Thanks to international effort of genome sequencing projects, last years brought massive amount of new amino acid sequences. Although experimental methods for determining protein structure are providing new structures, they cannot keep the pace at which sequences are resolved. For a large fraction of proteins whose structures will not be determined experimentally, computational methods can provide valuable information.

Selvita's goal is to provide computational methods that accurately predict protein structure and protein complexes. Our modeling technology is based on the CABS model, state-of-the-art approach to protein structure prediction. Our innovative, comparative modeling strategies enable high-accuracy structure prediction using existing, even remote, protein homologs as scaffolds. Combining results of structure prediction and modeling with lead optimization techniques provides a unique opportunity for a new level of rational drug design.

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1. Characterization of protein structural changes: an efficient modeling approach.
2. CLUSTERING AS A SUPPORTING TOOL FOR STRUCTURAL DRUG DESIGN