化学
数量结构-活动关系
品酒
抗菌剂
相似性(几何)
立体化学
人工智能
有机化学
食品科学
葡萄酒
计算机科学
图像(数学)
作者
Shu-Fen Wu,Wei Qi,Rongxin Su,Tonghe Li,Dan Lu,Zhimin He
标识
DOI:10.1016/j.ejmech.2014.07.015
摘要
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.
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