A Hybrid DELGA Algorithm for Protein Ligand Docking
E. Pavithra Vishalini1, D. Ramyachitra2, P. Lakshmi3
1E. Pavithra Vishalini*, Department of Computer Science, Bharathiar University, Coimbatore.
2D. Ramyachitra, Department of Computer Science, Bharathiar University, Coimbatore.
3P. Lakshmi, Department of Computer Science, Bharathiar University, Coimbatore.
Manuscript received on January 18, 2020. | Revised Manuscript received on January 26, 2020. | Manuscript published on February 10, 2020. | PP: 2836-2840 | Volume-9 Issue-4, February 2020. | Retrieval Number: C8986019320/2020©BEIESP | DOI: 10.35940/ijitee.C8986.029420
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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: Protein-ligand docking is a computational molecular modeling method that is used in drug design to predict the optimal binding pose between the ligand and receptor. Auto Dock is an open-source freeware program used to predict docking poses. It uses LGA) Lamarckian genetic algorithm to enumerate the binding energy. In this research work, we proposed an approach of hybrid Differential evolution base Lamarckian genetic (DELGA) algorithm to calculate the lowest binding energy. The experiment conducted to compute the 65 molecular instances, the results exposed that our approach predicts lowest docking energy with minimum root mean square deviation (RMSD) in comparison to the LGA, SA and PSO algorithms.
Keywords: Molecular Docking, Optimization algorithms, Binding Energy, Evolutionary Algorithms.
Scope of the Article: Design Optimization of Structures