Protein-protein complexes play key roles in all cellular signal transduction processes. We have developed a fast and accurate computational approach to predict changes in the binding free energy upon alanine mutations in protein-protein interfaces. The approach is based on a knowledge-based scoring function, DrugScore(PPI), for which pair potentials were derived from 851 complex structures and adapted against 309 experimental alanine scanning results. Based on this approach, we developed the DrugScore(PPI) webserver. The input consists of a protein-protein complex structure; the output is a summary table and bar plot of binding free energy differences for wild-type residue-to-Ala mutations. The results of the analysis are mapped on the protein-protein complex structure and visualized using J mol. A single interface can be analyzed within a few minutes. Our approach has been successfully validated by application to an external test set of 22 alanine mutations in the interface of Ras/RalGDS. The DrugScore(PPI) webserver is primarily intended for identifying hotspot residues in protein-protein interfaces, which provides valuable information for guiding biological experiments and in the development of protein-protein interaction modulators. The DrugScore(PPI) Webserver, accessible at http://cpclab.uni-duesseldorf.de/dsppi, is free and open to all users with no login requirement.