Dear friends and colleagues!

We would like to invite you to join Chemspace Webinar 'Artificial Intelligence (AI) Solutions for Computational and Organic Chemistry Tasks', which will take place at 5:00 PM (CET) on August, 27.

Please Sign in to the webinar.

Deep learning is revolutionizing many areas of science and technology. In this talk, we will provide an overview of the latest developments of machine learning and AI methods and application to the problem of drug discovery and development at Isayev’s Lab at CMU. We identify several areas where existing methods have the potential to accelerate pharmaceutical research and disrupt more traditional approaches. We will present a deep learning model that approximates the solution of the Schrodinger equation.

Focusing on parametrization for drug-like organic molecules and proteins, we have developed a single ‘universal’ model which is highly accurate compared to reference quantum mechanical calculations at speeds 10^6 faster. The potential is shown to accurately represent the underlying physical chemistry of molecules through various test cases including chemical reactions (both thermodynamics and kinetics), thermochemistry, structural optimization, and molecular dynamics simulations. The results presented in this talk will provide evidence of the broad applicability of deep learning to various chemistry problems involving organic molecules.