Protein Interaction Hotspot Identification Using Sequence-based Frequency-derived Features


They predict protein hotspots (small fractions of the protein interface that contribute to most of the necessary binding energies for interactions) passing protein amino acid sequence to a numerical serie (using electron-ion interaction pseudo-potential (EIIP) and ionization constant (IC) parameter of each amino acid, and transform it to a frequency by a Fourier transformation (in a similar way to Resonant Recognition Model, but RRM-based hotspots initially requires the computation of the characteristic frequency of a family of proteins and in this case is not imposed such a constraint).

They support the conjecture of Cosic's RRM that protein hotspots are associated with frequency features of physico-chemical characteristics of the amino acid sequence (but in RRM model this is associated with with electron-ion interaction potentials and here they have shown that protein hotspots may also involve specific frequency-related features for other physico-chemical characteristics such as ionization constant).


Last modified on 15-Mar-16

/ EMMIND - Electromagnetic Mind