Comparison of three nature inspired molecular docking algorithms
by Petra Čechová; Martin Kubala
International Journal of Bio-Inspired Computation (IJBIC), Vol. 17, No. 1, 2021

Abstract: Molecular docking uses different methods to generate and evaluate the binding between a receptor and a ligand. Three nature-inspired docking programs are compared on a test set of 65 receptor-ligand pairs. AutoDock uses a genetic algorithm inspired by the process of natural selection; PSOVina^2LS uses the particle swarm optimisation method, based on the behaviour of animal flocks and PLANTS uses an algorithm based on ant colonies. Using the default parameters, PSOVina^2LS achieved the best performance with respect to time required and docking accuracy, followed by PLANTS and, with a large gap, AutoDock. However, all the programs exhibited difficulties with redocking of ligands with more than ten rotable bonds.

Online publication date: Mon, 01-Mar-2021

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Bio-Inspired Computation (IJBIC):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com