title: Identifying the molecular functions of electron transport proteins using radial basis function networks and biochemical properties.
abstract: The electron transport proteins have an important role in storing and transferring electrons in cellular respiration, which is the most proficient process through which cells gather energy from consumed food. According to the molecular functions, the electron transport chain components could be formed with five complexes with several different electron carriers and functions. Therefore, identifying the molecular functions in the electron transport chain is vital for helping biologists understand the electron transport chain process and energy production in cells. This work includes two phases for discriminating electron transport proteins from transport proteins and classifying categories of five complexes in electron transport proteins. In the first phase, the performances from PSSM with AAIndex feature set were successful in identifying electron transport proteins in transport proteins with achieved sensitivity of 73.2%, specificity of 94.1%, and accuracy of 91.3%, with MCC of 0.64 for independent data set. With the second phase, our method can approach a precise model for identifying of five complexes with different molecular functions in electron transport proteins. The PSSM with AAIndex properties in five complexes achieved MCC of 0.51, 0.47, 0.42, 0.74, and 1.00 for independent data set, respectively. We suggest that our study could be a power model for determining new proteins that belongs into which molecular function of electron transport proteins.
authors.affiliation: Department of Computer Science and Engineering, Yuan Ze University, Chung-Li, Taiwan. Electronic address: khanhlee87@gmail.com.
authors.forename: Nguyen-Quoc-Khanh
authors.initials: NQ
authors.lastname: Le
authors.affiliation: Department of Computer Science and Engineering, Yuan Ze University, Chung-Li, Taiwan.
authors.forename: Trinh-Trung-Duong
authors.initials: TT
authors.lastname: Nguyen
authors.affiliation: Department of Computer Science and Engineering, Yuan Ze University, Chung-Li, Taiwan. Electronic address: yienou@gmail.com.
authors.forename: Yu-Yen
authors.initials: YY
authors.lastname: Ou
mesh_terms: D000465:Algorithms; D000596:Amino Acids / Q000737:chemistry; D002352:Carrier Proteins / Q000378:metabolism*; D004579:Electron Transport
chemical_list: D000596:Amino Acids; D002352:Carrier Proteins
keywords: Annotation; Electron transport proteins; Feature selection; Transporter