High-throughput binding affinity calculations at extreme scales

Jumana Dakka,Matteo Turilli,Peter V Coveney,Shantenu Jha,Vivek Balasubramanian,Stefan J Zasada,Shunzhou Wan,David W Wright

doi:10.1186/s12859-018-2506-6

Abstract

BackgroundResistance 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.ResultsWe 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.ConclusionsAs such, HTBAC advances the state of the art of binding affinity calculations and protocols. HTBAC provides the platform to enable scientists to study a wide range of cancer drugs and candidate ligands in order to support personalized clinical decision making based on genome sequencing and drug discovery.

Highlights

Resistance to chemotherapy and molecularly targeted therapies is a major factor in limiting the effectiveness of cancer treatment
In “Methods” section, we introduce RADICAL-Cybertools— a suite of building blocks to address the computational challenges—and describe how they are used by High-throughput Binding Affinity Calculator (HTBAC) to manage the execution of binding affinity calculations at extreme scales
We have developed a number of free energy calculation protocols based on the use of ensemble molecular dynamics simulations with the aim of meeting these requirements [14, 17,18,19]

Summary

Introduction

Resistance to chemotherapy and molecularly targeted therapies is a major factor in limiting the effectiveness of cancer treatment. 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. TKIs have been developed to selectively inhibit kinases involved in the signaling pathways that control growth and proliferation, which often become dysregulated in cancers. This targeting of specific cancers reduces the risk of damage to healthy cells and increases treatment success. The development of resistance to these drugs limits the amount of time that patients can derive benefits from their treatment. In some commonly targeted kinases such as Abl, these changes account for as many as 90% of treatment failure [5]

Objectives

Methods

Results

Conclusion