ReviewProteins2008
Principles of flexible protein-protein docking.
Review in Proteins, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 89 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.
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Who cites it
89 citing papers in PubMed.
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- Computable properties of selected monomeric acylphloroglucinols with anticancer and/or antimalarial activities and first-approximation docking study.Journal of molecular modeling · 2025Article
- Molecular Docking in Drug Discovery: Techniques, Applications, and Advancements.Current medicinal chemistry · 2025Review
- Multimeric protein interaction and complex prediction: Structure, dynamics and function.Computational and structural biotechnology journal · 2025Review
- Molecular Docking of Endolysins for Studying Peptidoglycan Binding Mechanism.Molecules (Basel, Switzerland) · 2024Article
- Protein language models are performant in structure-free virtual screening.Briefings in bioinformatics · 2024Article
- Virtual Screening of Peptide Libraries: The Search for Peptide-Based Therapeutics Using Computational Tools.International journal of molecular sciences · 2024Review
- Assessing Protein-Protein Docking Protocols: Case Studies of G-Protein-Coupled Receptor Interactions.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Critical Assessment of Methods for Predicting the 3D Structure of Proteins and Protein Complexes.Annual review of biophysics · 2023Review
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- In silico analysis of mutations near S1/S2 cleavage site in SARS-CoV-2 spike protein reveals increased propensity of glycosylation in Omicron strain.Journal of medical virology · 2022Article
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- Discovery of new Cdc2-like kinase 4 (CLK4) inhibitorsRSC advances · 2022Article
- Improved prediction of protein-protein interactions using AlphaFold2.Nature communications · 2022Article
- Prediction of Protein-Protein Binding Affinities from Unbound Protein Structures.Methods in molecular biology (Clifton, N.J.) · 2022Review
- Computational Modeling as a Tool to Investigate PPI: From Drug Design to Tissue Engineering.Frontiers in molecular biosciences · 2021Review
- Using collections of structural models to predict changes of binding affinity caused by mutations in protein-protein interactions.Protein science : a publication of the Protein Society · 2020Article
- Plant Antimicrobial Peptides: State of the Art, In Silico Prediction and Perspectives in the Omics Era.Bioinformatics and biology insights · 2020Review
29 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
Treating flexibility in molecular docking is a major challenge in cell biology research. Here we describe the background and the principles of existing flexible protein-protein docking methods, focusing on the algorithms and their rational. We describe how protein flexibility is treated in different stages of the docking process: in the preprocessing stage, rigid and flexible parts are identified and their possible conformations are modeled. This preprocessing provides information for the subsequent docking and refinement stages. In the docking stage, an ensemble of pre-generated conformations or the identified rigid domains may be docked separately. In the refinement stage, small-scale movements of the backbone and side-chains are modeled and the binding orientation is improved by rigid-body adjustments. For clarity of presentation, we divide the different methods into categories. This should allow the reader to focus on the most suitable method for a particular docking problem.
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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.