Literature DB >> 27289211

Novel function discovery through sequence and structural data mining.

Briallen Lobb1, Andrew C Doxey2.   

Abstract

Large-scale sequence and structural data is a goldmine of novel proteins, but how can this data be effectively mined for new functions? Here, we review protein function prediction methods and recent studies that apply these methods to discover new functionality. Core approaches include sequence-based homology detection, phylogenetic analysis, structural bioinformatics, and inference of functional associations using genomic context and related methods. With such a wide range of approaches, sequences may reveal new functionality regardless of their similarity to a characterized reference. Homologs of known function may be identified in unexpected species or associations. Detection of functional shifts in sequences may reveal new activities and specificities. New protein functions may also be predicted in uncharacterized sequences and structures. Finally, methods and data may be integrated and applied at increasingly large scales due to improved protein domain knowledge and structural coverage, which amplifies the ability to predict and discover novel protein functions.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Mesh:

Substances:

Year:  2016        PMID: 27289211     DOI: 10.1016/j.sbi.2016.05.017

Source DB:  PubMed          Journal:  Curr Opin Struct Biol        ISSN: 0959-440X            Impact factor:   6.809


  11 in total

1.  A Multi-Label Supervised Topic Model Conditioned on Arbitrary Features for Gene Function Prediction.

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Journal:  Genes (Basel)       Date:  2019-01-17       Impact factor: 4.096

2.  Exploring the dark foldable proteome by considering hydrophobic amino acids topology.

Authors:  Tristan Bitard-Feildel; Isabelle Callebaut
Journal:  Sci Rep       Date:  2017-01-30       Impact factor: 4.379

3.  An assessment of genome annotation coverage across the bacterial tree of life.

Authors:  Briallen Lobb; Benjamin Jean-Marie Tremblay; Gabriel Moreno-Hagelsieb; Andrew C Doxey
Journal:  Microb Genom       Date:  2020-03

4.  Characteristics of interactions at protein segments without non-local intramolecular contacts in the Protein Data Bank.

Authors:  Kota Kasahara; Shintaro Minami; Yasunori Aizawa
Journal:  PLoS One       Date:  2018-12-11       Impact factor: 3.240

5.  A most wanted list of conserved microbial protein families with no known domains.

Authors:  Stacia K Wyman; Aram Avila-Herrera; Stephen Nayfach; Katherine S Pollard
Journal:  PLoS One       Date:  2018-10-17       Impact factor: 3.240

Review 6.  Studies on Molecular Dynamics of Intrinsically Disordered Proteins and Their Fuzzy Complexes: A Mini-Review.

Authors:  Kota Kasahara; Hiroki Terazawa; Takuya Takahashi; Junichi Higo
Journal:  Comput Struct Biotechnol J       Date:  2019-06-13       Impact factor: 7.271

7.  Discovery of a proteolytic flagellin family in diverse bacterial phyla that assembles enzymatically active flagella.

Authors:  Ulrich Eckhard; Hina Bandukwala; Michael J Mansfield; Giada Marino; Jiujun Cheng; Iain Wallace; Todd Holyoak; Trevor C Charles; John Austin; Christopher M Overall; Andrew C Doxey
Journal:  Nat Commun       Date:  2017-09-12       Impact factor: 14.919

Review 8.  Tick Paralysis: Solving an Enigma.

Authors:  Ronel Pienaar; Albert W H Neitz; Ben J Mans
Journal:  Vet Sci       Date:  2018-05-14

9.  Structural bioinformatics predicts that the Retinitis Pigmentosa-28 protein of unknown function FAM161A is a homologue of the microtubule nucleation factor Tpx2.

Authors:  Timothy P Levine
Journal:  F1000Res       Date:  2020-08-27

Review 10.  Discovery and Biotechnological Exploitation of Glycoside-Phosphorylases.

Authors:  Ao Li; Mounir Benkoulouche; Simon Ladeveze; Julien Durand; Gianluca Cioci; Elisabeth Laville; Gabrielle Potocki-Veronese
Journal:  Int J Mol Sci       Date:  2022-03-11       Impact factor: 5.923

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