Evidence map›Paper›PMID 35132139›Full record

ArticleScientific reports2022

A highly accurate metadynamics-based Dissociation Free Energy method to calculate protein-protein and protein-ligand binding potencies.

Jing Wang, Alexey Ishchenko, Wei Zhang, Asghar Razavi, David Langley

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

  1. ModBindProceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  2. Article
  3. Free Energy and Flexibility Analysis of Autoinhibited Human BRAF.Journal of chemical information and modeling · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. In Vitro and In Vivo Effects of Resveratrol on Rat Hepatic CYP1A2.Pharmaceuticals (Basel, Switzerland) · 2025
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. ModBind, a Rapid Simulation-Based Predictor of Ligand Binding and Off-Rates.Journal of chemical information and modeling · 2025
    Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Molecular Dynamics Simulations in Protein-Protein Docking.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  19. Article
  20. 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

5 authors.

Jing WangArvinas, Inc., 5 Science Park, New Haven, CT, 06511, USA. jing.wang@arvinas.com.
Alexey IshchenkoArvinas, Inc., 5 Science Park, New Haven, CT, 06511, USA.
Wei ZhangArvinas, Inc., 5 Science Park, New Haven, CT, 06511, USA.
Asghar RazaviArvinas, Inc., 5 Science Park, New Haven, CT, 06511, USA.
David LangleyArvinas, Inc., 5 Science Park, New Haven, CT, 06511, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although seeking to develop a general and accurate binding free energy calculation method for protein-protein and protein-ligand interactions has been a continuous effort for decades, only limited successes have been obtained so far. Here, we report the development of a metadynamics-based procedure that calculates Dissociation Free Energy (DFE) and its application to 19 non-congeneric protein-protein complexes and hundreds of protein-ligand complexes covering eight targets. We achieved very high correlations in comparison to experimental binding free energies for these diverse sets of systems, demonstrating the generality and accuracy of the method. Since structures of most proteins are available owing to the recent success of prediction by artificial intelligence, a general free energy method such as DFE, combined with other methods, can make structure-based drug design a widely viable and reliable solution to develop both traditional small molecule drugs and biologic drugs as well as PROTACS.

Indexed as

Drug DesignLigandsMolecular Dynamics SimulationMultiprotein ComplexesProtein BindingProteinsThermodynamicsArtificial IntelligenceEnergy TransferLigandsMultiprotein ComplexesProteins

Identifiers

PMID35132139
PMCPMC8821539

What OpenQuestion holds

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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.