Name
Title | ||
|---|---|---|
HHVSF: A Framework to Accelerate Drug-Based High-Throughput Virtual Screening on High-Performance Computers. |
Abstract | ||
|---|---|---|
The High-performance High-throuhput Virtual Screening Framework (HHVSF) has been developed to accelerate High-Throughput Virtual Screening (HTVS) on high-performance computers. Task management and data management are two core components in HHVSF. Fine-grained computing resources are configured to support serial or threaded applications. Each task gets the input file from database through a preemptive algorithm and the failed tasks can be found and corrected. NoSQL database MongoDB is used as the data repository engine. Data is mobilized between the RAMDISK in computing node and the database. Data analysis is carried out after the computing process, and the results are stored in the database. Among the most popular molecular docking and molecular structure similarity packages, Autodock_vina (ADV) and WEGA were chosen to carry out experiments. Results show that when ADV was used for molecular docking, 10 million molecules were screened and analyzed in 22.31 h with 16000 cores, and the throughput reached up to 1324 molecules per second, averaging 145 molecules per second during the steady-running process. For WEGA, 958 million conformations were screened and analyzed in 34.12 min with 4000 cores, of which throughput reached up to 9448 molecules per second, 6430 molecules per second on average. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-319-69953-0_1 | Lecture Notes in Computer Science |
Keywords | DocType | Volume |
High-Throughput Virtual Screening,Drug discovery,High-Performance Computing,Molecular docking,Molecular structure similarity | Conference | 10776 |
ISSN | Citations | PageRank |
0302-9743 | 0 | 0.34 |
References | Authors | |
0 | 5 | |