In many cellular and signaling processes protein-protein and protein -peptide interactions are responsible for many biological activities, such as DNA replication and repair, gene regulation and transcription. At the interaction interface, only a small fraction of interacting interface residues termed as hot spots contribute most to the binding free energy of an interaction. Identification and characterization of hot spots is important to explore the underlying binding mechanism and the stability of protein–protein interactions. As the experimental screenings to identify and characterize hot spots are not feasible to carry out in reasonable time, there is a need to employ computational approaches to predict hot spots. These hot spots can be easily predicted using computational methods such as alanine scanning. In this work, we have extensively carried out Ala scan approaches to various benchmarking data sets of protein and peptides and predicted hot spots. Using the analysis of hot spots an attempt has been made to elucidate differences among protein-protein and protein peptide interactions. The knowledge of differences has implications for the molecular design of biologics.