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.
