Document Details
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Document Type |
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Article In Journal |
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Document Title |
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iCar-PseCp: identify carbonylation sites in proteins by Monte Carlo sampling and incorporating sequence coupled effects into general PseAAC iCar-PseCp: identify carbonylation sites in proteins by Monte Carlo sampling and incorporating sequence coupled effects into general PseAAC |
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Document Language |
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English |
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Abstract |
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Carbonylation is a posttranslational modification (PTM or PTLM), where a
carbonyl group is added to lysine (K), proline (P), arginine (R), and threonine (T)
residue of a protein molecule. Carbonylation plays an important role in orchestrating
various biological processes but it is also associated with many diseases such as
diabetes, chronic lung disease, Parkinson’s disease, Alzheimer’s disease, chronic
renal failure, and sepsis. Therefore, from the angles of both basic research and drug
development, we are facing a challenging problem: for an uncharacterized protein
sequence containing many residues of K, P, R, or T, which ones can be carbonylated,
and which ones cannot? To address this problem, we have developed a predictor
called iCar-PseCp by incorporating the sequence-coupled information into the general
pseudo amino acid composition, and balancing out skewed training dataset by Monte
Carlo sampling to expand positive subset. Rigorous target cross-validations on a same
set of carbonylation-known proteins indicated that the new predictor remarkably
outperformed its existing counterparts. For the convenience of most experimental
scientists, a user-friendly web-server for iCar-PseCp has been established at http://
www.jci-bioinfo.cn/iCar-PseCp, by which users can easily obtain their desired results
without the need to go through the complicated mathematical equations involved.
It has not escaped our notice that the formulation and approach presented here can
also be used to analyze many other problems in computational proteomics. |
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ISSN |
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2715-3555 |
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Journal Name |
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Oncotarget |
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Volume |
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7 |
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Issue Number |
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23 |
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Publishing Year |
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1437 AH
2016 AD |
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Article Type |
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Article |
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Added Date |
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Wednesday, July 12, 2017 |
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Researchers
| Jianhua Jia | Jia, Jianhua | Researcher | Doctorate | |
| Xuan Xiao | Xiao, Xuan | Researcher | Doctorate | |
| Zi Liu | Liu, Zi | Researcher | Doctorate | |
| Bingxiang Liu | Liu, Bingxiang | Researcher | Doctorate | |
| Kuo-Chen Chou | Chou, Kuo-Chen | Researcher | Doctorate | |
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