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Siddhartha Laghuvarapu –  Dual Degree CNS

Siddhartha Laghuvarapu received his MS-Dual Degree in Computational Natural Sciences. His  research work was supervised by Dr. U Deva Priyakumar.

Here’s a summary of  Siddhartha’s M.S thesis, Deep learning for prediction of molecular properties and drug interactions as explained by him: 

Accurate and fast estimation of energies is an important problem in Computational Chemistry as they are essential to model various chemical and biological processes. Traditional QM based methods, although very accurate, cannot be scaled to large systems. Deep learning methods offer a computationally tractable alternative while also being accurate. In my work, a novel deep learning model based on chemically interpretable features is developed for accurate energy prediction. Through various experiments, it has been shown to be accurate across chemical tasks. The second part of my thesis deals with prediction of drug-drug interactions using deep learning. Prediction of adverse Drug-drug interactions is an important consideration while preparing new drugs and their experimental evaluation is expensive. In my work, a novel deep learning model for accurate prediction of drug-drug interactions is proposed.