VinaMPI: Facilitating multiple receptor high-throughput virtual docking on high-performance computers

被引:56
作者
Ellingson, Sally R. [1 ,2 ]
Smith, Jeremy C. [2 ,3 ]
Baudry, Jerome [2 ,3 ]
机构
[1] Univ Tennessee, Knoxville, TN 37996 USA
[2] Oak Ridge Natl Lab, UT ORNL Ctr Mol Biophys, Oak Ridge, TN USA
[3] Univ Tennessee, Dept Biochem Cellular & Mol Biol, Knoxville, TN USA
关键词
drug discovery; high-throughput docking; multiprotein docking; high-performance computing; DRUG DISCOVERY; MOLECULAR DOCKING; DYNAMICS; LIGANDS; SPACE;
D O I
10.1002/jcc.23367
中图分类号
O6 [化学];
学科分类号
070301 [无机化学];
摘要
The program VinaMPI has been developed to enable massively large virtual drug screens on leadership-class computing resources, using a large number of cores to decrease the time-to-completion of the screen. VinaMPI is a massively parallel Message Passing Interface (MPI) program based on the multithreaded virtual docking program AutodockVina, and is used to distribute tasks while multithreading is used to speed-up individual docking tasks. VinaMPI uses a distribution scheme in which tasks are evenly distributed to the workers based on the complexity of each task, as defined by the number of rotatable bonds in each chemical compound investigated. VinaMPI efficiently handles multiple proteins in a ligand screen, allowing for high-throughput inverse docking that presents new opportunities for improving the efficiency of the drug discovery pipeline. VinaMPI successfully ran on 84,672 cores with a continual decrease in job completion time with increasing core count. The ratio of the number of tasks in a screening to the number of workers should be at least around 100 in order to have a good load balance and an optimal job completion time. The code is freely available and downloadable. Instructions for downloading and using the code are provided in the Supporting Information. (c) 2013 Wiley Periodicals, Inc.
引用
收藏
页码:2212 / 2221
页数:10
相关论文
共 31 条
[1]
Discovery of drug-like inhibitors of an essential RNA-editing ligase in Trypanosoma brucei [J].
Amaro, Rommie E. ;
Schnaufer, Achim ;
Interthal, Heidrun ;
Hol, Wim ;
Stuart, Kenneth D. ;
McCammon, J. Andrew .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2008, 105 (45) :17278-17283
[2]
[Anonymous], P 2008 ACM IEEE C SU
[3]
The end of the beginning for genomic medicine [J].
Bailey, D ;
Zanders, E ;
Dean, P .
NATURE BIOTECHNOLOGY, 2001, 19 (03) :207-209
[4]
Prediction of potential toxicity and side effect protein targets of a small molecule by a ligand-protein inverse docking approach [J].
Chen, YZ ;
Ung, CY .
JOURNAL OF MOLECULAR GRAPHICS & MODELLING, 2001, 20 (03) :199-218
[5]
Task-Parallel Message Passing Interface Implementation of Autodock4 for Docking of Very Large Databases of Compounds Using High-Performance Super-Computers [J].
Collignon, Barbara ;
Schulz, Roland ;
Smith, Jeremy C. ;
Baudry, Jerome .
JOURNAL OF COMPUTATIONAL CHEMISTRY, 2011, 32 (06) :1202-1209
[6]
Molecular dynamics simulations and drug discovery [J].
Durrant, Jacob D. ;
McCammon, J. Andrew .
BMC BIOLOGY, 2011, 9
[7]
Ellingson SR, 2012, P 3 INT WORKSH EM CO, P33, DOI [10.1145/2483954.2483961, DOI 10.1145/2483954.2483961]
[8]
Estrada T., 2010, Proceedings of the 1st ACM Conference on Bioinformatics and Computational Biology, P204, DOI DOI 10.1145/1854776.1854807
[9]
The druggable genome [J].
Hopkins, AL ;
Groom, CR .
NATURE REVIEWS DRUG DISCOVERY, 2002, 1 (09) :727-730
[10]
Benchmarking sets for molecular docking [J].
Huang, Niu ;
Shoichet, Brian K. ;
Irwin, John J. .
JOURNAL OF MEDICINAL CHEMISTRY, 2006, 49 (23) :6789-6801