DRUG DISCOVERY VIA REINFORCEMENT LEARNING WITH THREE-DIMENSIONAL MODELING
(iEdison No. 0685901-21-0044)

Patent ID: 10717 | Status: Filed

Abstract

In this contribution, we propose a novel framework, 3D-MolGNNRL, coupling reinforcement learning (RL) to a deep generative model based on 3D-Scaffold to generate target candidates specific to a protein pocket building up atom by atom from the core scaffold. 3D-MolGNNRL provides an efficient way to optimize key features within a protein pocket using a parallel graph neural network model. The agent learns to build molecules in 3D space while optimizing the binding affinity, potency, and synthetic accessibility of the candidates generated for the SARS-CoV-2 Main protease.

Application Number

18/370,814

Inventors

Bontha,Mridula V S
Kumar,Neeraj
Pope,Jenna A
McNaughton,Andrew D
Knutson,Carter R

Market Sector

Biological Sciences and Omics