Thanks to enormous progress in sequencing of genome data currently we know millions of protein sequences. At the same time, due to costly and difficult procedures, the number of experimentally solved protein structures is much smaller, ca. 60,000. Thus, theoretical, in silico, prediction of protein structures and dynamics is essential for understanding the molecular basis of drug action, metabolic and signaling pathways in living cells, designing new technologies in the life science and material sciences. The next and even more challenging step in structural genomics is the determination of protein complexes, needed to have a complete molecular-level understanding of a protein function.

Selvita Protein Modeling Platform (SPMP) is a new kind, web-based, protein modeling tool, built on the idea that the protein modeling can be more user-friendly and practical. The SPMP is designed for protein modelers and biologists, who want to use protein and protein assembly structure information in a drug design or in studies of molecular mechanisms.

Starting with the homology modeling set of tools along with unique structure prediction from sequence-only and protein-protein docking capabilities, the SPMP allows researchers to obtain comparative views of protein structure data and their binding modes they need to understand.