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Concurrent and Adaptive Extreme Scale Binding Free Energy Calculations

Dakka, J; Farkas-Pall, K; Turilli, M; Wright, DW; Coveney, PV; Jha, S; (2018) Concurrent and Adaptive Extreme Scale Binding Free Energy Calculations. In: Proceedings of IEEE 14th International Conference on e-Science (e-Science) 2018. (pp. pp. 189-200). IEEE: Danvers (MA), USA. Green open access

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Abstract

The efficacy of drug treatments depends on how tightly small molecules bind to their target proteins. The rapid and accurate quantification of the strength of these interactions (as measured by 'binding affinity') is a grand challenge of computational chemistry, surmounting which could revolutionize drug design and provide the platform for patient specific medicine. Recent evidence suggests that molecular dynamics (MD) can achieve useful predictive accuracy (? 1 kcal/mol). For this predictive accuracy to impact clinical decision making, binding free energy results must be turned around rapidly and without loss of accuracy. This demands advances in algorithms, scalable software systems, and efficient utilization of supercomputing resources. We introduce a framework called HTBAC, designed to support accurate and scalable drug binding affinity calculations, while marshaling large simulation campaigns. We show that HTBAC supports the specification and execution of adaptive free-energy protocols at scale and with minimal overheads on NCSA Blue Waters. We validate the results obtained and show how adaptivity can be used to improve accuracy while reducing resource consumption of TIES, a widely used free-energy protocol.

Type: Proceedings paper
Title: Concurrent and Adaptive Extreme Scale Binding Free Energy Calculations
Event: 2018 IEEE 14th International Conference on e-Science (e-Science)
Location: Amsterdam, Netherlands
Dates: 29th-1st November 2018
ISBN-13: 978-1-5386-9156-4
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/eScience.2018.00034
Publisher version: https://doi.org/10.1109/eScience.2018.00034
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Protocols, Drugs, Computational modeling, Adaptation models, Microsoft Windows, Compounds, Adaptive systems
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Chemistry
URI: https://discovery.ucl.ac.uk/id/eprint/10071522
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