The research is focused on the development of molecular recognition methods for structural proteomics, Immunoinformatics and bioinformatics. The major goals are to develop approaches to the structural modeling of protein interactions and to design procedures for reconstruction and characterization of the network of connections between proteins in a genome.

Progress in the description of life processes at the molecular level requires better understanding of protein interactions. Computational studies of structural and physicochemical aspects of these interactions are important for revealing the underlying fundamental principles and for designing better tools to model protein complexes.

The number of protein-protein interactions in a genome is significantly larger than the number of individual proteins. In an effort to reconstruct protein interactions, most protein structures have to be models of limited accuracy. Thus the structure-based methods for building this network have to be fast and insensitive to significant inaccuracies of modeled structures.

Our research efforts combine proteomics research with computational problems motivated by genomics and medical research. Computational, biochemical, and molecular biological tools are used in an interdisciplinary approach to designing peptide fragments as synthetic drugs that specifically target diseased cells or infectious agents. The long term goal of our research is the development of selective strategies for the treatment of infectious diseases.

Our long-term goals are to understand the fundamental principles of protein interaction and to create a structure-based description of genomes