IDENTIFICATION OF PROTEIN-PROTEIN BINDING SITES BY INCORPORATING THE PHYSICOCHEMICAL PROPERTIES AND STATIONARY WAVELET TRANSFORMS INTO PSEUDO AMINO ACID COMPOSITION - Kobilova , Guzal Ilhomovna; Rahmatullayeva , Madina Jasur kizi (Educational Research in Universal Sciences, 2024)
With the explosive growth of protein sequences entering into protein data banks in the post-genomic era, it is highly demanded to develop automated methods for rapidly and effectively identifying the protein–protein binding sites (PPBS) based on the sequence information alone. To address this problem, we proposed a predictor called iPPBSPseAAC, in which each amino acid residue site of the proteins concerned was treated as a 15-tuple peptide segment generated by sliding a window along the protein chains with its center aligned with the target residue. The working peptide segment is further formulated by a general form of pseudo amino acid composition via the following procedures: (1) it is converted into a numerical series via the physicochemical properties of amino acids; (2) the numerical series is subsequently converted into a 20-D feature vector by means of the stationary wavelet transform technique. Formed by many individual “Random Forest” classifiers, the operation engine to run prediction is a two-layer ensemble classifier, with the 1st-layer voting out the best training data-set from many bootstrap systems and the 2nd-layer voting out the most relevant one from seven physicochemical properties.