Literature DB >> 20980272

Identification of subfamily-specific sites based on active sites modeling and clustering.

Raquel C de Melo-Minardi1, Karine Bastard, François Artiguenave.   

Abstract

MOTIVATION: Current computational approaches to function prediction are mostly based on protein sequence classification and transfer of annotation from known proteins to their closest homologous sequences relying on the orthology concept of function conservation. This approach suffers a major weakness: annotation reliability depends on global sequence similarity to known proteins and is poorly efficient for enzyme superfamilies that catalyze different reactions. Structural biology offers a different strategy to overcome the problem of annotation by adding information about protein 3D structures. This information can be used to identify amino acids located in active sites, focusing on detection of functional polymorphisms residues in an enzyme superfamily. Structural genomics programs are providing more and more novel protein structures at a high-throughput rate. However, there is still a huge gap between the number of sequences and available structures. Computational methods, such as homology modeling provides reliable approaches to bridge this gap and could be a new precise tool to annotate protein functions.
RESULTS: Here, we present Active Sites Modeling and Clustering (ASMC) method, a novel unsupervised method to classify sequences using structural information of protein pockets. ASMC combines homology modeling of family members, structural alignment of modeled active sites and a subsequent hierarchical conceptual classification. Comparison of profiles obtained from computed clusters allows the identification of residues correlated to subfamily function divergence, called specificity determining positions. ASMC method has been validated on a benchmark of 42 Pfam families for which previous resolved holo-structures were available. ASMC was also applied to several families containing known protein structures and comprehensive functional annotations. We will discuss how ASMC improves annotation and understanding of protein families functions by giving some specific illustrative examples on nucleotidyl cyclases, protein kinases and serine proteases. AVAILABILITY: http://www.genoscope.fr/ASMC/.

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Year:  2010        PMID: 20980272     DOI: 10.1093/bioinformatics/btq595

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  15 in total

1.  Revealing the hidden functional diversity of an enzyme family.

Authors:  Karine Bastard; Adam Alexander Thil Smith; Carine Vergne-Vaxelaire; Alain Perret; Anne Zaparucha; Raquel De Melo-Minardi; Aline Mariage; Magali Boutard; Adrien Debard; Christophe Lechaplais; Christine Pelle; Virginie Pellouin; Nadia Perchat; Jean-Louis Petit; Annett Kreimeyer; Claudine Medigue; Jean Weissenbach; François Artiguenave; Véronique De Berardinis; David Vallenet; Marcel Salanoubat
Journal:  Nat Chem Biol       Date:  2013-11-17       Impact factor: 15.040

2.  Metabolism: digging up enzyme functions.

Authors:  Matthew J Wargo
Journal:  Nat Chem Biol       Date:  2013-11-17       Impact factor: 15.040

3.  Parallel evolution of non-homologous isofunctional enzymes in methionine biosynthesis.

Authors:  Karine Bastard; Alain Perret; Aline Mariage; Thomas Bessonnet; Agnès Pinet-Turpault; Jean-Louis Petit; Ekaterina Darii; Pascal Bazire; Carine Vergne-Vaxelaire; Clémence Brewee; Adrien Debard; Virginie Pellouin; Marielle Besnard-Gonnet; François Artiguenave; Claudine Médigue; David Vallenet; Antoine Danchin; Anne Zaparucha; Jean Weissenbach; Marcel Salanoubat; Véronique de Berardinis
Journal:  Nat Chem Biol       Date:  2017-06-05       Impact factor: 15.040

4.  Multi-omics data integration analysis identifies the spliceosome as a key regulator of DNA double-strand break repair.

Authors:  Dana Sherill-Rofe; Oded Raban; Steven Findlay; Dolev Rahat; Irene Unterman; Arash Samiei; Amber Yasmeen; Zafir Kaiser; Hellen Kuasne; Morag Park; William D Foulkes; Idit Bloch; Aviad Zick; Walter H Gotlieb; Yuval Tabach; Alexandre Orthwein
Journal:  NAR Cancer       Date:  2022-04-08

5.  A novel acyl-CoA beta-transaminase characterized from a metagenome.

Authors:  Alain Perret; Christophe Lechaplais; Sabine Tricot; Nadia Perchat; Carine Vergne; Christine Pellé; Karine Bastard; Annett Kreimeyer; David Vallenet; Anne Zaparucha; Jean Weissenbach; Marcel Salanoubat
Journal:  PLoS One       Date:  2011-08-03       Impact factor: 3.240

6.  Structure-guided selection of specificity determining positions in the human Kinome.

Authors:  Mark Moll; Paul W Finn; Lydia E Kavraki
Journal:  BMC Genomics       Date:  2016-08-18       Impact factor: 3.969

7.  An approach to functionally relevant clustering of the protein universe: Active site profile-based clustering of protein structures and sequences.

Authors:  Stacy T Knutson; Brian M Westwood; Janelle B Leuthaeuser; Brandon E Turner; Don Nguyendac; Gabrielle Shea; Kiran Kumar; Julia D Hayden; Angela F Harper; Shoshana D Brown; John H Morris; Thomas E Ferrin; Patricia C Babbitt; Jacquelyn S Fetrow
Journal:  Protein Sci       Date:  2017-03-08       Impact factor: 6.725

8.  Ligand-binding specificity and promiscuity of the main lignocellulolytic enzyme families as revealed by active-site architecture analysis.

Authors:  Li Tian; Shijia Liu; Shuai Wang; Lushan Wang
Journal:  Sci Rep       Date:  2016-03-24       Impact factor: 4.379

9.  ALVIS: interactive non-aggregative visualization and explorative analysis of multiple sequence alignments.

Authors:  Roland F Schwarz; Asif U Tamuri; Marek Kultys; James King; James Godwin; Ana M Florescu; Jörg Schultz; Nick Goldman
Journal:  Nucleic Acids Res       Date:  2016-01-26       Impact factor: 16.971

10.  Isofunctional Protein Subfamily Detection Using Data Integration and Spectral Clustering.

Authors:  Elisa Boari de Lima; Wagner Meira; Raquel Cardoso de Melo-Minardi
Journal:  PLoS Comput Biol       Date:  2016-06-27       Impact factor: 4.475

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