Evidence map›Paper›PMID 40999494›Full record

ArticleJournal of cheminformatics2025

Evaluating ligand docking methods for drugging protein-protein interfaces: insights from AlphaFold2 and molecular dynamics refinement.

Jordi Gómez Borrego, Marc Torrent Burgas

Abstract read
In one paragraph

Article in Journal of cheminformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

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3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. The Five-Decade Journey of Small Cell Lung Cancer.Cancer communications (London, England) · 2026
    Review
  9. Article
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

2 authors.

Jordi Gómez BorregoThe Systems Biology of Infection Laboratory, Department of Biochemistry and Molecular Biology, Biosciences Faculty, Universitat Autònoma de Barcelona, 08193, Cerdanyola del Vallès, Spain.
Marc Torrent BurgasThe Systems Biology of Infection Laboratory, Department of Biochemistry and Molecular Biology, Biosciences Faculty, Universitat Autònoma de Barcelona, 08193, Cerdanyola del Vallès, Spain. marc.torrent@uab.cat.

Funding

Generalitat de Catalunya 2023 FI-100278Ministerio de Ciencia e Innovación PDC2021-121544-I00
6 · The paper itself

Abstract

Advances in docking protocols have significantly enhanced the field of protein-protein interaction (PPI) modulation, with AlphaFold2 (AF2) and molecular dynamics (MD) refinements playing pivotal roles. This study evaluates the performance of AF2 models against experimentally solved structures in docking protocols targeting PPIs. Using a dataset of 16 interactions with validated modulators, we benchmarked eight docking protocols, revealing similar performance between native and AF2 models. Local docking strategies outperformed blind docking, with TankBind_local and Glide providing the best results across the structural types tested. MD simulations and other ensemble generation algorithms such as AlphaFlow, refined both native and AF2 models, improving docking outcomes but showing significant variability across conformations. These results suggest that, while structural refinement can enhance docking in some cases, overall performance appears to be constrained by limitations in scoring functions and docking methodologies. Although protein ensembles can improve virtual screening, predicting the most effective conformations for docking remains a challenge. These findings support the use of AF2-generated structures in docking protocols targeting PPIs and highlight the need to improve current scoring methodologies. SCIENTIFIC CONTRIBUTION: This study provides a systematic benchmark of docking protocols applied to protein-proteininteractions (PPIs) using both experimentally solved structures and AlphaFold2 models. Byintegrating molecular dynamics ensembles and AlphaFlow-generated conformations, we showthat structural refinement improves docking outcomes in selected cases, but overallperformance remains constrained by docking scoring function limitations. Our analysis showsthat AlphaFold2 models perform comparably to native structures in PPI docking, validating theiruse when experimental data are unavailable. These results establish a reference framework forfuture PPI-focused virtual screening and underscore the need for improved scoring functionsand ensemble-based approaches to better exploit emerging structural prediction tools.

Indexed as

AlphaFoldBenchmarkingMolecular dockingMolecular dynamicsProtein interactionVirtual screening

Identifiers

PMID40999494
PMCPMC12465486

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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.