FireProt 1.0



FireProt 1.0 is a web server providing a robust computational strategy for predicting highly stable multiple-point mutants that combines energy- and evolution-based approaches with smart filtering to identify additive stabilizing mutations. Within its workflow, FireProt integrates sixteen computational tools, utilizing both sequence and structural information in the process. The web server provides users with a one-stop-shop solution for the design of thermostable proteins, constructed by three strategies: (i) evolution-based approach, utilizing back-to-consensus analysis; (ii) energy-based approach, using conservation, correlation and energy information and (iii) combined approach. FireProt can be applied to any protein for which a tertiary structure and homologous sequences are available, and will facilitate the rapid development of robust proteins for biomedical and biotechnological applications.

Preliminary reference: Musil, M., Stourac, J., Bendl, J., Brezovsky, J., Prokop, Z., Zendulka, J., Martinek, T., Bednar, D., Damborsky, J., 2017: FireProt: Web Server for Automated Design of Thermostable Proteins, Nucleic Acids Research (submitted)

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PredictSNPPredictSNP 1.0


PredictSNP1 is an ensemble-­based classifier for prediction of the effect of amino acid substitutions and their prioritization for experimental characterization. It combines six well­-established computational methods (MAPP, PhD-­SNP, PolyPhen­-1, PolyPhen­-2, SIFT and SNAP) by two-level weighted consensus approach to provide more accurate and robust alternative to the predictions delivered by individual tools. The predictions from the computational tools are supplemented by experimental annotations from the Protein Mutant Database and the UniProt database.

PredictSNP2 extends the scope of genome analysis to the level of nucleotide substitutions that enables to identify disease­-related variants within the whole genome. Similarly to PredictSNP1, the results of five existing best-­performing tools (CADD, DANN, FATHMM, FunSeq2 and GWAVA) are combined by two­-level weighted consensus approach. To provide a comprehensive evaluation of variants, the predictions are complemented with annotations from eight databases.

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HotSpot Wizard

HotSpot Wizard 2.0

HotSpot Wizard is a web server for automated identification of ‘hot spots’ and design of smart libraries for engineering proteins’ stability, catalytic activity, substrate specificity and enantioselectivity. HotSpot Wizard implements four different established protein engineering strategies, enabling the user to selectively target sites affecting the protein’s stability and catalytic properties. The server should be useful for protein engineers interested in exploring the structure of their favourite protein and for the design of mutations in site-directed mutagenesis and focused directed evolution experiments. Compared to its predecessor, HotSpot Wizard 2.0 introduces several major improvements, and a new graphical interface.

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CAVER is a software tool widely used for the identification and characterization of transport pathways in macromolecular structures. A new version – CAVER 3.0 enables automatic analysis of tunnels and channels in large ensembles of protein conformations since the analysis of molecular dynamics simulation is essential for the estimation of pathway characteristics and elucidation of the structural basis of the tunnel gating. CAVER 3.0 paves the way for the study of important biochemical phenomena in the area of molecular transport, molecular recognition and enzymatic catalysis. The software is freely available as a multiplatform JAVA command-line application or PyMol plug-in.

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CAVER Analyst 1.0

CAVER Analyst is a software tool for calculation, analysis and real-time visualization of access tunnels and channels in static and dynamic protein structures. It provides an intuitive graphic user interface for setting up the calculation and interactive exploration of identified tunnels/channels and their characteristics. CAVER Analyst is a multi-platform software written in JAVA freely available for non-commercial use.

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Alzheimer’s Disease Consortium Meeting April 7-8
ES-Cat project Kick-off meeting in Cambridge
Loschmidt Laboratories place importance on combining theory and practice
Laboratory growing international
G. Dankova and A. Kunka awarded Brno Ph.D. Talent
Jaroslav Bendl, Ph.D.: From Loschmidt Laboratories to Mount Sinai School of Medicine in New York
Open Postdoc Position: Bioinformatics & Modeling