Multiple sequence alignments as tools for protein structure and function prediction

FireProt: web server for automated design of thermostable proteins

There is a continuous interest in increasing proteins stability to enhance their usability in numerous biomedical and biotechnological applications. A number of in silico tools for the prediction of the effect of mutations on protein stability have been developed recently. However, only single-point mutations with a small effect on protein stability are typically predicted with the existing tools and have to be followed by laborious protein expression, purification, and characterization. Here, we present FireProt, a web server for the automated design of multiple-point thermostable mutant proteins that combines structural and evolutionary information in its calculation core. FireProt utilizes sixteen tools and three protein engineering strategies for making reliable protein designs. The server is complemented with interactive, easy-to-use interface that allows users to directly analyze and optionally modify designed thermostable mutants. FireProt is freely available at http://loschmidt.chemi.muni.cz/fireprot.

Deciphering epitope specificities within polyserum using affinity selection of random peptides and a novel algorithm based on pattern recognition theory

While numerous strategies have been developed to map epitope specificities for monoclonal antibodies, few have been designed for elucidating epitope specificity within complex polysera. We have developed a novel algorithm based on pattern recognition theory that can be used to characterize the breadth of epitope specificities within a polyserum based on affinity selection of random peptides. To attribute these random peptides to a specific epitope, the sequences of the affinity-selected peptides were matched against a database of random peptides selected using well-described monoclonal antibodies. To test this novel algorithm, we employed polyserum from patients infected with West Nile virus and isolated 109 unique sequences which were recognized selectively by serum from West Nile virus-infected patients but not uninfected patients. Through application of our algorithm, it was possible to match 20% of the polyserum-selected peptides to the database of peptides isolated by affinity selection using monoclonal antibodies against the virus envelope protein. Statistical analysis demonstrated that the peptides selected with the polyserum could not be attributed to the peptide database by chance. This novel algorithm provides the basis for further development of methods to characterize the breadth of epitope recognition within a complex pool of antibodies.