title: Predicting Citrullination Sites in Protein Sequences Using mRMR Method and Random Forest Algorithm.
abstract: BACKGROUND
  As one of essential post-translational modifications (PTMs), the citrullination or deimination on an arginine residue would change the molecular weight and electrostatic charge of its side-chain. And it has been found that the citrullination in protein sequences was catalyzed by a type of Ca2+-dependent enzyme family called peptidylarginine deiminase (PAD), which include five isotypes: PAD1, 2, 3, 4/5, and 6. Citrullinated proteins participate in many biological processes, e.g. the citrullination of myelin basic protein (MBP) assists the early development of central nervous system. However, abnormal modifications on citrullinated proteins would also lead to some severe human diseases including multiple sclerosis and rheumatoid arthritis.
  
  
  OBJECTIVE
  Therefore, it is necessary and important to identify the citrullination sites in protein sequences. The information about the location of citrulliantion sites in protein sequences will be useful to investigate the molecular functions and disease mechanisms related to citrullinated proteins.
  
  
  METHODS
  In this study, we investigated the peptide segments that contain the citrullination sites in the centers, which were encoded into numeric digits from four aspects. Thus, we yielded a training set with 116 positive samples and 232 negative samples. Then, a reliable feature selection technique, called maximum-relevance-minimum-redundancy (mRMR), was applied to analyze these features, and four algorithms, including random forest (RF), Dagging, nearest neighbor algorithm (NNA), and support vector machine (SVM), together with the incremental feature selection (IFS) method were adopted to extract important features.
  
  
  RESULTS
  Finally an optimal classifier derived from RF algorithm was constructed to predict citrullination sites. 44 most prominent features were comprehensively analyzed and their biological characteristics in citrullination catalysis were also revealed.
  
  
  CONCLUSIONS
  We believed that the biological features obtained in this pioneering work would provide some useful insights into the formation and function of citrullination and the optimal classifier could be a useful tool to identify citrullination sites in protein sequences.
authors.affiliation: School of Life Sciences, Shanghai University, Shanghai 200444, China.
authors.forename: Qing
authors.initials: Q
authors.lastname: Zhang
authors.affiliation: School of Life Sciences, Shanghai University, Shanghai 200444, China.
authors.forename: Xijun
authors.initials: X
authors.lastname: Sun
authors.affiliation: Department of Computer Science, Guangdong AIB Polytechnic, Guangdong, China.
authors.forename: Kaiyan
authors.initials: K
authors.lastname: Feng
authors.affiliation: School of Life Sciences, Shanghai University, Shanghai 200444, China.
authors.forename: ShaoPeng
authors.initials: S
authors.lastname: Wang
authors.affiliation: Institute of Health Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
authors.forename: Yu-Hang
authors.initials: YH
authors.lastname: Zhang
authors.affiliation: School of Life Sciences, Shanghai University, Shanghai 200444, China.
authors.forename: SiBao
authors.initials: S
authors.lastname: Wang
authors.affiliation: Department of Radiology, Columbia University Medical Center, New York, NY, 10032, China.
authors.forename: Lin
authors.initials: L
authors.lastname: Lu
authors.affiliation: School of Life Sciences, Shanghai University, Shanghai 200444, China.
authors.forename: Yu-Dong
authors.initials: YD
authors.lastname: Cai
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D001120:Arginine / Q000378:metabolism*; D001665:Binding Sites; D002956:Citrulline / Q000378:metabolism*; D006801:Humans; D006867:Hydrolases / Q000378:metabolism; D011499:Protein Processing, Post-Translational; D000076342:Protein-Arginine Deiminases; D060388:Support Vector Machine
chemical_list: D002956:Citrulline; D001120:Arginine; D006867:Hydrolases; D000076342:Protein-Arginine Deiminases
keywords: Post-translational modification; citrullination site; maximum relevance minimum redundancy; random forest