Evidence map›Paper›PMID 41546627›Full record

ArticleJournal of chemical information and modeling2026

A Relative Binding Free Energy Framework for Structurally Dissimilar Molecules.

Hsu-Chun Tsai, Shi Zhang, Tai-Sung Lee, Timothy J Giese, Charles Lin, James Xu, Yinhui Yi, Darrin M York, Abir Ganguly, Albert C Pan

Abstract read
In one paragraph

Article in Journal of chemical information and modeling, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. The Five-Decade Journey of Small Cell Lung Cancer.Cancer communications (London, England) · 2026
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Hsu-Chun TsaiTandemAI, New York, New York 10036, United States.ORCID 0000-0001-7027-5649
Shi ZhangLaboratory for Biomolecular Simulation Research,Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, New Jersey 08854, United States.
Tai-Sung LeeLaboratory for Biomolecular Simulation Research,Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, New Jersey 08854, United States.ORCID 0000-0003-2110-2279
Timothy J GieseLaboratory for Biomolecular Simulation Research,Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, New Jersey 08854, United States.
Charles LinTandemAI, New York, New York 10036, United States.
James XuTandemAI, New York, New York 10036, United States.
Yinhui YiTandemAI, New York, New York 10036, United States.
Darrin M YorkLaboratory for Biomolecular Simulation Research,Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, New Jersey 08854, United States.ORCID 0000-0002-9193-7055
Abir GangulyTandemAI, New York, New York 10036, United States.ORCID 0000-0002-0630-1109
Albert C PanTandemAI, New York, New York 10036, United States.

Funding

Next-generation integrated quantum force fields for biomedical applicationsR01GM107485 · NIGMS · RUTGERS, THE STATE UNIV OF N.J. · PI Darrin M York · 2015 to 2026
$3.8M
A next-generation extendable simulation environment for affordable, accurate, and efficient free energy simulationsR01GM149874 · NIGMS · RUTGERS, THE STATE UNIV OF N.J. · PI TAI-SUNG LEE · 2023 to 2026
$1.3M
NIGMS NIH HHS R01 GM107485NIGMS NIH HHS R01 GM149874
6 · The paper itself

Abstract

Relative binding free energy (RBFE) calculations, widely used to predict the potencies of congeneric small molecules binding to a protein receptor, can greatly increase the efficiency of the hit-to-lead and lead optimization stages of the drug discovery process. Traditional RBFE methods, however, cannot be easily applied to small molecules lacking a common core or binding mode, precluding their use in a challenging but crucial component of many drug discovery campaigns. In principle, an absolute binding free energy (ABFE) method can be applied to such molecules, but ABFE often suffers from high computational cost and poor statistical convergence due to the large amount of additional sampling required when compared to RBFE. Here, we introduce core-hopping binding free energy (CBFE) calculations, a computationally efficient framework for the accurate determination of relative binding free energies between small molecules with different cores, leveraging several recently developed techniques such as Alchemical Enhanced Sampling (ACES) with optimized transformation pathways and flexible λ-spacing, as well as λ-dependent Boresch restraints. We benchmark the performance of CBFE across 4 protein systems consisting of 56 small molecules, and find that the results are consistent with RBFE for a congeneric series of ligands and offer considerable improvement in computational cost and precision relative to ABFE results for a series of small molecules with diverse cores and binding modes. All CBFE-related developments are fully implemented in the GPU-accelerated AMBER free energy module (pmemd.cuda) and are available as part of the latest official AMBER release.

Indexed as

Small Molecule LibrariesDrug DiscoveryLigandsProtein BindingProteinsThermodynamicsLigandsProteinsSmall Molecule Libraries

Identifiers

PMID41546627
PMCPMC12998237

What OpenQuestion holds

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LicenceTDM
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Registered trials

None linked

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.