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NanoAgents: Molecular Docking Using Multi-Agent Technology
M. Harindra R. Fernando, Asoka S. Karunananda, Roshan P. Perera
Pages - 37 - 51     |    Revised - 31-07-2016     |    Published - 31-08-2016
Volume - 7   Issue - 3    |    Publication Date - August 2016  Table of Contents
Molecular Docking, Multi-agent, Drug Discovery.
Traditional computer-based simulators for manual molecular docking for rational drug discovery have been very time consuming. In this research, a multi agent-based solution, named as NanoAgent, has been developed to automate the drug discovery process with little human intervention. In this solution, ligands and proteins are implemented as agents who pose the knowledge of permitted connections with other agents to form new molecules. The system also includes several other agents for surface determination, cavity finding and energy calculation. These agents autonomously activate and communicate with each other to come up with a most probable structure over the ligands and proteins, which are participating in deliberation. Domain ontology is maintained to store the common knowledge of molecular bindings, whereas specific rules pertaining to the behaviour of ligands and proteins are stored in their personal ontologies. Existing, Protein Data Bank (PDB) has also been used to calculate the space required by ligand to bond with the receptor. The drug discovery process of NanoAgent has exemplified exciting features of multi agent technology, including communication, coordination, negotiation, butterfly effect, self-organizing and emergent behaviour. Since agents consume fewer computing resources, NanoAgent has recorded optimal performance during the drug discovery process. NanoAgent has been tested for the discovery of the known drugs for the known protein targets. It has 80% accuracy by considering the prediction of the correct actual existence of the docked molecules using energy calculations. By comparing the time taken for the manual docking process with the time taken for the molecular docking by NanoAgent, there has been 95% efficiency.
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Mr. M. Harindra R. Fernando
University of Moratuwa - Sri Lanka
Professor Asoka S. Karunananda
General Sir John Kotelawala Defence University, Sri Lanka - Sri Lanka
Professor Roshan P. Perera
General Sir John Kotelawala Defence University, Sri Lanka - Sri Lanka