ArticleBMC bioinformatics2015
PCalign: a method to quantify physicochemical similarity of protein-protein interfaces.
Article in BMC bioinformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- A Review of Current Computational Tools for Peptide-Protein Docking.Journal of computational chemistry · 2026Review
- In Silico Ligand-Based Screening of PDB Database for Searching Unique Motifs Against SARS-CoV-2.Biomolecules · 2026Article
- In silico screening of protein-binding peptides with an application to developing peptide inhibitors against antibiotic resistance.PNAS nexus · 2024Article
- Database-Driven Identification of Structurally Similar Protein-Protein Interfaces.Journal of chemical information and modeling · 2024Article
- Quantitative comparison of protein-protein interaction interface using physicochemical feature-based descriptors of surface patches.Frontiers in molecular biosciences · 2023Article
- Predicting Protein-Peptide Complex Structures by Accounting for Peptide Flexibility and the Physicochemical Environment.Journal of chemical information and modeling · 2022Article
- PatchSearch: a web server for off-target protein identification.Nucleic acids research · 2019Article
- Capturing a Dynamic Chaperone-Substrate Interaction Using NMR-Informed Molecular Modeling.Journal of the American Chemical Society · 2016Article
- G-LoSA: An efficient computational tool for local structure-centric biological studies and drug design.Protein science : a publication of the Protein Society · 2016Article
- Protein-Protein Interfaces in Viral Capsids Are Structurally Unique.Journal of molecular biology · 2015Article
- Predicting the Effect of Mutations on Protein-Protein Binding Interactions through Structure-Based Interface Profiles.PLoS computational biology · 2015Article
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3 authors.
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Abstract
backgroundStructural comparison of protein-protein interfaces provides valuable insights into the functional relationship between proteins, which may not solely arise from shared evolutionary origin. A few methods that exist for such comparative studies have focused on structural models determined at atomic resolution, and may miss out interesting patterns present in large macromolecular complexes that are typically solved by low-resolution techniques.
resultsWe developed a coarse-grained method, PCalign, to quantitatively evaluate physicochemical similarities between a given pair of protein-protein interfaces. This method uses an order-independent algorithm, geometric hashing, to superimpose the backbone atoms of a given pair of interfaces, and provides a normalized scoring function, PC-score, to account for the extent of overlap in terms of both geometric and chemical characteristics. We demonstrate that PCalign outperforms existing methods, and additionally facilitates comparative studies across models of different resolutions, which are not accommodated by existing methods. Furthermore, we illustrate potential application of our method to recognize interesting biological relationships masked by apparent lack of structural similarity.
conclusionsPCalign is a useful method in recognizing shared chemical and spatial patterns among protein-protein interfaces. It outperforms existing methods for high-quality data, and additionally facilitates comparison across structural models with different levels of details with proven robustness against noise.
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