Molecular simulation methods in drug discovery: a prospective outlook

被引:18
作者
Barril, Xavier [1 ,2 ,3 ]
Javier Luque, F. [1 ,2 ]
机构
[1] Univ Barcelona, Fac Farm, Dept Fisicoquim, E-08028 Barcelona, Spain
[2] Univ Barcelona, Fac Farm, Inst Biomed IBUB, E-08028 Barcelona, Spain
[3] ICREA, Barcelona 08010, Spain
关键词
Molecular simulation; Drug discovery; Target flexibility; Target druggability; Binding affinity; GRAPHICAL PROCESSING UNITS; ACCURATE PREDICTION; QUANTUM-MECHANICS; BINDING-AFFINITY; REPLICA EXCHANGE; SCORING FUNCTION; HIV-1; PROTEASE; DOCKING; INHIBITORS; ENERGIES;
D O I
10.1007/s10822-011-9506-1
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Over the last decades, molecular simulations have spread through the drug discovery arena. This trend is expected to continue in the foreseeable future thanks to increased performance and the positive impact they can exert on productivity. In this article we highlight three aspects of molecular modelling for which we expect significant improvements over the next 25 years. Increased computational resources, faster algorithms and novel methods to sample rare events will provide a better handle on target flexibility and its relation with ligand binding. More accurate target druggability predictions will improve the success, but also broaden the scope of target-based drug discovery strategies. Finally, the use of higher levels of theory will increase the accuracy of protein-ligand binding affinity predictions, resulting in better hit identification success rates as well as more efficient lead optimization processes.
引用
收藏
页码:81 / 86
页数:6
相关论文
共 74 条
[1]   Combining docking and molecular dynamic simulations in drug design [J].
Alonso, Hernan ;
Bliznyuk, Andrey A. ;
Gready, Jill E. .
MEDICINAL RESEARCH REVIEWS, 2006, 26 (05) :531-568
[2]   Quantum Mechanical Binding Free Energy Calculation for Phosphopeptide Inhibitors of the Lck SH2 Domain [J].
Anisimov, Victor M. ;
Cavasotto, Claudio N. .
JOURNAL OF COMPUTATIONAL CHEMISTRY, 2011, 32 (10) :2254-2263
[3]  
[Anonymous], 2004, SCIENCE, V303, P1798, DOI 10.1126/science.303.5665.1796
[4]   Molecular motions in drug design: the coming age of the metadynamics method [J].
Biarnes, Xevi ;
Bongarzone, Salvatore ;
Vargiu, Attilio Vittorio ;
Carloni, Paolo ;
Ruggerone, Paolo .
JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN, 2011, 25 (05) :395-402
[5]   Structural adaptability in the ligand-binding pocket of the ecdysone hormone receptor [J].
Billas, IML ;
Iwema, T ;
Garnier, JM ;
Mitschler, A ;
Rochel, N ;
Moras, D .
NATURE, 2003, 426 (6962) :91-96
[6]   A Medicinal Chemist's Guide to Molecular Interactions [J].
Bissantz, Caterina ;
Kuhn, Bernd ;
Stahl, Martin .
JOURNAL OF MEDICINAL CHEMISTRY, 2010, 53 (14) :5061-5084
[7]   Rapid estimation of relative protein-ligand binding affinities using a high-throughput version of MM-PBSA [J].
Brown, Scott P. ;
Muchmore, Steven W. .
JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2007, 47 (04) :1493-1503
[8]   Pyrano[3,2-c]quinoline-6-Chlorotacrine Hybrids as a Novel Family of Acetylcholinesterase- and β-Amyloid-Directed Anti-Alzheimer Compounds [J].
Camps, Pelayo ;
Formosa, Xavier ;
Galdeano, Carles ;
Munoz-Torrero, Diego ;
Ramirez, Lorena ;
Gomez, Elena ;
Isambert, Nicolas ;
Lavilla, Rodolfo ;
Badia, Albert ;
Victoria Clos, M. ;
Bartolini, Manuela ;
Mancini, Francesca ;
Andrisano, Vincenza ;
Arce, Mariana P. ;
Isabel Rodriguez-Franco, M. ;
Huertas, Oscar ;
Dafni, Thomai ;
Javier Luque, F. .
JOURNAL OF MEDICINAL CHEMISTRY, 2009, 52 (17) :5365-5379
[9]   Ligand docking and structure-based virtual screening in drug discovery [J].
Cavasotto, Claudio N. ;
Orry, Andrew J. W. .
CURRENT TOPICS IN MEDICINAL CHEMISTRY, 2007, 7 (10) :1006-1014
[10]   Structure-based maximal affinity model predicts small-molecule druggability [J].
Cheng, Alan C. ;
Coleman, Ryan G. ;
Smyth, Kathleen T. ;
Cao, Qing ;
Soulard, Patricia ;
Caffrey, Daniel R. ;
Salzberg, Anna C. ;
Huang, Enoch S. .
NATURE BIOTECHNOLOGY, 2007, 25 (01) :71-75