ReviewInterface focus2020
Rapid, accurate, precise and reproducible ligand-protein binding free energy prediction.
Review in Interface focus, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 75 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
75 citing papers in PubMed.
- Reliability of AI Methods in Drug Discovery: Evaluation of Boltz-2 for Structure and Binding Affinity Prediction.Journal of chemical theory and computation · 2026Article
- Article
- Doing More with Less: Accurate and Scalable Ligand Free Energy Calculations by Focusing on the Binding Site.Journal of chemical information and modeling · 2026Article
- A Computational Framework to Evaluate Interactions of BPA and Its Analogs with Human Liver X Receptor-Beta for Health Risk Assessment.Chemical research in toxicology · 2026Article
- Article
- Data-Efficient Equivariant NNPs Enable DFT-Accurate Simulations and Implicit Solvation Free Energies.The journal of physical chemistry. B · 2025Article
- Systematic evaluation of predictors for binding free energy changes upon mutations in protein complexes.Briefings in bioinformatics · 2025Article
- Rapid, accurate, and reproduciblemSphere · 2025Article
- A Computationally Efficient Method to Generate Plausible Conformers for Ensemble Docking and Binding Free Energy Calculations.Journal of chemical information and modeling · 2025Article
- A NewPharmaceuticals (Basel, Switzerland) · 2025Article
- Molecular Dynamics Simulations of Plasma-Antifolate Drug Synergy in Cancer Therapy.Biomolecules · 2025Article
- Computational identification of aspartic protease inhibitors for antimalarial drug development against Plasmodium Vivax.Scientific reports · 2025Article
- Mechanism of astragaloside A against lung adenocarcinoma based on network pharmacology combined with molecular dynamics simulation technique.Scientific reports · 2025Article
- DeepConf: Leveraging ANI-ML Potentials for Exploring Local Minima with Application to Bioactive Conformations.Journal of chemical information and modeling · 2025Article
- Impact of Varying Velocities and Solvation Boxes on Alchemical Free-Energy Simulations.Journal of chemical information and modeling · 2025Article
- Rapid, Accurate and Reproducible Prediction of the Glass Transition Temperature Using Ensemble-Based Molecular Dynamics Simulation.Journal of chemical theory and computation · 2025Article
- Anticancer Potential of Quercetin on Oral Squamous Cell Carcinoma: A Scoping Review and Molecular Docking.European journal of dentistry · 2025Article
- Structure-based computational design of antibody mimetics: challenges and perspectives.FEBS open bio · 2025Review
- Rationalizing protein-ligand interactions via the effective fragment potential method and structural data from classical molecular dynamics.The Journal of chemical physics · 2025Article
- The impact of curation errors in the PDBBind Database on machine learning predictions of protein-protein binding affinity.Database : the journal of biological databases and curation · 2025Article
15 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
A central quantity of interest in molecular biology and medicine is the free energy of binding of a molecule to a target biomacromolecule. Until recently, the accurate prediction of binding affinity had been widely regarded as out of reach of theoretical methods owing to the lack of reproducibility of the available methods, not to mention their complexity, computational cost and time-consuming procedures. The lack of reproducibility stems primarily from the chaotic nature of classical molecular dynamics (MD) and the associated extreme sensitivity of trajectories to their initial conditions. Here, we review computational approaches for both relative and absolute binding free energy calculations, and illustrate their application to a diverse set of ligands bound to a range of proteins with immediate relevance in a number of medical domains. We focus on ensemble-based methods which are essential in order to compute statistically robust results, including two we have recently developed, namely thermodynamic integration with enhanced sampling and enhanced sampling of MD with an approximation of continuum solvent. Together, these form a set of rapid, accurate, precise and reproducible free energy methods. They can be used in real-world problems such as hit-to-lead and lead optimization stages in drug discovery, and in personalized medicine. These applications show that individual binding affinities equipped with uncertainty quantification may be computed in a few hours on a massive scale given access to suitable high-end computing resources and workflow automation. A high level of accuracy can be achieved using these approaches.
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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.