Work

Differential evolution-binary particle swarm optimization algorithm for the analysis of aryl β-diketo acids for HIV-1 integrase inhibition

Year: 2012

Type: conference-paper

Abstract: A hybrid differential evolution-binary particle swarm optimization (DE-BPSO) algorithm is proposed as a feature selection algorithm in the development of quantitative structure-activity relationship (QSAR) models. DE is used to evolve the velocities of the particle swarm from which a series of rules are used to determine the discrete values of the position vectors which form chemical descriptor subsets. These descriptor subsets are then used to develop models for QSAR analysis. DE-BPSO was found to outperform the standalone BPSO algorithm. The DE-BPSO algorithm was then used to develop multiple linear regression models for the analysis of aryl β-diketo acid compounds for the inhibition of HIV-1 integrase. This model highlights the significance of hydrophobicity and partial positive charges of the hydrogen atoms on the molecular surface in influencing the biological activities of these compounds for the inhibition of HIV-1 integrase.

Source: IEEE Congress on Evolutionary Computation (CEC)

DOI: 10.1109/cec.2012.6256578

Authors: Gene M. Ko, A. Srinivas Reddy, Sunil Kumar, Rajni Garg, Barbara A. Bailey, Ahmad R. Hadaegh

Institutions: San Diego State University, La Jolla Bioengineering Institute, California State University, San Marcos

Language: English

Topic: Computational Drug Discovery Methods

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W2133875871

FWCI: 1.105

Cites: 35

Cited by: 8

Related to: 10