ArticleProceedings of the National Academy of Sciences of the United States of America2022
Matching protein surface structural patches for high-resolution blind peptide docking.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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16 citing papers in PubMed, 33 citations in OpenAlex.
- Strategic Template Filtering Accelerates Fragment-Based Peptide Docking.Journal of chemical information and modeling · 2026Article
- Structural basis of signal peptide recognition by the signal peptidase complex.Nature communications · 2026Article
- Peptide-protein docking: from physics-based models to generative intelligence.Chemical communications (Cambridge, England) · 2026Review
- A Review of Current Computational Tools for Peptide-Protein Docking.Journal of computational chemistry · 2026Review
- Peptide-based drug design using generative AI.Chemical communications (Cambridge, England) · 2026Review
- Docking in the Dark: Insights into Protein-Protein and Protein-Ligand Blind Docking.Pharmaceuticals (Basel, Switzerland) · 2025Review
- A Computational Perspective to Intermolecular Interactions and the Role of the Solvent on Regulating Protein Properties.Chemical reviews · 2025Review
- Nesprin-2 contains BH3-like motifs that can promote cell death.Cell death discovery · 2025Article
- Elucidation of short linear motif-based interactions of the MIT and rhodanese domains of the ubiquitin-specific protease 8.Biology direct · 2025Article
- Collagen-targeted protein nanomicelles for the imaging of non-alcoholic steatohepatitis.Acta biomaterialia · 2024Article
- Current Computational Methods for Protein-peptide Complex Structure Prediction.Current medicinal chemistry · 2024Review
- Computational Study of Driving Forces in ATSP, PDIQ, and P53 Peptide Binding: C═O···C═O Tetrel Bonding Interactions at Work.Journal of chemical information and modeling · 2023Article
- Review
- Funneling modulatory peptide design with generative models: Discovery and characterization of disruptors of calcineurin protein-protein interactions.PLoS computational biology · 2023Article
- Towards rational computational peptide design.Frontiers in bioinformatics · 2022Article
- Modelling peptide-protein complexes: docking, simulations and machine learning.QRB discovery · 2022Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Peptide docking can be perceived as a subproblem of protein–protein docking. However, due to the short length and flexible nature of peptides, many do not adopt one defined conformation prior to binding. Therefore, to tackle a peptide docking problem, not only the relative orientation, but also the bound conformation of the peptide needs to be modeled. Traditional peptide-centered approaches use information about peptide sequences to generate representative conformer ensembles, which can then be rigid-body docked to the receptor. Alternatively, one may look at this problem from the viewpoint of the receptor, namely, that the protein surface defines the peptide-bound conformation. Here, we present PatchMAN (Patch-Motif AligNments), a global peptide-docking approach that uses structural motifs to map the receptor surface with backbone scaffolds extracted from protein structures. On a nonredundant set of protein–peptide complexes, starting from free receptor structures, PatchMAN successfully models and identifies near-native peptide–protein complexes in 58%/84% within 2.5 Å/5 Å interface backbone RMSD, with corresponding sampling in 81%/100% of the cases, outperforming other approaches. PatchMAN leverages the observation that structural units of peptides with their binding pocket can be found not only within interfaces, but also within monomers. We show that the bound peptide conformation is sampled based on the structural context of the receptor only, without taking into account any sequence information. Beyond peptide docking, this approach opens exciting new avenues to study principles of peptide–protein association, and to the design of new peptide binders. PatchMAN is available as a server at https://furmanlab.cs.huji.ac.il/patchman/.
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