A New Descriptor of Amino Acids-SVGER and its Applications in Peptide QSAR

In the study of peptide quantitative structure activity relationship (QSAR), a new descriptor of amino acids (SVGER) was calculated. It was applied in two peptides which are angiotensin converting enzyme inhibitors and bitter tasting threshold of di-peptide. QSAR models were built by stepwise multiple regression-multiple linear regression (SMR-MLR) and stepwise multiple regression-partial least square regression (SMR-PLS). In the SMR-MLR models for angiotensin converting enzyme inhibitors, the squared cross-validation correlation coefficient (Q_LOO² ) was 0.907, squared correlation coefficient between predicted and observed activities (R_cum² ) was 0.977 and external multiple correlation coefficient (Q_ext² ) was 0.867. The corresponding data for the bitter tasting threshold of di-peptide were 0.802, 0.966, 0.719. While in the SMR-PLS model, Q_LOO² , R_cum² and Q_ext² were 0.804, 0.915, 0.858 for angiotensin converting enzyme inhibitors and 0.782, 0.881, 0.747 for bitter tasting threshold of di-peptide. Our results showed that descriptor SVGER can afford good account of relationships between activity and structure of peptide drugs.