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QSAR Study of Angiotensin I-Converting Enzyme Inhibitory Peptides Using SVHEHS Descriptor and OSC-SVM

  • Xiao Guan
  • Jing LiuEmail author
Article
  • 97 Downloads

Abstract

In this paper, four models of quantitative structure–activity relationship (QSAR) for 84 angiotensin I-converting enzyme inhibitory (ACEI) dipeptides, 169 ACEI tripeptides and 15 ACEI tetrapeptides and the total 268 peptides were established, respectively. During every modeling process, the structure of the peptides were firstly described using a set of amino acid descriptor SVHEHS proposed previously in our laboratory, then QSAR models were developed successfully by orthogonal signal correction combined with support vector machine (OSC-SVM). Furthermore, all models were validated by the reasonable statistical parameters, such as correlation coefficient (R2), cross-validated correlation coefficient (q2) and external validation coefficient (q2ext), etc. The results demonstrated that all developed QSAR models had excellent fitting accuracy and predictive ability. It could be a very promising approach for QSAR study on bioactive peptides using SVHEHS descriptor and OSC-SVM.

Keywords

Quantitative structure–activity relationship ACE inhibitory peptide Descriptor Support vector machine Modeling 

Notes

Acknowledgements

The work was supported by the National Key Research and Development Program of China (2017YFD0401202), the National Natural Science Foundation of China (31701515) and the Special Fund for Scientific Research in the Grain Public Interest (201513003-8).

Compliance with Ethical Standards

Conflict of interest

Xiao Guan and Jing Liu declares that they have no conflict of interest.

Ethical Approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Informed Consent

Informed consent was obtained from all individual participants included in the study.

Supplementary material

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Medical Instrument and Food EngineeringUniversity of Shanghai for Science and TechnologyShanghaiPeople’s Republic of China
  2. 2.College of Information EngineeringShanghai Maritime UniversityShanghaiPeople’s Republic of China

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