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The analysis of the three-dimensional shape of proteins enables detailed insight into the mechanisms governing their biological function. The investigation of structural information can reveal, for instance, knowledge on remote homologies among related proteins or the amino acids involved in the catalytic reaction or ligand binding. ProCeryon has been developing a portfolio of tools to exploit structural information to the fullest extent.

With our fold recognition technology we predict protein structures in silico. This way, structure-based characterization is extended to proteins whose structures are not yet available. The core of our structure prediction technology are knowledge-based potentials which are derived from the interactions observed in well-defined protein structures. Such potentials have been demonstrated repeatedly to be capable of identifying native protein structures.

For the analysis of protein structures, we have developed algorithms for protein structure superimposition and methods to study energetic states of protein structures. Applications of these techniques include the identification of active sites, detection of remote homologies, estimation of the effects of mutations and polymorphisms on protein structure and stability.

Additionally, we have incorporated in our technological platform the various methods of sequence comparison whose performance has been enhanced through the integration of proprietary data bases and algorithms.


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