Literature DB >> 20383542

Prediction of catalytic residues based on an overlapping amino acid classification.

Yongchao Dou1, Xiaoqi Zheng, Jialiang Yang, Jun Wang.   

Abstract

Protein sequence conservation is a powerful and widely used indicator for predicting catalytic residues from enzyme sequences. In order to incorporate amino acid similarity into conservation measures, one attempt is to group amino acids into disjoint sets. In this paper, based on the overlapping amino acids classification proposed by Taylor, we define the relative entropy of Venn diagram (RVD) and RVD2. In large-scale testing, we demonstrate that RVD and RVD2 perform better than many existing conservation measures in identifying catalytic residues, especially than the commonly used relative entropy (RE) and Jensen-Shannon divergence (JSD). To further improve RVD and RVD2, two new conservation measures are obtained by combining them with the classical JSD. Experimental results suggest that these combination measures have excellent performances in identifying catalytic residues.

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Year:  2010        PMID: 20383542     DOI: 10.1007/s00726-010-0587-2

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


  6 in total

1.  Sequence conservation in the prediction of catalytic sites.

Authors:  Yongchao Dou; Xingbo Geng; Hongyun Gao; Jialiang Yang; Xiaoqi Zheng; Jun Wang
Journal:  Protein J       Date:  2011-04       Impact factor: 2.371

2.  iCataly-PseAAC: Identification of Enzymes Catalytic Sites Using Sequence Evolution Information with Grey Model GM (2,1).

Authors:  Xuan Xiao; Meng-Juan Hui; Zi Liu; Wang-Ren Qiu
Journal:  J Membr Biol       Date:  2015-06-16       Impact factor: 1.843

3.  RF-Hydroxysite: a random forest based predictor for hydroxylation sites.

Authors:  Hamid D Ismail; Robert H Newman; Dukka B Kc
Journal:  Mol Biosyst       Date:  2016-07-19

4.  Identification of catalytic residues using a novel feature that integrates the microenvironment and geometrical location properties of residues.

Authors:  Lei Han; Yong-Jun Zhang; Jiangning Song; Ming S Liu; Ziding Zhang
Journal:  PLoS One       Date:  2012-07-19       Impact factor: 3.240

5.  L1pred: a sequence-based prediction tool for catalytic residues in enzymes with the L1-logreg classifier.

Authors:  Yongchao Dou; Jun Wang; Jialiang Yang; Chi Zhang
Journal:  PLoS One       Date:  2012-04-27       Impact factor: 3.240

6.  RF-Phos: A Novel General Phosphorylation Site Prediction Tool Based on Random Forest.

Authors:  Hamid D Ismail; Ahoi Jones; Jung H Kim; Robert H Newman; Dukka B Kc
Journal:  Biomed Res Int       Date:  2016-03-15       Impact factor: 3.411

  6 in total

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