Stable Drug Designing By Minimizing Drug Protein Interaction Energy Using PSO

TL;DR

This paper introduces a PSO-based method for designing drugs by optimizing their structure to minimize drug-protein interaction energy, considering variable-length structures and multiple forces for improved accuracy.

Contribution

It presents a novel PSO algorithm that models drugs as variable-length trees and optimizes their structure and orientation for stable binding to target proteins.

Findings

PSO outperforms previous drug design methods.

Optimized drugs show lower docking energy.

Enhanced accuracy by considering multiple inter-molecular forces.

Abstract

Each and every biological function in living organism happens as a result of protein-protein interactions.The diseases are no exception to this. Identifying one or more proteins for a particular disease and then designing a suitable chemical compound (known as drug) to destroy these proteins has been an interesting topic of research in bio-informatics. In previous methods, drugs were designed using only seven chemical components and were represented as a fixed-length tree. But in reality, a drug contains many chemical groups collectively known as pharmacophore. Moreover, the chemical length of the drug cannot be determined before designing the drug.In the present work, a Particle Swarm Optimization (PSO) based methodology has been proposed to find out a suitable drug for a particular disease so that the drug-protein interaction becomes stable. In the proposed algorithm, the drug is represented as a variable length tree and essential functional groups are arranged in different positions of that drug. Finally, the structure of the drug is obtained and its docking energy is minimized simultaneously. Also, the orientation of chemical groups in the drug is tested so that it can bind to a particular active site of a target protein and the drug fits well inside the active site of target protein. Here, several inter-molecular forces have been considered for accuracy of the docking energy. Results show that PSO performs better than the earlier methods.