title: Structural position correlation analysis (SPCA) for protein family.
abstract: BACKGROUND
  The proteins in a family, which perform the similar biological functions, may have very different amino acid composition, but they must share the similar 3D structures, and keep a stable central region. In the conservative structure region similar biological functions are performed by two or three catalytic residues with the collaboration of several functional residues at key positions. Communication signals are conducted in a position network, adjusting the biological functions in the protein family.
  
  
  METHODS
  A computational approach, namely structural position correlation analysis (SPCA), is developed to analyze the correlation relationship between structural segments (or positions). The basic hypothesis of SPCA is that in a protein family the structural conservation is more important than the sequence conservation, and the local structural changes may contain information of biology functional evolution. A standard protein P(0) is defined in a protein family, which consists of the most-frequent amino acids and takes the average structure of the protein family. The foundational variables of SPCA is the structural position displacements between the standard protein P(0) and individual proteins P(i) of the family. The structural positions are organized as segments, which are the stable units in structural displacements of the protein family. The biological function differences of protein members are determined by the position structural displacements of individual protein P(i) to the standard protein P(0). Correlation analysis is used to analyze the communication network among segments.
  
  
  CONCLUSIONS
  The structural position correlation analysis (SPCA) is able to find the correlation relationship among the structural segments (or positions) in a protein family, which cannot be detected by the amino acid sequence and frequency-based methods. The functional communication network among the structural segments (or positions) in protein family, revealed by SPCA approach, well illustrate the distantly allosteric interactions, and contains valuable information for protein engineering study.
authors.affiliation: State Key Laboratory of Non-food Biomass Energy and Enzyme Technology, National Engineering Research Center for Non-food Biorefinery, Guangxi Academy of Sciences, Nanning, Guangxi, China. qishi_du@yahoo.com.cn
authors.forename: Qi-Shi
authors.initials: QS
authors.lastname: Du
authors.forename: Jian-Zong
authors.initials: JZ
authors.lastname: Meng
authors.forename: Cheng-Hua
authors.initials: CH
authors.lastname: Wang
authors.forename: Si-Yu
authors.initials: SY
authors.lastname: Long
authors.forename: Ri-Bo
authors.initials: RB
authors.lastname: Huang
mesh_terms: D000595:Amino Acid Sequence; D000596:Amino Acids / Q000737:chemistry; D000818:Animals; D020134:Catalytic Domain; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D017124:Conserved Sequence; D030562:Databases, Protein; D006801:Humans; D008958:Models, Molecular; D008969:Molecular Sequence Data; D016296:Mutagenesis; D011487:Protein Conformation; D017434:Protein Structure, Tertiary; D011506:Proteins / Q000737:chemistry*; D017386:Sequence Homology, Amino Acid
chemical_list: D000596:Amino Acids; D011506:Proteins