Application of 3D Pose Similarity in Molecular Docking on Ensemble of Crystal-Structures for Accurate Prediction of Activity

This project aims to develop a method for accurately assessing the enzymatic activity of large libraries of compounds. To do this we will employ computational modeling of small molecules in an ensemble of protein crystal structures. The results of this work will lead to a better understanding of the relationship between docked poses and crystal poses, and of the relationship between docked poses and pharmacological activity. The results of this work will help Variational AI understand how to effectively leverage docked poses to more accurately predict and optimize pharmacological activity, facilitating Variational AI’s drug discovery efforts.

Faculty Supervisor:

Rebecca Davis

Student:

Partner:

Variational AI

Discipline:

Physics

Sector:

Professional, scientific and technical services

University:

University of Manitoba

Program: