Paper Title :Drug Potency Prediction on Coronavirus Target Replicase Polyprotein 1AB Chembl4523582 Using Random Forest

Author :Preslyn Peter, Michael Moses T

Article Citation :Preslyn Peter ,Michael Moses T , (2022 ) " Drug Potency Prediction on Coronavirus Target Replicase Polyprotein 1AB Chembl4523582 Using Random Forest " , International Journal of Advances in Science, Engineering and Technology(IJASEAT) , pp. 76-79, Volume-10,Issue-3

Abstract : Abstract - One of the major objectives of drug discovery is to identify bioactive molecular structures that could interfere with molecular processes, allowing the possibility of curing a disease. Past research has confirmed replicase polyprotein 1ab being responsible for virulence. However the study is done on CHEMBL5118(SARS coronavirus) and not on CHEMBL4523582(Severe acute respiratory syndrome coronavirus 2).With SARS Coronavirus 2 being responsible for the pandemic it becomes extremely important to identify the inhibitors of CHEMBL4523582 The difference structural properties cause different biological activities. Quantitative structure-activity relationship (QSAR) is a computational or mathematical modeling method to reveal relationships between biological activities and the structural properties of chemical compounds. The biological activity of a compound is quantified either by its affinity (given as Ki/Kd) and/or by its potency (given as IC50/EC50). In this study, the data was taken from the ChemBl database of the Target named replicase polyprotein 1ab CHEMBL4523582. Lipinski descriptors and PubChem molecular descriptors were calculated for all the compounds and a curated dataset was obtained. The data was then subjected to the machine learning Random Forest. The model provided a Q2 value of 0.8398 and R2 value of 0.75.41 which have passed the model acceptance criteria provided by Tropsha A, Golbraikh. Keywords - Random Forest, CHEMBL4523582, PubChem Molecular Descriptor, QSAR, pIC50

Type : Research paper

Published : Volume-10,Issue-3

	|		PDF	|	Viewed - 51	|	Published on 2022-11-08