Bioinformatics software predicts the effect of cancer-associated mutations

Researchers from the University of the Basque Country (UPV/EHU) have created a bioinformatics tool, WREGEX 2.0, to predict the effect of cancer-related mutations. Created by a multidisciplinary team the software can analyse up to 40,000 proteins per minute.

Proteins consist of chains of amino acids and in each one it is possible to make out short sequences of amino acids with a discrete function called functional motifs. In some instances these motifs have already been described, in others, they are yet to be specified.

When a functional motif appears modified, the mutation could influence the development of a disease such as cancer. Verifying the possible changes in a protein is one of the first steps in conducting research into its function. The human proteome is made up of around 40,000 proteins so finding the mutations in each one is a massive undertaking.

This provided the impetus for the three main researchers on the project. José Antonio Rodríguez provided the biological question; Asier Fullaondo, the knowledge of bioinformatics tools and databases; and Gorka Prieto, the programming skills.

Initially, these PhD holders developed a piece of software, WREGEX that can be used to predict and automatically seek out 'functional motifs' - the small groups of amino acids that develop specific tasks in a protein.

The team took another step and combined the information on the sequences of all known human proteins with the COSMIC catalogue that gathers the mutations linked to cancer. This led to the creation of WREGEX 2.0.

This new version allows a normal protein to be compared with the mutant so as to be able to predict 'functional motifs' that have been modified and which could be linked to cancer. ‘You may also have experience in how a motif functions and you want to find out which proteins it could appear in and whether it appears modified into cancer. With this software you can obtain candidates to start to study,’ explained Gorka Prieto.

The result is a piece of software that combines three types of information: the protein sequences, the functional motifs, and the cancer mutations. ‘One of the main features of WREGEX 2.0 is that it can simultaneously study highly complex proteomes with masses of proteins and combine information, in the case of the trial, with cancer mutations; but the door is open for using other databases containing information about other types of mutations. The advantage, moreover, is that 40,000 proteins a minute can be analysed, while with other programs the analysis of a single protein took several minutes,’ explained Asier Fullaondo.

So far, thirteen pieces of research have already used this computing tool. Researchers in China, Japan, Korea, Germany and the United States have accessed the server to carry out their analysis.

Further reading: ‘Gorka Prieto, Asier Fullaondo & Jose A. Rodríguez. Proteome-wide search for functional motifs altered in tumors: Prediction of nuclear export signals inactivated by cancer-related mutations. Scientific Reports. doi:10.1038/srep25869’

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