FunClust: a web server for the identification of structural motifs in a set of non-homologous protein structures

Discovering conserved three-dimensional (3D) patterns among protein structures may provide valuable insights into protein classification, functional annotations or the rational design of multi-target drugs. Thus, several computational tools have been developed to discover and compare protein 3D-patterns. However, most of them only consider previously known 3D-patterns such as orthosteric binding sites or structural motifs. This fact makes necessary the development of new methods for the identification of all possible 3D-patterns that exist in protein structures (allosteric sites, enzyme-cofactor interaction motifs, among others). In this work, we present 3D-PP, a new free access web server for the discovery and recognition all similar 3D amino acid patterns among a set of proteins structures (independent of their sequence similarity). This new tool does not require any previous structural knowledge about ligands, and all data are organized in a high-performance graph database. The input can be a text file with the PDB access codes or a zip file of PDB coordinates regardless of the origin of the structural data: X-ray crystallographic experiments or in silico homology modeling. The results are presented as lists of sequence patterns that can be further analyzed within the web page. We tested the accuracy and suitability of 3D-PP using two sets of proteins coming from the Protein Data Bank: (a) Zinc finger containing and (b) Serotonin target proteins. We also evaluated its usefulness for the discovering of new 3D-patterns, using a set of protein structures coming from in silico homology modeling methodologies, all of which are overexpressed in different types of cancer. Results indicate that 3D-PP is a reliable, flexible and friendly-user tool to identify conserved structural motifs, which could be relevant to improve the knowledge about protein function or classification. The web server can be freely utilized at https://appsbio.utalca.cl/3d-pp/.

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Recurrent Structural Motifs in Non-Homologous Protein Structures

International Journal of Molecular Sciences ◽

10.3390/ijms14047795 ◽

2013 ◽

Vol 14 (4) ◽

pp. 7795-7814 ◽

Cited By ~ 4

Author(s):

Maria Johansson ◽

Vincent Zoete ◽

Nicolas Guex

Keyword(s):

Protein Structures ◽

Structural Motifs ◽

Homologous Protein

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PALI: a database of alignments and phylogeny of homologous protein structures

Bioinformatics ◽

10.1093/bioinformatics/17.4.375 ◽

2001 ◽

Vol 17 (4) ◽

pp. 375-376 ◽

Cited By ~ 18

Author(s):

S. Sujatha ◽

S. Balaji ◽

N. Srinivasan

Keyword(s):

Protein Structures ◽

Homologous Protein

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The visualCMAT: A web-server to select and interpret correlated mutations/co-evolving residues in protein families

Journal of Bioinformatics and Computational Biology ◽

10.1142/s021972001840005x ◽

2018 ◽

Vol 16 (02) ◽

pp. 1840005 ◽

Cited By ~ 8

Author(s):

Dmitry Suplatov ◽

Yana Sharapova ◽

Daria Timonina ◽

Kirill Kopylov ◽

Vytas Švedas

Keyword(s):

Rational Design ◽

Visual Analysis ◽

Structural Information ◽

Protein Structures ◽

Web Server ◽

Physical Contact ◽

Protein Families ◽

Sequence Alignments ◽

Homologous Proteins ◽

Correlated Mutations

The visualCMAT web-server was designed to assist experimental research in the fields of protein/enzyme biochemistry, protein engineering, and drug discovery by providing an intuitive and easy-to-use interface to the analysis of correlated mutations/co-evolving residues. Sequence and structural information describing homologous proteins are used to predict correlated substitutions by the Mutual information-based CMAT approach, classify them into spatially close co-evolving pairs, which either form a direct physical contact or interact with the same ligand (e.g. a substrate or a crystallographic water molecule), and long-range correlations, annotate and rank binding sites on the protein surface by the presence of statistically significant co-evolving positions. The results of the visualCMAT are organized for a convenient visual analysis and can be downloaded to a local computer as a content-rich all-in-one PyMol session file with multiple layers of annotation corresponding to bioinformatic, statistical and structural analyses of the predicted co-evolution, or further studied online using the built-in interactive analysis tools. The online interactivity is implemented in HTML5 and therefore neither plugins nor Java are required. The visualCMAT web-server is integrated with the Mustguseal web-server capable of constructing large structure-guided sequence alignments of protein families and superfamilies using all available information about their structures and sequences in public databases. The visualCMAT web-server can be used to understand the relationship between structure and function in proteins, implemented at selecting hotspots and compensatory mutations for rational design and directed evolution experiments to produce novel enzymes with improved properties, and employed at studying the mechanism of selective ligand’s binding and allosteric communication between topologically independent sites in protein structures. The web-server is freely available at https://biokinet.belozersky.msu.ru/visualcmat and there are no login requirements.

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Homology modeling using SWISS-Model for Biochemistry I v1

10.17504/protocols.io.byntpven ◽

2021 ◽

Author(s):

Michael Friedman ◽

Chris Berndsen

Keyword(s):

Nucleic Acids ◽

Homology Modeling ◽

Homology Modelling ◽

Protein Structures ◽

Web Server ◽

James Madison

Protocol for homology modeling proteins for use in Biochemistry I at James Madison University. Protocol guides students to use the SWISS-Model web server (citations below). Citations for servers: Waterhouse, A., Bertoni, M., Bienert, S., Studer, G., Tauriello, G., Gumienny, R., Heer, F. T., de Beer, T. A. P., Rempfer, C., Bordoli, L., Lepore, R., and Schwede, T. (2018) SWISS-MODEL: homology modelling of protein structures and complexes. Nucleic Acids Res. 46, W296–W303.

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