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3D-PP: A tool for discovering conserved three-dimensional protein patterns

dc.contributor.authorValdés-Jiménez A.
dc.contributor.authorLarriba-Pey J.-L.
dc.contributor.authorNúñez-Vivanco G.
dc.contributor.authorReyes-Parada M.
dc.date.accessioned2020-09-02T22:29:52Z
dc.date.available2020-09-02T22:29:52Z
dc.date.issued2019
dc.identifier10.3390/ijms20133174
dc.identifier.citation20, 13, -
dc.identifier.issn16616596
dc.identifier.urihttps://hdl.handle.net/20.500.12728/6495
dc.descriptionDiscovering 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/. © 2019 by the authors. Licensee MDPI, Basel, Switzerland.
dc.language.isoen
dc.publisherMDPI AG
dc.subject3D-patterns
dc.subjectConserved patterns
dc.subjectSimilarity
dc.subjectzinc ion
dc.subjectalgorithm
dc.subjectamino acid sequence
dc.subjectArticle
dc.subjectbinding site
dc.subjectcomputer model
dc.subjectcryoelectron microscopy
dc.subjectcrystal structure
dc.subjectdrug design
dc.subjectenzyme active site
dc.subjecthydrogen bond
dc.subjectmolecular docking
dc.subjectprotein analysis
dc.subjectProtein Data Bank
dc.subjectprotein function
dc.subjectprotein structure
dc.subjectprotein synthesis
dc.subjectprotein unfolding
dc.subjectsequence alignment
dc.subjectsignal transduction
dc.subjectvirtual reality
dc.subjectX ray crystallography
dc.subjectallosteric site
dc.subjectanimal
dc.subjectconserved sequence
dc.subjecthuman
dc.subjectprocedures
dc.subjectprotein conformation
dc.subjectsequence analysis
dc.subjectsoftware
dc.subjectAllosteric Site
dc.subjectAmino Acid Sequence
dc.subjectAnimals
dc.subjectConserved Sequence
dc.subjectHumans
dc.subjectProtein Conformation
dc.subjectSequence Analysis, Protein
dc.subjectSoftware
dc.title3D-PP: A tool for discovering conserved three-dimensional protein patterns
dc.typeArticle


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