Literature DB >> 28521678

iPGK-PseAAC: Identify Lysine Phosphoglycerylation Sites in Proteins by Incorporating Four Different Tiers of Amino Acid Pairwise Coupling Information into the General PseAAC.

Li-Ming Liu1, Yan Xu2, Kuo-Chen Chou3.   

Abstract

BACKGROUND: Occurring at Lys residues, the PGK (lysine phosphoglycerylation) is a special kind of post-translational modification (PTM). It may invert the charge potential of the modified residue and change the protein structures and functions, causing various diseases in liver, brain, and kidney.
OBJECTIVE: From the angles of both basic research and drug development, we are facing a critical challenging problem: for an uncharacterized protein sequence containing many Lys residues, which ones can be of phosphoglycerylation, and which ones cannot?
METHOD: To address this problem, we have developed a predictor called iPGK-PseAAC by incorporating into the general PseAAC (pseudo amino acid composition) with four different tiers of amino acid pairwise coupling information, where tiers 1, 2, 3, and 4 refer to the amino acid pairwise couplings between all the 1st, 2nd, 3rd, and 4th most contiguous residues along a protein segment, respectively.
RESULTS: Rigorous cross-validations indicated that the proposed predictor remarkably outperformed its existing counterparts.
CONCLUSION: The proposed predictor iPGK-PseAAC will become a very useful bioinformatics tool for medicinal chemistry. For the convenience of most experimental scientists, a user-friendly webserver for iGPK-PseAAC has been established at http://app.aporc.org/iPGK-PseAAC/, by which users can easily obtain their desired results without the need to go through the complicated mathematical equations involved. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Entities:  

Keywords:  Amino acid pairwise coupling; PseAAC; SVM; lyszzm321990residues; phosphoglycerylation; post-translational modification (PTM)

Mesh:

Substances:

Year:  2017        PMID: 28521678     DOI: 10.2174/1573406413666170515120507

Source DB:  PubMed          Journal:  Med Chem        ISSN: 1573-4064            Impact factor:   2.745


  26 in total

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6.  Assessing the Performances of Protein Function Prediction Algorithms from the Perspectives of Identification Accuracy and False Discovery Rate.

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Journal:  Oncotarget       Date:  2017-06-20

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9.  iDNAProt-ES: Identification of DNA-binding Proteins Using Evolutionary and Structural Features.

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10.  Prediction of HIV-1 and HIV-2 proteins by using Chou's pseudo amino acid compositions and different classifiers.

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Journal:  Sci Rep       Date:  2018-02-05       Impact factor: 4.379

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