Multi-objective Genetic Algorithm for De Novo Drug Design (MoGADdrug)

Title:Multi-objective Genetic Algorithm for De Novo Drug Design (MoGADdrug)

Volume: 17 Issue: 3

Author(s): R. Vasundhara Devi*, S. Siva Sathya and Mohane S. Coumar

Affiliation:

• Department of Computer Science, Pondicherry University, Pondicherry,India

Keywords: De novo drug design, drug-likeness, genetic algorithm, multi-objective optimization, oral bio-availability, tanimoto similarity.

Abstract:

Background: A multi-objective genetic algorithm for De novo drug design (MoGADdrug) has been proposed in this paper for the design of novel drug-like molecules similar to some reference molecules. The algorithm developed accepts a set of fragments extracted from approved drugs and available in fragment libraries and combines them according to specified rules to discover new drugs through the in-silico method.

Methods: For this process, a genetic algorithm has been used, which encodes the fragments as genes of variable length chromosomes and applies various genetic operators throughout the generations. A weighted sum approach is used to simultaneously optimize the structural similarity of the new drug to a reference molecule as well as its drug-likeness property.

Results: Five reference molecules namely Lidocaine, Furano-pyrimidine derivative, Imatinib, Atorvastatin and Glipizide have been chosen for the performance evaluation of the algorithm.

Conclusion: Also, the newly designed molecules were analyzed using ZINC, PubChem databases and docking investigations.

Cite this article as:

Devi Vasundhara R. *, Sathya Siva S. and Coumar S. Mohane , Multi-objective Genetic Algorithm for De Novo Drug Design (MoGADdrug), Current Computer-Aided Drug Design 2021; 17 (3) . https://dx.doi.org/10.2174/1573409916666200620194143