Metaheuristics Based Optimization Technique for Protein-Ligand Docking
Abhishek.K1, S. Balaji2

1Abhishek.K, Research Scholar-Jain University, Dept. of Information Science & Engineering., Jyothy Institute of Technology, Tataguni,Bengaluru-560082, India.
2S. Balaji, Centre for Incubation, Innovation, Research and Consultancy, Jyothy Institute of Technology, Tataguni, Off Kanakapura Road, Bengaluru-560082, India.

Manuscript received on 02 August 2019. | Revised Manuscript received on 07 August 2019. | Manuscript published on 30 September 2019. | PP: 4617-4622 | Volume-8 Issue-3 September 2019 | Retrieval Number: C6834098319/2019©BEIESP | DOI: 10.35940/ijrte.C6834.098319
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (

Abstract: Virtual screening using molecular docking requires optimization, which can be solved by using metaheuristics methods. Typically the interaction between two compounds is calculated using computationally intensive Scoring Functions (SF) which is computed in several spots which are called as binding surfaces. In this paper we present a novel approach for molecular docking which is based on parameterized and parallel metaheuristics which is useful in leveraging heterogeneous computing based on heterogeneous architectures. The approach decides on the optimization technique at running time by setting up a new configuration schema that allows parallel offloading of the data intensive sections of the docking. Hence the docking process is carried out in parallel efficiently while performing the metaheuristics execution. The approach carries out docking and computations of molecular interactions required for SF in parallel so that the time efficiency is improved. This opens a new path for further developments in virtual screening methods in heterogeneous platform.
Keywords: Drug Discovery, Virtual Screening, Molecular Docking, High Performance Computing, Metaheuristics, Heterogeneous Computing

Scope of the Article:
Bio-Science and Bio-Technology