We describe a multi parametric-approach, YAPPIS-Finder, for predicting the PPI sites on protein surface. A non-redundant database of comprised of 2,265 protein-protein interaction interfaces (PPIIs) involving 4,530 protein-protein interacting partners
(PPIPs) and depicting the interaction between protein-chains of experimentally determined PPCs was used in designing the YAPPIS-Finder. Parametric score obtained on analyzing these 4,530 PPIPs with respect to their residue interface propensity, their
hydrophobic content, and amount of solvation free energy associated with them provided the basis of YAPPIS-Finder. By applying YAPPIS-Finder on another dataset 4,290 PPIPs from 2,145 PPIIs, the optimal range of the parametric scores and protein-probe van
der Waals energy of interaction was determined. Subsequently, taking the optimal range of PPIP parametric scores and threshold for protein-probe van der Waals energy of interaction into the consideration, the YAPPIS-Finder was tested on a blind dataset of
554 protein-chains and it was found predicting 69.67% sites correctly. On predicting only one PPI site on each protein-chain, the YAPPIS-Finder found covering 22.91% of actually sites in the predicted site. Contrary to this, the sites predicted by SPPIDER
covered 22.7% of actual sites. However, on predicting two PPI sites for each protein-chain, the percentage coverage of actual sites in the predicted sites by YAPPIS-Finder exceeded two-fold (i.e. 41.81%), thus making the YAPPIS-Finder a better method.