Identifying the molecular functions of electron transport proteins using radial basis function networks and biochemical properties

Nguyen Quoc Khanh Le, Trinh Trung Duong Nguyen, Yu Yen Ou

研究成果: 雜誌貢獻文章

16 引文 (Scopus)

摘要

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.
原文英語
頁(從 - 到)166-178
頁數13
期刊Journal of Molecular Graphics and Modelling
73
DOIs
出版狀態已發佈 - 五月 1 2017
對外發佈Yes

指紋

Radial basis function networks
Carrier Proteins
proteins
electrons
Electron Transport
Electrons
respiration
classifying
cells
food
Proteins

ASJC Scopus subject areas

  • Spectroscopy
  • Physical and Theoretical Chemistry
  • Computer Graphics and Computer-Aided Design
  • Materials Chemistry

引用此文

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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.",
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AB - 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.

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