Literature DB >> 24623120

The construction of an amino acid network for understanding protein structure and function.

Wenying Yan1, Jianhong Zhou, Maomin Sun, Jiajia Chen, Guang Hu, Bairong Shen.   

Abstract

Amino acid networks (AANs) are undirected networks consisting of amino acid residues and their interactions in three-dimensional protein structures. The analysis of AANs provides novel insight into protein science, and several common amino acid network properties have revealed diverse classes of proteins. In this review, we first summarize methods for the construction and characterization of AANs. We then compare software tools for the construction and analysis of AANs. Finally, we review the application of AANs for understanding protein structure and function, including the identification of functional residues, the prediction of protein folding, analyzing protein stability and protein-protein interactions, and for understanding communication within and between proteins.

Mesh:

Substances:

Year:  2014        PMID: 24623120     DOI: 10.1007/s00726-014-1710-6

Source DB:  PubMed          Journal:  Amino Acids        ISSN: 0939-4451            Impact factor:   3.520


  24 in total

1.  Network Connectivity, Centrality and Fragmentation in the Greek-Key Protein Topology.

Authors:  Zeinab Haratipour; Hind Aldabagh; Yaohang Li; Lesley H Greene
Journal:  Protein J       Date:  2019-10       Impact factor: 2.371

2.  The PyInteraph Workflow for the Study of Interaction Networks From Protein Structural Ensembles.

Authors:  Matteo Lambrughi; Valentina Sora; Matteo Tiberti
Journal:  Methods Mol Biol       Date:  2021

Review 3.  Building Bridges Between Structural and Network-Based Systems Biology.

Authors:  Christos T Chasapis
Journal:  Mol Biotechnol       Date:  2019-03       Impact factor: 2.695

4.  NAPS: Network Analysis of Protein Structures.

Authors:  Broto Chakrabarty; Nita Parekh
Journal:  Nucleic Acids Res       Date:  2016-05-05       Impact factor: 16.971

5.  Network theory reveals principles of spliceosome structure and dynamics.

Authors:  Harpreet Kaur; Clarisse van der Feltz; Yichen Sun; Aaron A Hoskins
Journal:  Structure       Date:  2021-09-29       Impact factor: 5.006

6.  Prediction of hemophilia A severity using a small-input machine-learning framework.

Authors:  Tiago J S Lopes; Ricardo Rios; Tatiane Nogueira; Rodrigo F Mello
Journal:  NPJ Syst Biol Appl       Date:  2021-05-25

7.  NPPD: A Protein-Protein Docking Scoring Function Based on Dyadic Differences in Networks of Hydrophobic and Hydrophilic Amino Acid Residues.

Authors:  Edward S C Shih; Ming-Jing Hwang
Journal:  Biology (Basel)       Date:  2015-03-24

8.  A hybrid method for identification of structural domains.

Authors:  Yongpan Hua; Min Zhu; Yuelong Wang; Zhaoyang Xie; Menglong Li
Journal:  Sci Rep       Date:  2014-12-15       Impact factor: 4.379

9.  Dynamic residue interaction network analysis of the oseltamivir binding site of N1 neuraminidase and its H274Y mutation site conferring drug resistance in influenza A virus.

Authors:  Mohini Yadav; Manabu Igarashi; Norifumi Yamamoto
Journal:  PeerJ       Date:  2021-06-02       Impact factor: 2.984

10.  Cheminformatic quantum mechanical enzyme model design: A catechol-O-methyltransferase case study.

Authors:  Thomas J Summers; Qianyi Cheng; Manuel A Palma; Diem-Trang Pham; Dudley K Kelso; Charles Edwin Webster; Nathan J DeYonker
Journal:  Biophys J       Date:  2021-08-04       Impact factor: 3.699

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