Literature DB >> 29476832

Using Chou's general PseAAC to analyze the evolutionary relationship of receptor associated proteins (RAP) with various folding patterns of protein domains.

S Muthu Krishnan1.   

Abstract

The receptor-associated protein (RAP) is an inhibitor of endocytic receptors that belong to the lipoprotein receptor gene family. In this study, a computational approach was tried to find the evolutionarily related fold of the RAP proteins. Through the structural and sequence-based analysis, found various protein folds that are very close to the RAP folds. Remote homolog datasets were used potentially to develop a different support vector machine (SVM) methods to recognize the homologous RAP fold. This study helps in understanding the relationship of RAP homologs folds based on the structure, function and evolutionary history.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Molecular evolution; PSSM; Rap protein fold; Support vector machine

Mesh:

Substances:

Year:  2018        PMID: 29476832     DOI: 10.1016/j.jtbi.2018.02.008

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  7 in total

1.  iPhosY-PseAAC: identify phosphotyrosine sites by incorporating sequence statistical moments into PseAAC.

Authors:  Yaser Daanial Khan; Nouman Rasool; Waqar Hussain; Sher Afzal Khan; Kuo-Chen Chou
Journal:  Mol Biol Rep       Date:  2018-10-11       Impact factor: 2.316

2.  Predicting membrane proteins and their types by extracting various sequence features into Chou's general PseAAC.

Authors:  Ahmad Hassan Butt; Nouman Rasool; Yaser Daanial Khan
Journal:  Mol Biol Rep       Date:  2018-09-20       Impact factor: 2.316

3.  Evolutionary insights into the active-site structures of the metallo-β-lactamase superfamily from a classification study with support vector machine.

Authors:  Lili Wang; Ling Yang; Yu-Lan Feng; Hao Zhang
Journal:  J Biol Inorg Chem       Date:  2020-09-18       Impact factor: 3.358

Review 4.  Some illuminating remarks on molecular genetics and genomics as well as drug development.

Authors:  Kuo-Chen Chou
Journal:  Mol Genet Genomics       Date:  2020-01-01       Impact factor: 3.291

5.  PScL-HDeep: image-based prediction of protein subcellular location in human tissue using ensemble learning of handcrafted and deep learned features with two-layer feature selection.

Authors:  Matee Ullah; Ke Han; Fazal Hadi; Jian Xu; Jiangning Song; Dong-Jun Yu
Journal:  Brief Bioinform       Date:  2021-11-05       Impact factor: 13.994

6.  iRNA-3typeA: Identifying Three Types of Modification at RNA's Adenosine Sites.

Authors:  Wei Chen; Pengmian Feng; Hui Yang; Hui Ding; Hao Lin; Kuo-Chen Chou
Journal:  Mol Ther Nucleic Acids       Date:  2018-03-30       Impact factor: 8.886

7.  iMethylK_pseAAC: Improving Accuracy of Lysine Methylation Sites Identification by Incorporating Statistical Moments and Position Relative Features into General PseAAC via Chou's 5-steps Rule.

Authors:  Sarah Ilyas; Waqar Hussain; Adeel Ashraf; Yaser Daanial Khan; Sher Afzal Khan; Kuo-Chen Chou
Journal:  Curr Genomics       Date:  2019-05       Impact factor: 2.236

  7 in total

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