HydPred: a novel method for the identification of protein hydroxylation sites that reveals new insights into human inherited disease. Issue 2 (14th December 2015)
- Record Type:
- Journal Article
- Title:
- HydPred: a novel method for the identification of protein hydroxylation sites that reveals new insights into human inherited disease. Issue 2 (14th December 2015)
- Main Title:
- HydPred: a novel method for the identification of protein hydroxylation sites that reveals new insights into human inherited disease
- Authors:
- Li, Shuyan
Lu, Jun
Li, Jiazhong
Chen, Ximing
Yao, Xiaojun
Xi, Lili - Abstract:
- Abstract : HydPred was presented as the most reliable tool up to now for the identification of protein hydroxylation sites with a user-friendly web server at Web:http://lishuyan.lzu.edu.cn/hydpred/ . Abstract : The disruption of protein hydroxylation is highly associated with several serious diseases and consequently the identification of protein hydroxylation sites has attracted significant attention recently. Here, we report the development of an improved method, called HydPred, to identify protein hydroxylation sites (hydroxyproline and hydroxylysine) based on the synthetic minority over-sampling technique (SMOTE), the random forest (RF) algorithm and four blocks of newly composed features that are derived from the protein primary sequence. The HydPred method achieved the best prediction performance reported until now with Matthew's correlation coefficient values of 0.770 and 0.857 for hydroxyproline and hydroxylysine, respectively, according to jack-knife cross-validation. This represents an improvement of 8% for hydroxyproline and 19% for hydroxylysine compared to the best results of available predictors. The prediction performance of HydPred for the external validation of hydroxyproline and hydroxylysine was also improved compared with other published methods. We subsequently applied HydPred to study the association of disruption of hydroxylation sites with human inherited disease. The analyses suggested that the loss of hydroxylation sites is more likely to causeAbstract : HydPred was presented as the most reliable tool up to now for the identification of protein hydroxylation sites with a user-friendly web server at Web:http://lishuyan.lzu.edu.cn/hydpred/ . Abstract : The disruption of protein hydroxylation is highly associated with several serious diseases and consequently the identification of protein hydroxylation sites has attracted significant attention recently. Here, we report the development of an improved method, called HydPred, to identify protein hydroxylation sites (hydroxyproline and hydroxylysine) based on the synthetic minority over-sampling technique (SMOTE), the random forest (RF) algorithm and four blocks of newly composed features that are derived from the protein primary sequence. The HydPred method achieved the best prediction performance reported until now with Matthew's correlation coefficient values of 0.770 and 0.857 for hydroxyproline and hydroxylysine, respectively, according to jack-knife cross-validation. This represents an improvement of 8% for hydroxyproline and 19% for hydroxylysine compared to the best results of available predictors. The prediction performance of HydPred for the external validation of hydroxyproline and hydroxylysine was also improved compared with other published methods. We subsequently applied HydPred to study the association of disruption of hydroxylation sites with human inherited disease. The analyses suggested that the loss of hydroxylation sites is more likely to cause disease instead of the gain of hydroxylation sites and 52 different human inherited diseases were found to be highly associated with the loss of hydroxylation sites. Therefore, HydPred represents a new strategy to discover the molecular basis of pathogenesis associated with abnormal hydroxylation. HydPred is now available online as a user-friendly web server at Web:http://lishuyan.lzu.edu.cn/hydpred/ . … (more)
- Is Part Of:
- Molecular bioSystems. Volume 12:Issue 2(2016:Feb.)
- Journal:
- Molecular bioSystems
- Issue:
- Volume 12:Issue 2(2016:Feb.)
- Issue Display:
- Volume 12, Issue 2 (2016)
- Year:
- 2016
- Volume:
- 12
- Issue:
- 2
- Issue Sort Value:
- 2016-0012-0002-0000
- Page Start:
- 490
- Page End:
- 498
- Publication Date:
- 2015-12-14
- Subjects:
- Molecular biology -- Periodicals
Biochemistry -- Periodicals
571.7405 - Journal URLs:
- http://www.rsc.org/Publishing/Journals/mb/index.asp ↗
http://www.rsc.org/ ↗ - DOI:
- 10.1039/c5mb00681c ↗
- Languages:
- English
- ISSNs:
- 1742-206X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5900.798350
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 1034.xml