POAP: A GNU parallel based multithreaded pipeline of open babel and AutoDock suite for boosted high throughput virtual screening. (June 2018)

• Record Type: Journal Article
• Authors: Samdani, A.; Vetrivel, Umashankar
• Is Part Of: Computational biology and chemistry. Volume 74(2018)
• Page Start: 39
• Page End: 48
• Publication Date: 2018-06
• Subjects: GNU parallel -- AutoDock -- Open babel -- Virtual screening -- Parallel processing -- Ligand preparation; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2018.02.012
• Languages: English
• ISSNs: 1476-9271

Abstract

Graphical abstract: Highlights: POAP is a GNU Parallel based pipeline that enables optimally parallelized HTVS run by coupling Open Babel and AutoDock suite. The Ligand preparation option in POAP is unique offering extensive parameter feeding and well optimized parallelization. POAP provides high scalability and optimal usage of CPU cores leading to significant reduction of computational time. POAP features multi receptor docking and comparative analysis enabling drug repurposing studies. Abstract: High throughput virtual screening plays a crucial role in hit identification during the drug discovery process. With the rapid increase in the chemical libraries, virtual screening process becomes computationally challenging, thereby posing a demand for efficiently parallelized software pipelines. Here we present a GNU Parallel based pipeline-POAP that is programmed to run Open Babel and AutoDock suite under highly optimized parallelization. The ligand preparation module is a unique feature in POAP, as it offers extensive options for geometry optimization, conformer generation, parallelization and also quarantines erroneous datasets for seamless operation. POAP also features multi receptor docking that can be utilized for comparative virtual screening and drug repurposing studies. As demonstrated using different structural datasets, POAP proves to be an efficient pipeline that enables high scalability, seamless operability, dynamic file handling and optimal utilization of CPU's for computationally demanding tasks. POAP is distributed freely under GNU GPL license and can be downloaded at https://github.com/inpacdb/POAP .