ArticleBMC bioinformatics2018
High-throughput binding affinity calculations at extreme scales.
Article in BMC bioinformatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Equilibrium and Nonequilibrium Ensemble Methods for Accurate, Precise and Reproducible Absolute Binding Free Energy Calculations.Journal of chemical theory and computation · 2025Article
- TIES 2.0: A Dual-Topology Open Source Relative Binding Free Energy Builder with Web Portal.Journal of chemical information and modeling · 2023Article
- Pre-exascale HPC approaches for molecular dynamics simulations. Covid-19 research: A use case.Wiley interdisciplinary reviews. Computational molecular science · 2022Article
- Ensembles Are Required to Handle Aleatoric and Parametric Uncertainty in Molecular Dynamics Simulation.Journal of chemical theory and computation · 2021Article
- Estrogenic activity of lignin-derivable alternatives to bisphenol A assessedRSC advances · 2021Article
- Rapid, accurate, precise and reproducible ligand-protein binding free energy prediction.Interface focus · 2020Review
- Continuous Evaluation of Ligand Protein Predictions: A Weekly Community Challenge for Drug Docking.Structure (London, England : 1993) · 2019Article
- Application of ESMACS binding free energy protocols to diverse datasets: Bromodomain-containing protein 4.Scientific reports · 2019Article
- Adaptive ensemble simulations of biomolecules.Current opinion in structural biology · 2018Review
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.