EProS--a Database and Toolbox for Investigating Protein Sequence-structure-function Relationships Through Energy Profiles

Overview

Journal Nucleic Acids Res

Publisher Oxford University Press

Specialty Biochemistry

Date 2012 Nov 20

PMID 23161695

Citations 3

Authors

Florian Heinke

Stefan Schildbach

Daniel Stockmann

Dirk Labudde

Affiliations

Soon will be listed here.

Abstract

Gaining information about structural and functional features of newly identified proteins is often a difficult task. This information is crucial for understanding sequence-structure-function relationships of target proteins and, thus, essential in comprehending the mechanisms and dynamics of the molecular systems of interest. Using protein energy profiles is a novel approach that can contribute in addressing such problems. An energy profile corresponds to the sequence of energy values that are derived from a coarse-grained energy model. Energy profiles can be computed from protein structures or predicted from sequences. As shown, correspondences and dissimilarities in energy profiles can be applied for investigations of protein mechanics and dynamics. We developed eProS (energy profile suite, freely available at http://bioservices.hs-mittweida.de/Epros/), a database that provides ∼76 000 pre-calculated energy profiles as well as a toolbox for addressing numerous problems of structure biology. Energy profiles can be browsed, visualized, calculated from an uploaded structure or predicted from sequence. Furthermore, it is possible to align energy profiles of interest or compare them with all entries in the eProS database to identify significantly similar energy profiles and, thus, possibly relevant structural and functional relationships. Additionally, annotations and cross-links from numerous sources provide a broad view of potential biological correspondences.

Citing Articles

Information theoretic measures for quantifying sequence-ensemble relationships of intrinsically disordered proteins.

Cohan M, Ruff K, Pappu R Protein Eng Des Sel. 2019; 32(4):191-202.

PMID: 31375817 PMC: 7462041. DOI: 10.1093/protein/gzz014.

Application of an interpretable classification model on Early Folding Residues during protein folding.

Bittrich S, Kaden M, Leberecht C, Kaiser F, Villmann T, Labudde D BioData Min. 2019; 12:1.

PMID: 30627219 PMC: 6321665. DOI: 10.1186/s13040-018-0188-2.

Characterizing the relation of functional and Early Folding Residues in protein structures using the example of aminoacyl-tRNA synthetases.

Bittrich S, Schroeder M, Labudde D PLoS One. 2018; 13(10):e0206369.

PMID: 30376559 PMC: 6207335. DOI: 10.1371/journal.pone.0206369.

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