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Ligand Design- A Multiobjective Optimization Based Approach
Sreedhar D. and Chandrika S.

Published in: International Journal of Computer Sciences and Engineering
Volume- 5, Issue-2, pp.141-147, Feb 2017
DPI :-> 16.10022.IJCSE.2017.V5I2.141147.1265

Excess accumulation or inadequate production of certain protein leads to diseases. A drug can play most important role in this scenario. A drug is an organic molecule that triggers or inhibits the function of a biomolecule such as a protein; this will be beneficial to the patient. In the most basic sense, drug design involves the design of small molecules that are complementary in shape and charge to the bio molecular target with which they interact and therefore will bind to it. The process of drug discovery by laboratory experiments is time consuming and very expensive. To reduce the time and cost of drug discovery process, computational techniques are incorporated to speed up the process. Initially dock the molecular fragments obtained by breaking the sigma bonds between the bioactive molecules against tuberculosis to the target site of the protein using docking software known as AutoDock. The score obtained from this is given as input to the program. Then, prioritize the fragments using Multiobjective Differential Evolution (MODE) algorithm with two objectives namely oral bioavailability and free energy. Next step is to design set of ligand molecules that can be represented as an array of fragments. Then analyses the performance of proposed approach by comparing it with another multiobjective optimization algorithm namely Archived Multiobjective Simulated Annealing (AMOSA).

Key-Words / Index Term
Drug Discovery, Drug Design, Multi-objective Differential Evolution, AMOSA

How to cite this article
Sreedhar D. and Chandrika S. , “ Ligand Design- A Multiobjective Optimization Based Approach”, International Journal of Computer Sciences and Engineering, 5, Issue-2, pp.141-147, Feb 2017. DPI:16.10022.IJCSE.V5.I2.1265