High-throughput Binding Affinity Calculations at Extreme Scales

TL;DR

This paper introduces HTBAC, a scalable high-performance computing framework that significantly accelerates binding affinity calculations, enabling rapid and flexible drug discovery processes at extreme computational scales.

Contribution

The paper presents HTBAC, a novel, scalable, and automated framework for high-throughput binding affinity calculations on supercomputers, improving speed and flexibility.

Findings

Achieves near-perfect weak scaling on hundreds of pipelines

Enables rapid, protocol-invariant binding affinity calculations

Advances state-of-the-art in computational drug discovery

Abstract

Resistance to chemotherapy and molecularly targeted therapies is a major factor in limiting the effectiveness of cancer treatment. In many cases, resistance can be linked to genetic changes in target proteins, either pre-existing or evolutionarily selected during treatment. Key to overcoming this challenge is an understanding of the molecular determinants of drug binding. Using multi-stage pipelines of molecular simulations we can gain insights into the binding free energy and the residence time of a ligand, which can inform both stratified and personal treatment regimes and drug development. To support the scalable, adaptive and automated calculation of the binding free energy on high-performance computing resources, we introduce the High- throughput Binding Affinity Calculator (HTBAC). HTBAC uses a building block approach in order to attain both workflow flexibility and performance. We demonstrate close to perfect weak scaling to hundreds of concurrent multi-stage binding affinity calculation pipelines. This permits a rapid time-to-solution that is essentially invariant of the calculation protocol, size of candidate ligands and number of ensemble simulations. As such, HTBAC advances the state of the art of binding affinity calculations and protocols.