David Bednář

Site-specific analysis of protein hydration based on unnatural amino acid fluorescence.

Hydration of proteins profoundly affects their functions. We describe a simple and general method for site-specific analysis of protein hydration based on the in vivo incorporation of fluorescent unnatural amino acids and their analysis by steady-state fluorescence spectroscopy. Using this method, we investigate the hydration of functionally important regions of dehalogenases. The experimental results are compared to findings from molecular dynamics simulations.

FireProt: web server for automated design of thermostable proteins

Abstract 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.

Computer-assisted engineering of hyperstable fibroblast growth factor 2

Fibroblast growth factors (FGFs) serve numerous regulatory functions in complex organisms, and their corresponding therapeutic potential is of growing interest to academics and industrial researchers alike. However, applications of these proteins are limited due to their low stability. Here we tackle this problem using a generalizable computer‐assisted protein engineering strategy to create a unique modified FGF2 with nine mutations displaying unprecedented stability and uncompromised biological function. The data from the characterization of stabilized FGF2 showed a remarkable prediction potential of in silico methods and provided insight into the unfolding mechanism of the protein. The molecule holds a considerable promise for stem cell research and medical or pharmaceutical applications.