge for the future. Future Med Chem 2009;1(1):65-93
   PubMed Web of Science ®Google Scholar
• Vucic D, Fairbrother WJ. The inhibitor of apoptosis proteins as therapeutic targets in cancer. Clin Cancer Res 2007;13(20):5995-6000
   PubMed Web of Science ®Google Scholar
• FDA Clinical trials Available from: https://clinicaltrials.gov
   Google Scholar
• Huang J-W, Zhang Z, Wu B, Fragment-based design of small molecule X-linked inhibitor of apoptosis protein inhibitors. J Med Chem 2008;51:7111-18
   PubMed Web of Science ®Google Scholar
• Congreve M, Marshall F. The impact of GPCR structures on pharmacology and structure-based drug design. Br J Pharmacol 2010;159:986-96
   PubMed Web of Science ®Google Scholar
• Carlsson J, Yoo L, Gao Z-G, Structure-based discovery of A2A adenosine receptor ligands. J Med Chem 2010;53:3748-55
   PubMed Web of Science ®Google Scholar
• Jaakola VP, Griffith MT, Hanson MA, The 2.6 angstrom crystal structure of a human A(2A) adenosine receptor bound to an antagonist. Science 2008;322:1211-17
   PubMed Web of Science ®Google Scholar
• Aronovitz LG, Redican-Bigott G, Hormozi S, New drug development: science, business, regulatory, and intellectual property issues cited as hampering drug development efforts. Report to congessional requesters, GAO-07-49 USA; 2006
   Google Scholar
• Podolyan Y, Walters MA, Karypis G. Assessing synthetic accessibility of chemical compounds using machine learning methods. J Chem Inf Model 2010;50(6):979-91
   PubMed Web of Science ®Google Scholar
• Law J, Zsoldos Z, Simon A, Route designer: a retrosynthetic analysis tool utilizing automated retrosynthetic rule generation. J Chem Inf Model 2009;49(3):593-602
   PubMed Web of Science ®Google Scholar