Scientists have discovered a grouping of 75 paralogs that they say can hold the key to understanding more about human diseases and support better drug discovery.

Led by the Earlham Institute (EI) in Norwich, England, scientists from the U.K. and Hungary have discovered 75 critical paralog groups containing proteins with close evolutionary relationships to each other where one or two members in these groups can be critically important for a specific function and also their mutations can cause cancer or other inherited diseases.

Paralogs are genes related by duplication within a genome that are able to form and evolve new functions, which have similar functions in relations to cellular signaling. This means that there are several duplicated genes within the genome that might be redundant or less prominent when it comes to key cellular signaling pathways.

The discovery of these proteins identifies what their indispensable role in human cellular signaling pathways, as well as how to potentially guide drug targets and find biomarkers for disease diagnosis in the future.

Tamas Korcsmaros, a fellow at EI and the Institute of Food Research as well as lead author of the study, explained the function of the proteins.

“Our cells must be able to detect and respond to many different pieces of genetic information coming from both internal and external sources,” Korscsmaros said in a statement. “However, not all proteins in the cell are equally important.

“In the post-genomic era, we already know there are key groups of proteins responsible for detecting, transmitting and communicating through cross-talk between different cellular pathways,” he added. “Previously, it was challenging to identify which proteins, in which group, are more critical for the overall function of the cell; and those that are more relevant in causing diseases such as cancer, diabetes or neurodegenerative disorders.”

Korscsmaros said the discovery will allow scientists to continue to study and learn about the human biology.

“The computational biology workflow we developed and confirmed with known examples provides an easily applicable method for disease-specific analysis,” he said. “The concept will also help us to understand fundamental biological questions in comparative genomics on how duplication in the course of evolution led to more complex organs [such as the brain] and organisms.”

Dezső Módos, research associate at the University of Cambridge and first author of the study, described the importance of the study.

“Our study shows the importance of similar proteins [paralogs] in signaling networks,” he said in a statement. “Taking into account the paralog specificity in drug discovery because different paralog-specific signal routes could lead to totally different results like cell death or proliferation.”

The study, which appeared in Scientific Reports, can be viewed here.