High-Throughput Lead Optimization with AMBER
Project Summary
This project develops an adaptive, high-throughput computational framework for predicting protein–ligand binding affinities within 60 hours, using advanced AMBER-based methods optimized for GPU supercomputing to support rapid lead optimization in drug discovery.
Project Description
The overall objective of this project is to address a major obstacle in computer-aided drug discovery and precision medicine: the absence of computational workflows capable of reliably identifying the most tight-binding ligands from a design pool of proposed compounds within 60 hours of wall-clock time (a typical time range required for a drug discovery team in industry). The researchers will develop and test a new adaptive framework for high-throughput lead optimization that integrates advanced methods and features in AMBER to achieve ligand-protein binding predictions. The framework will be optimized to run with unprecedented efficiency on advanced GPU supercomputing platforms such as Polaris.
