ArticleScientific reports2019
Accurate Classification of Biological and non-Biological Interfaces in Protein Crystal Structures using Subtle Covariation Signals.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- ESpma: A method for assessing biological/non-biological interfaces using point-clouds-based structural features and protein language models.Protein science : a publication of the Protein Society · 2026Article
- Efficacy of phage vB_Ps_ZCPS13 in controlling Pan-drug-resistant Pseudomonas aeruginosa from urinary tract infections (UTIs) and eradicating biofilms from urinary catheters.Virology journal · 2025Article
- RNA sculpting by the primordial Helix-clasp-Helix-Strand-Loop (HcH-SL) motif enforces chemical recognition enabling diverse KH domain functions.The Journal of biological chemistry · 2025Review
- Protein-protein interaction prediction methods: from docking-based to AI-based approaches.Biophysical reviews · 2022Review
- Simple mechanisms for the evolution of protein complexity.Protein science : a publication of the Protein Society · 2022Review
- PDB-wide identification of physiological hetero-oligomeric assemblies based on conserved quaternary structure geometry.Structure (London, England : 1993) · 2021Article
- Modeling and Structure Determination of Homo-Oligomeric Proteins: An Overview of Challenges and Current Approaches.International journal of molecular sciences · 2021Review
- QSalignWeb: A Server to Predict and Analyze Protein Quaternary Structure.Frontiers in molecular biosciences · 2021Review
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2 authors.
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Abstract
Proteins often work as oligomers or multimers in vivo. Therefore, elucidating their oligomeric or multimeric form (quaternary structure) is crucially important to ascertain their function. X-ray crystal structures of numerous proteins have been accumulated, providing information related to their biological units. Extracting information of biological units from protein crystal structures represents a meaningful task for modern biology. Nevertheless, although many methods have been proposed for identifying biological units appearing in protein crystal structures, it is difficult to distinguish biological protein-protein interfaces from crystallographic ones. Therefore, our simple but highly accurate classifier was developed to infer biological units in protein crystal structures using large amounts of protein sequence information and a modern contact prediction method to exploit covariation signals (CSs) in proteins. We demonstrate that our proposed method is promising even for weak signals of biological interfaces. We also discuss the relation between classification accuracy and conservation of biological units, and illustrate how the selection of sequences included in multiple sequence alignments as sources for obtaining CSs affects the results. With increased amounts of sequence data, the proposed method is expected to become increasingly useful.
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