Abstract
A novel set of descriptors G-scale was derived from 457 physicochemical properties of the natural amino acids. The descriptors were then applied to study on quantitative structure-activity relationships (QSARs) of nine peptide datasets of angiotensin-converting enzyme inhibitor (ACE-inhibitor) oligopeptides (between dipeptides and decapeptides) by using partial least square (PLS) regression. The multiple correlation coefficients (R2) and leave one out cross validation values (Q2) of PLS models are better than or close to the results of references. The results show that the descriptors proposed here may be a useful structural expression method, and they may be hopefully used in biological activity study of ACE-inhibitor oligopeptides.
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Acknowledgments
This study was supported by the National Natural Science Foundation of China (No. 60873103), and supported by the Key Project of Natural Science Foundation of China (No. 30830090), Create new drugs national major projects (2009ZX09503-005), and the Foundation for the Author of National Excellent Doctoral Dissertation of P.R. China (200776).
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Wang, X., Wang, J., Lin, Y. et al. QSAR study on angiotensin-converting enzyme inhibitor oligopeptides based on a novel set of sequence information descriptors. J Mol Model 17, 1599–1606 (2011). https://doi.org/10.1007/s00894-010-0862-x
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DOI: https://doi.org/10.1007/s00894-010-0862-x