@article{DIVYA T_YAMUNA M_2019, title={DRUG pKa VALUE PREDICTION – FROM COMPRESSED GRAPH}, volume={7}, url={https://journals.innovareacademics.in/index.php/ijet/article/view/29034}, abstractNote={<p><strong>Objective: </strong>Topological indices are interesting since they capture some of the properties of a molecule in a single number. pKa value indicates the strength of the acid in each molecule of the chemical compounds or drugs. The objective of this research was to predict the pKa value of drugs using graph theory.</p> <p><strong>Method: </strong>In this paper, we use a graph property eccentricity and the regression, a statistical model to predict the value of pKa by compressing the hexagonal system of the graph structure of drugs which reduces the calculation of eccentricity.</p> <p><strong>Results: </strong>pKa value of the new medicine can be determined using regression analysis by fitting in a linear equation of a straight line.</p> <p><strong>Conclusion: </strong>The results obtained in this research work clearly indicated that we found out the pKa value of local anesthesia which has similar structures. Further, we can use this method for other physicochemical properties such as boiling point, melting point, and vapor pressure by compressing the drug graph.</p>}, number={5}, journal={Innovare Journal of Engineering and Technology}, author={DIVYA T and YAMUNA M}, year={2019}, month={Sep.}, pages={1–6} }