CoMFA and CoMSIA analysis of ACE-inhibitory, antimicrobial and bitter-tasting peptides

Shufen Wu; Wei Qi; Rongxin Su; Tonghe Li; Dan Lu; Zhimin He

doi:10.1016/j.ejmech.2014.07.015

CoMFA and CoMSIA analysis of ACE-inhibitory, antimicrobial and bitter-tasting peptides

Eur J Med Chem. 2014 Sep 12:84:100-6. doi: 10.1016/j.ejmech.2014.07.015. Epub 2014 Jul 7.

Authors

Shufen Wu¹, Wei Qi², Rongxin Su³, Tonghe Li¹, Dan Lu¹, Zhimin He⁴

Affiliations

¹ Chemical Engineering Research Center, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China.
² Chemical Engineering Research Center, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China; State Key Laboratory of Chemical Engineering, Tianjin University, Tianjin 300072, PR China; Tianjin Key Laboratory of Membrane Science and Desalination Technology, Tianjin University, Tianjin 300072, PR China; The Co-Innovation Center of Chemistry and Chemical Engineering of Tianjin, PR China. Electronic address: qiwei@tju.edu.cn.
³ Chemical Engineering Research Center, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China; State Key Laboratory of Chemical Engineering, Tianjin University, Tianjin 300072, PR China; Tianjin Key Laboratory of Membrane Science and Desalination Technology, Tianjin University, Tianjin 300072, PR China; The Co-Innovation Center of Chemistry and Chemical Engineering of Tianjin, PR China.
⁴ Chemical Engineering Research Center, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China; State Key Laboratory of Chemical Engineering, Tianjin University, Tianjin 300072, PR China; The Co-Innovation Center of Chemistry and Chemical Engineering of Tianjin, PR China.

PMID: 25016232
DOI: 10.1016/j.ejmech.2014.07.015

Abstract

Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were applied to the ACE-inhibitory, antimicrobial, and bitter-tasting peptides. Predictive 3D-QSAR models were established using SYBYL multifit molecular alignment rule over a training set and a test set. The optimum models were all statistically significant with cross-validated coefficients (Q(2)) >0.5 and conventional coefficients (R(2)) >0.9, indicating that they were reliable enough for activity prediction. The obtained results may aid in the design of novel bioactive peptides.

Keywords: ACE inhibition; Antimicrobial; Bitterness; CoMFA; CoMSIA.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms
Angiotensin-Converting Enzyme Inhibitors / chemistry*
Anti-Infective Agents / chemistry*
Models, Molecular
Peptides / chemistry*
Quantitative Structure-Activity Relationship
Regression Analysis
Taste*

Substances

Angiotensin-Converting Enzyme Inhibitors
Anti-Infective Agents
Peptides