New software has been developed by researchers at the University of Basque County that is able to analyze mutations within proteins. These mutations are potential inducers of diseases, including but not limited to cancer. The development is easy, free, versatile and offers a fast bioinformatics application that is capable of analyzing and combining the information from 40,000 proteins within a matter of 60 seconds.

Proteins are made up of chains of amino acids and in each one it is possible to make out short sequences of amino acids with a discrete function known as functional motifs. In certain situations the motifs have already been described, while in others they may not have been specified. When a normal functioning motif appears to be modified, the mutation can then influence the development of a disease, like cancer. Verifying the change (or changes) that may occur is one of the first steps in conducting research into its function. We must keep in mind that the current draft of the human proteome is made up of over 40,000 proteins.

Pinpointing mutations one at a time is a very difficult task and this is why the three researchers began to work on the bioinformatics tool. José Antonio Rodríguez, Asier Fullaondo and Gorka Prieto created a piece of software known as the WREGEX that can be used in order to predict and automatically trace “functional motifs”. These are a small group of amino acids that develop specific tasks within a protein. The team tested the program to predict motifs that move a protein from the nucleus to the cytoplasm of a cell. At the end of their research phase back in 2014, they published a paper explaining their findings in Bioinformatics journal. José Antonio Rodríguez says the problem was when you answer one question during any type of research; you open up a door that contains even more questions. The new question was: which proteins in a sequence of amino acids could have a functional cancer-mutant ‘motif’?

To find an answer, the researchers combined the information on the sequences of all known human proteins with the COSMIC catalogue that gathers the mutations linked to cancer. This is when WREGEX 2.0 was born which allows a normal protein to be compared with the same mutant one, letting it help predict functional motifs that have been modified and may be linked to cancer. Gorka Prieto says 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 begin a study.

New Software Can Predict Cancer Mutations

A mutation of amino acid 144 of the UPSP21 protein (containing over 500 amino acids) causes it to grow in the nucleus of a cell instead of remaining outside. Picture shows the protein in green and the cell nucleus in blue. (Image credit: UPV/EHU
A mutation of amino acid 144 of the UPSP21 protein (containing over 500 amino acids) causes it to grow in the nucleus of a cell instead of remaining outside. Picture shows the protein in green and the cell nucleus in blue. (Image credit: UPV/EHU

In order to test the bioinformatics program, the team carried out a “cell exportation trial”. Various candidates were chosen that could constitute a motif responsible for moving the protein outside the nucleus of the cell. After modifying them according to the tumor mutations described in the COSMIC catalogue and checking their functioning, a new trial was started. Candidates acted as an “exportation signal” that the mutated affected the way they worked, and that the software was proved to be valid.

Asier Fullaondo says 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 still open for using the databases containing information about other types of mutations. The advantage is that 40,000 proteins a minute can be analyzed while with other programs the analysis of a single protein took several minutes at minimum. With the new software, it is possible to predict that the alteration in a protein may influence the development of disease, not just in cancer but in a wide range of other health problems.

Thus far, thirteen pieces of research have used this computing tool. Researchers from China, Japan, Korea, Germany and the United States have accessed the server. The team is already thinking about continuing their work and finding new ways to improve the tool.

The full study was published in Scientific Reports journal.