ArticleBMC bioinformatics2008
SCOWLP classification: structural comparison and analysis of protein binding regions.
Article in BMC bioinformatics, 2008. 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.
- Review of computational methods for virus-host protein interaction prediction: a case study on novel Ebola-human interactions.Briefings in functional genomics · 2018Review
- Rational Structure-Based Rescaffolding Approach to De Novo Design of Interleukin 10 (IL-10) Receptor-1 Mimetics.PloS one · 2016Article
- Non-redundant unique interface structures as templates for modeling protein interactions.PloS one · 2014Article
- KBDOCK 2013: a spatial classification of 3D protein domain family interactions.Nucleic acids research · 2014Article
- Computational study and peptide inhibitors design for the CDK9 - cyclin T1 complex.Journal of molecular modeling · 2013Article
- GIRAF: a method for fast search and flexible alignment of ligand binding interfaces in proteins at atomic resolution.Biophysics (Nagoya-shi, Japan) · 2012Article
- InterEvol database: exploring the structure and evolution of protein complex interfaces.Nucleic acids research · 2012Article
- SCOWLP update: 3D classification of protein-protein, -peptide, -saccharide and -nucleic acid interactions, and structure-based binding inferences across folds.BMC bioinformatics · 2011Article
- Comprehensive, atomic-level characterization of structurally characterized protein-protein interactions: the PICCOLO database.BMC bioinformatics · 2011Article
- Article
- Catalytic residues in hydrolases: analysis of methods designed for ligand-binding site prediction.Journal of computer-aided molecular design · 2011Article
- 3did: identification and classification of domain-based interactions of known three-dimensional structure.Nucleic acids research · 2011Article
- Novel peptide-mediated interactions derived from high-resolution 3-dimensional structures.PLoS computational biology · 2010Article
- A survey of available tools and web servers for analysis of protein-protein interactions and interfaces.Briefings in bioinformatics · 2009Article
- Analysis of the impact of solvent on contacts prediction in proteins.BMC structural biology · 2009Article
- Energetic determinants of protein binding specificity: insights into protein interaction networks.Proteomics · 2009Article
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4 authors.
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Abstract
backgroundDetailed information about protein interactions is critical for our understanding of the principles governing protein recognition mechanisms. The structures of many proteins have been experimentally determined in complex with different ligands bound either in the same or different binding regions. Thus, the structural interactome requires the development of tools to classify protein binding regions. A proper classification may provide a general view of the regions that a protein uses to bind others and also facilitate a detailed comparative analysis of the interacting information for specific protein binding regions at atomic level. Such classification might be of potential use for deciphering protein interaction networks, understanding protein function, rational engineering and design. DESCRIPTION: Protein binding regions (PBRs) might be ideally described as well-defined separated regions that share no interacting residues one another. However, PBRs are often irregular, discontinuous and can share a wide range of interacting residues among them. The criteria to define an individual binding region can be often arbitrary and may differ from other binding regions within a protein family. Therefore, the rational behind protein interface classification should aim to fulfil the requirements of the analysis to be performed.We extract detailed interaction information of protein domains, peptides and interfacial solvent from the SCOWLP database and we classify the PBRs of each domain family. For this purpose, we define a similarity index based on the overlapping of interacting residues mapped in pair-wise structural alignments. We perform our classification with agglomerative hierarchical clustering using the complete-linkage method. Our classification is calculated at different similarity cut-offs to allow flexibility in the analysis of PBRs, feature especially interesting for those protein families with conflictive binding regions. The hierarchical classification of PBRs is implemented into the SCOWLP database and extends the SCOP classification with three additional family sub-levels: Binding Region, Interface and Contacting Domains. SCOWLP contains 9,334 binding regions distributed within 2,561 families. In 65% of the cases we observe families containing more than one binding region. Besides, 22% of the regions are forming complex with more than one different protein family.
conclusionThe current SCOWLP classification and its web application represent a framework for the study of protein interfaces and comparative analysis of protein family binding regions. This comparison can be performed at atomic level and allows the user to study interactome conservation and variability. The new SCOWLP classification may be of great utility for reconstruction of protein complexes, understanding protein networks and ligand design. SCOWLP will be updated with every SCOP release. The web application is available at http://www.scowlp.org.
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