Hybrid Parallelization of Protein-Ligand Docking using Fast Fourier Transformations and Rigid Body conformation
Abhishek K1, S. Balaji2

1Abhishek K, Research, Department of Information Science & Engineering, Jyothy Institute of Technology, Bengaluru, India.

2S. Balaji, Research, Centre for Incubation, Innovation, Jyothy Institute of Technology, Tataguni, Bengaluru, India.

Manuscript received on 05 March 2019 | Revised Manuscript received on 12 March 2019 | Manuscript Published on 20 March 2019 | PP: 157-160 | Volume-8 Issue- 4S2 March 2019 | Retrieval Number: D1S0032028419/2019©BEIESP

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Docking has become a very important technique catering a wide spectrum of applications and Drug Design / Discovery is one such domain. Docking has become an integral part of proteomics ever since its advent. With the advent of ubiquitous computing and computational proteomics, docking technique has become very invaluable technique for in-silico analysis. Docking is a technique in which the preferred orientation of one molecule to another to form a stable complex is determined or predicted. This knowledge of orientation can be applied to know about binding affinity between two molecules which is known as Scoring Functions (SF). Scoring functions essentially give an insight about how likely one molecule gets bound with another molecule Virtual screening is an in-silico technique which is mainly used in the drug discovery to search libraries of small molecules to identify those structures which are most likely to bind to a target. In virtual screening a large set of libraries of compounds are evaluated to re-score the enrichment or to find out the binding affinity. In this work, we study and evaluate Heterogeneous Parallel Processing Based Virtual Screening Pipeline for Effective Rescoring in Protein-Ligand Docking. We present the study of FFT based docking algorithms that leverages High-Performance Computing platform which is horizontally scalable and enterprise a better performance.

Keywords: High-Performance Computing, Ligand Protein Docking, GPU, Multiconformer Library, FFT.
Scope of the Article: Information-Centric Networking