istar: A Web Platform for Large-Scale Protein-Ligand Docking

被引:87
作者
Li, Hongjian [1 ]
Leung, Kwong-Sak [1 ]
Ballester, Pedro J. [2 ]
Wong, Man-Hon [1 ]
机构
[1] Chinese Univ Hong Kong, Dept Comp Sci & Engn, Shatin, Hong Kong, Peoples R China
[2] European Bioinformat Inst, Cambridge, England
关键词
EMPIRICAL SCORING FUNCTIONS; BINDING-AFFINITY; PDBBIND DATABASE; AUTODOCK VINA; VALIDATION; DISCOVERY; OPTIMIZATION; CHEMISTRY; DESIGN; ZINC;
D O I
10.1371/journal.pone.0085678
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Protein-ligand docking is a key computational method in the design of starting points for the drug discovery process. We are motivated by the desire to automate large-scale docking using our popular docking engine idock and thus have developed a publicly-accessible web platform called istar. Without tedious software installation, users can submit jobs using our website. Our istar website supports 1) filtering ligands by desired molecular properties and previewing the number of ligands to dock, 2) monitoring job progress in real time, and 3) visualizing ligand conformations and outputting free energy and ligand efficiency predicted by idock, binding affinity predicted by RF-Score, putative hydrogen bonds, and supplier information for easy purchase, three useful features commonly lacked on other online docking platforms like DOCK Blaster or iScreen. We have collected 17,224,424 ligands from the All Clean subset of the ZINC database, and revamped our docking engine idock to version 2.0, further improving docking speed and accuracy, and integrating RF-Score as an alternative rescoring function. To compare idock 2.0 with the state-of-the-art AutoDock Vina 1.1.2, we have carried out a rescoring benchmark and a redocking benchmark on the 2,897 and 343 protein-ligand complexes of PDBbind v2012 refined set and CSAR NRC HiQ Set 24Sept2010 respectively, and an execution time benchmark on 12 diverse proteins and 3,000 ligands of different molecular weight. Results show that, under various scenarios, idock achieves comparable success rates while outperforming AutoDock Vina in terms of docking speed by at least 8.69 times and at most 37.51 times. When evaluated on the PDBbind v2012 core set, our istar platform combining with RF-Score manages to reproduce Pearson's correlation coefficient and Spearman's correlation coefficient of as high as 0.855 and 0.859 respectively between the experimental binding affinity and the predicted binding affinity of the docked conformation. istar is freely available at http://istar.cse.cuhk.edu.hk/idock.
引用
收藏
页数:12
相关论文
共 49 条
[1]   Selective Flexibility of Side-Chain Residues Improves VEGFR-2 Docking Score using AutoDock Vina [J].
Abreu, Rui M. V. ;
Froufe, Hugo J. C. ;
Queiroz, Maria-Joao R. P. ;
Ferreira, Isabel C. F. R. .
CHEMICAL BIOLOGY & DRUG DESIGN, 2012, 79 (04) :530-534
[2]   MOLA: a bootable, self-configuring system for virtual screening using AutoDock4/Vina on computer clusters [J].
Abreu, Rui M. V. ;
Froufe, Hugo J. C. ;
Queiroz, Maria Joao R. P. ;
Ferreira, Isabel C. F. R. .
JOURNAL OF CHEMINFORMATICS, 2010, 2
[3]   VSDK: Virtual screening of small molecules using AutoDock Vina on Windows platform [J].
Baba, Natsumi ;
Akaho, Eiichi .
BIOINFORMATION, 2011, 6 (10) :387-388
[4]  
Ballester PJ, 2012, LECT NOTES COMPUT SC, V7632, P14, DOI 10.1007/978-3-642-34123-6_2
[5]   Hierarchical virtual screening for the discovery of new molecular scaffolds in antibacterial hit identification [J].
Ballester, Pedro J. ;
Mangold, Martina ;
Howard, Nigel I. ;
Robinson, Richard L. Marchese ;
Abell, Chris ;
Blumberger, Jochen ;
Mitchell, John B. O. .
JOURNAL OF THE ROYAL SOCIETY INTERFACE, 2012, 9 (77) :3196-3207
[6]   Comments on "Leave-Cluster-Out Cross-Validation Is Appropriate for Scoring Functions Derived from Diverse Protein Data Sets": Significance for the Validation of Scoring Functions [J].
Ballester, Pedro J. ;
Mitchell, John B. O. .
JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2011, 51 (08) :1739-1741
[7]   A machine learning approach to predicting protein-ligand binding affinity with applications to molecular docking [J].
Ballester, Pedro J. ;
Mitchell, John B. O. .
BIOINFORMATICS, 2010, 26 (09) :1169-1175
[8]   Binding MOAD, a high-quality protein-ligand database [J].
Benson, Mark L. ;
Smith, Richard D. ;
Khazanov, Nickolay A. ;
Dimcheff, Brandon ;
Beaver, John ;
Dresslar, Peter ;
Nerothin, Jason ;
Carlson, Heather A. .
NUCLEIC ACIDS RESEARCH, 2008, 36 :D674-D678
[9]   Announcing the worldwide Protein Data Bank [J].
Berman, H ;
Henrick, K ;
Nakamura, H .
NATURE STRUCTURAL BIOLOGY, 2003, 10 (12) :980-980
[10]   The Protein Data Bank [J].
Berman, HM ;
Westbrook, J ;
Feng, Z ;
Gilliland, G ;
Bhat, TN ;
Weissig, H ;
Shindyalov, IN ;
Bourne, PE .
NUCLEIC ACIDS RESEARCH, 2000, 28 (01) :235-242