Software

Powerful platform for rapid rational design of mutant proteins

We have designed our software keeping simplicity in mind. Operated through a highly intuitive interface, the online platform is the solution for the rapid rational design of mutant proteins. And ensures a straight and optimal user experience.

With 15 years of academic research and already more than 500 users, Dezyme software has demonstrated to offer a significantly greater predictive power compared to classical methods, consequently limiting the number of experimental tests. By allowing the systematic in-silico screening of mutant proteins, even the most complex, Dezyme is an efficient solution to improve the stability and the thermal resistance.

The software precisely identifies, in an automated way, the relevant mutations with the required stability properties. It evaluates the changes in stability of a given protein or peptide under specific single-site mutations specified by the user or under all possible single-site mutations, on the basis of the experimental or modeled protein structure.  Sequence regions corresponding to stability weaknesses, i.e. regions that are not optimal for stability or that could benefit from being mutated, are clearly identified.

The highly intuitive interface ensures fast exploitation of the software. So that the user can focus on the subsequent experimental studies that will be performed.

  • Flexible system to predict, with similar accuracy, mutant proteins that are modeled or based on experimental structures.
  • Multiple modes:
    • Systematic: evaluation of the stability changes on all possible mutations.
    • Manual: evaluation of the stability changes on one or more given mutations.
    • File: evaluation of the stability changes on a list of mutations specified by the user in an uploaded file.

References

Method & Perfomances: Dehouck Y, Grosfils A, Folch B, Gilis D, Bogaerts Ph, Rooman M. Prediction of protein stability changes upon mutations using statistical potentials and neural networks: PoPMuSiC 2.0. Bioinformatics 25:2537-2543 (2009)

Webserver & Sequence optimality: Dehouck Y, Kwasigroch JM, Gilis D, Rooman M. PoPMuSiC 2.1: a web server for the estimation of protein stability changes upon mutation and sequence optimality. BMC Bioinformatics 12:151 (2011)

Using PoPMuSiC with structural models: Gonnelli G, Rooman M, Dehouck Y. Structure-based mutant stability predictions on proteins of unknown structure. Journal of Biotechnology (2012)

    Outcome

    • Highly predictive
    • Rational protein design
    • Out of the box thinking