Flexible CDOCKER: Development and Application of a Pseudo-Explicit Structure-Based Docking Method Within CHARMM

被引:90
作者
Gagnon, Jessica K. [1 ]
Law, Sean M. [1 ]
Brooks, Charles L., III [1 ]
机构
[1] Univ Michigan, Dept Chem, Ann Arbor, MI 48109 USA
关键词
protein-ligand; sampling; in silico screening; CSAR BENCHMARK EXERCISE; PROTEIN-LIGAND DOCKING; SCORING FUNCTION; DRUG-DISCOVERY; FLEXIBILITY; BINDING; DYNAMICS; RECOGNITION; STRATEGIES; MECHANICS;
D O I
10.1002/jcc.24259
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Protein-ligand docking is a commonly used method for lead identification and refinement. While traditional structure-based docking methods represent the receptor as a rigid body, recent developments have been moving toward the inclusion of protein flexibility. Proteins exist in an interconverting ensemble of conformational states, but effectively and efficiently searching the conformational space available to both the receptor and ligand remains a well-appreciated computational challenge. To this end, we have developed the Flexible CDOCKER method as an extension of the family of complete docking solutions available within CHARMM. This method integrates atomically detailed side chain flexibility with grid-based docking methods, maintaining efficiency while allowing the protein and ligand configurations to explore their conformational space simultaneously. This is in contrast to existing approaches that use induced-fit like sampling, such as Glide or Autodock, where the protein or the ligand space is sampled independently in an iterative fashion. Presented here are developments to the CHARMM docking methodology to incorporate receptor flexibility and improvements to the sampling protocol as demonstrated with re-docking trials on a subset of the CCDC/Astex set. These developments within CDOCKER achieve docking accuracy competitive with or exceeding the performance of other widely utilized docking programs. (c) 2015 Wiley Periodicals, Inc.
引用
收藏
页码:753 / 762
页数:10
相关论文
共 61 条
[41]   PROPKA3: Consistent Treatment of Internal and Surface Residues in Empirical pKa Predictions [J].
Olsson, Mats H. M. ;
Sondergaard, Chresten R. ;
Rostkowski, Michal ;
Jensen, Jan H. .
JOURNAL OF CHEMICAL THEORY AND COMPUTATION, 2011, 7 (02) :525-537
[42]   Ligand-Protein DataBase: Linking protein-ligand complex structures to binding data [J].
Roche, O ;
Kiyama, R ;
Brooks, CL .
JOURNAL OF MEDICINAL CHEMISTRY, 2001, 44 (22) :3592-3598
[43]   SAMPL2 challenge: prediction of solvation energies and tautomer ratios [J].
Skillman, A. Geoffrey ;
Geballe, Matthew T. ;
Nicholls, Anthony .
JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN, 2010, 24 (04) :257-258
[44]   CSAR Benchmark Exercise of 2010: Combined Evaluation Across All Submitted Scoring Functions [J].
Smith, Richard D. ;
Dunbar, James B., Jr. ;
Ung, Peter Man-Un ;
Esposito, Emilio X. ;
Yang, Chao-Yie ;
Wang, Shaomeng ;
Carlson, Heather A. .
JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2011, 51 (09) :2115-2131
[45]   Protein-ligand docking: Current status and future challenges [J].
Sousa, Sergio Filipe ;
Fernandes, Pedro Alexandrino ;
Ramos, Maria Joao .
PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS, 2006, 65 (01) :15-26
[46]   Study of a highly accurate and fast protein-ligand docking method based on molecular dynamics [J].
Taufer, M ;
Crowley, M ;
Price, DJ ;
Chien, AA ;
Brooks, CL .
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2005, 17 (14) :1627-1641
[47]   Implications of protein flexibility for drug discovery [J].
Teague, SJ .
NATURE REVIEWS DRUG DISCOVERY, 2003, 2 (07) :527-541
[48]   Software News and Update AutoDock Vina: Improving the Speed and Accuracy of Docking with a New Scoring Function, Efficient Optimization, and Multithreading [J].
Trott, Oleg ;
Olson, Arthur J. .
JOURNAL OF COMPUTATIONAL CHEMISTRY, 2010, 31 (02) :455-461
[49]   CHARMM General Force Field: A Force Field for Drug-Like Molecules Compatible with the CHARMM All-Atom Additive Biological Force Fields [J].
Vanommeslaeghe, K. ;
Hatcher, E. ;
Acharya, C. ;
Kundu, S. ;
Zhong, S. ;
Shim, J. ;
Darian, E. ;
Guvench, O. ;
Lopes, P. ;
Vorobyov, I. ;
MacKerell, A. D., Jr. .
JOURNAL OF COMPUTATIONAL CHEMISTRY, 2010, 31 (04) :671-690
[50]   DrugScoreCSD-knowledge-based scoring function derived from small molecule crystal data with superior recognition rate of near-native ligand poses and better affinity prediction [J].
Velec, HFG ;
Gohlke, H ;
Klebe, G .
JOURNAL OF MEDICINAL CHEMISTRY, 2005, 48 (20) :6296-6303