Abstract:

Primary structure characterization is the key to quantitative sequence-activity modeling(QSAM) of polypeptides. This paper reported three new descriptors, GS-AA531, MSCC and GS-AA531-MSC, identified through integrating the information in peptide or protein primary structure. The calculations identified these descriptions were simple, only based on amino acid sequence, suitable to peptides with different lengths and could capture the context features. The new descriptors and other reference descriptors were applied to the two AMPs systems(equal and unequal length peptides) for constructing QSAM models combined with features screening. The accuracies of fitting, leave-one-out cross validation, and extra-sample prediction for the models based on GS-AA531 and GS-AA531-MSC descriptors improved significantly compared with those based on the other descriptors. Therefore, the new peptide or protein descriptors GS-AA531 and GS-AA531-MSC are pro-mising for broad applications in peptide or protein QSAM study.

Key words: Structural characterization, Quantitative sequence-activity model, Antimicrobial peptide, Support vector regression, Feature screening