Protein–protein interactions mediate several cellular functions, which can be understood from the information obtained using the three-dimensional structures of protein–protein complexes and binding affinity data. This review focuses on computational aspects of predicting the best native-like complex structure and binding affinities. The first part covers the prediction of protein–protein complex structures and the advantages of conformational searching and scoring functions in protein–protein docking. The second part is devoted to various aspects of protein–protein interaction thermodynamics, such as databases for binding affinities and other thermodynamic parameters, computational methods to predict the binding affinity using either the three-dimensional structures of complexes or amino acid sequences, and change in binding affinities of the complexes upon mutations. We provide the latest developments on protein–protein docking and binding affinity studies along with a list of available computational resources for understanding protein–protein interactions.