Literature DB >> 30260564

Identification of Moonlighting Proteins in Genomes Using Text Mining Techniques.

Aashish Jain1,2, Hareesh Gali2, Daisuke Kihara1,2,3.   

Abstract

Moonlighting proteins is an emerging concept for considering protein functions, which indicate proteins with two or more independent and distinct functions. An increasing number of moonlighting proteins have been reported in the past years; however, a systematic study of the topic has been hindered because the secondary functions of proteins are usually found serendipitously by experiments. Toward systematic identification and study of moonlighting proteins, computational methods for identifying moonlighting proteins from several different information sources, database entries, literature, and large-scale omics data have been developed. In this study, an overview for finding moonlighting proteins is discussed. Then, the literature-mining method, DextMP, is applied to find new moonlighting proteins in three genomes, Arabidopsis thaliana, Caenorhabditis elegans, and Drosophila melanogaster. Potential moonlighting proteins identified by DextMP are further examined by a two-step manual literature checking procedure, which finally yielded 13 new moonlighting proteins. Identified moonlighting proteins are categorized into two classes based on the clarity of the distinctness of two functions of the proteins. A few cases of the identified moonlighting proteins are described in detail. Further direction for improving the DextMP algorithm is also discussed.
© 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  bifunctional proteins; functional genomics; moonlighting proteins; protein function annotation; text mining

Mesh:

Year:  2018        PMID: 30260564      PMCID: PMC6404977          DOI: 10.1002/pmic.201800083

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   3.984


  62 in total

1.  Do current sequence analysis algorithms disclose multifunctional (moonlighting) proteins?

Authors:  Antonio Gómez; Nuria Domedel; Juan Cedano; Jaume Piñol; Enrique Querol
Journal:  Bioinformatics       Date:  2003-05-01       Impact factor: 6.937

2.  Caenorhabditis elegans EFA-6 limits microtubule growth at the cell cortex.

Authors:  Sean M O'Rourke; Sara N Christensen; Bruce Bowerman
Journal:  Nat Cell Biol       Date:  2010-11-14       Impact factor: 28.824

Review 3.  Structural disorder throws new light on moonlighting.

Authors:  Peter Tompa; Csilla Szász; László Buday
Journal:  Trends Biochem Sci       Date:  2005-09       Impact factor: 13.807

4.  Using PFP and ESG Protein Function Prediction Web Servers.

Authors:  Qing Wei; Joshua McGraw; Ishita Khan; Daisuke Kihara
Journal:  Methods Mol Biol       Date:  2017

Review 5.  Regulation of Arf activation: the Sec7 family of guanine nucleotide exchange factors.

Authors:  James E Casanova
Journal:  Traffic       Date:  2007-09-10       Impact factor: 6.215

6.  Evaluation of function predictions by PFP, ESG,and PSI-BLAST for moonlighting proteins.

Authors:  Ishita Khan; Meghana Chitale; Catherine Rayon; Daisuke Kihara
Journal:  BMC Proc       Date:  2012-11-13

7.  Genome-Wide Detection and Analysis of Multifunctional Genes.

Authors:  Yuri Pritykin; Dario Ghersi; Mona Singh
Journal:  PLoS Comput Biol       Date:  2015-10-05       Impact factor: 4.475

8.  Why study moonlighting proteins?

Authors:  Constance J Jeffery
Journal:  Front Genet       Date:  2015-06-19       Impact factor: 4.599

9.  MultitaskProtDB-II: an update of a database of multitasking/moonlighting proteins.

Authors:  Luís Franco-Serrano; Sergio Hernández; Alejandra Calvo; María A Severi; Gabriela Ferragut; JosepAntoni Pérez-Pons; Jaume Piñol; Òscar Pich; Ángel Mozo-Villarias; Isaac Amela; Enrique Querol; Juan Cedano
Journal:  Nucleic Acids Res       Date:  2018-01-04       Impact factor: 16.971

10.  The Arabidopsis At1g30680 gene encodes a homologue to the phage T7 gp4 protein that has both DNA primase and DNA helicase activities.

Authors:  Joann Diray-Arce; Bin Liu; John D Cupp; Travis Hunt; Brent L Nielsen
Journal:  BMC Plant Biol       Date:  2013-03-04       Impact factor: 4.215

View more
  3 in total

1.  Moonlighting protein prediction using physico-chemical and evolutional properties via machine learning methods.

Authors:  Farshid Shirafkan; Sajjad Gharaghani; Karim Rahimian; Reza Hasan Sajedi; Javad Zahiri
Journal:  BMC Bioinformatics       Date:  2021-05-24       Impact factor: 3.169

2.  The Balancing Act of Intrinsically Disordered Proteins: Enabling Functional Diversity while Minimizing Promiscuity.

Authors:  Mauricio Macossay-Castillo; Giulio Marvelli; Mainak Guharoy; Aashish Jain; Daisuke Kihara; Peter Tompa; Shoshana J Wodak
Journal:  J Mol Biol       Date:  2019-03-13       Impact factor: 5.469

3.  IdentPMP: identification of moonlighting proteins in plants using sequence-based learning models.

Authors:  Xinyi Liu; Yueyue Shen; Youhua Zhang; Fei Liu; Zhiyu Ma; Zhenyu Yue; Yi Yue
Journal:  PeerJ       Date:  2021-08-06       Impact factor: 2.984

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.