Scientists have developed an advanced computer tool called “MoPegen” to help identify genetic mutations that were previously invisible in proteins, which opens new horizons in cancer research and treatment.
The tool developed researchers from the University of California, Plos Angeles in the United States and the University of Toronto, and published their results in the “Nature Biotechnology” results on Nature Biotechnology on June 16, and was written by Yurrick Alert.
The algorithm launches the full potential of the protographic science by overcoming a major challenge in linking genetic mutations to protein changes.
Protegenomics combines the study of genomics and protections, and protein science is the study of reactions, functions, composition and structure of proteins and cellular activities to provide a comprehensive molecular image of diseases.
This tool will help to understand how changes in our DNA affects proteins, and how it eventually contributes to cancer, degenerative neurological diseases and other conditions. It also provides a new way to create diagnostic tests, and to find therapeutic goals that were not clear for previous researchers.
The main challenge was the inability to accurately detect the changing peptides, which limits the ability to identify genetic mutations at the protein level. Current protein tools often fail to capture the full diversity of protein changes. To overcome this challenge, the researchers developed the MP Jin program, which enables the determination of protein changes with more accurately.
“We have developed the MB Jin program to help researchers identify genetic variables that are actually expressed at the level of protein, which addresses a long -term challenge in the field of genetic protein,” said Dr. Chenghao Chu, post PhD researcher at the Department of Human Genetics at the University of California, Plos Angeles and co -author of the study.
He added, “Our tool greatly improves the discovery of hidden protein changes using an approach based on graphs to address all kinds of genetic changes efficiently. This provides a more comprehensive vision of protein diversity, and researchers give a much more accurate picture of how mutations affect the disease.”
This level of accuracy is extremely important because proteins play an essential role in almost every biological function, and changes in their structure can indicate the development of the disease, especially in cancer, and proteins analysis to detect these changes still represents a huge mathematical challenge.
Huge ability to analyze complex data
Unlike the current methods that primarily discover simple genetic changes such as replacement of single amino acids, the Mo Pep Jin tool is designed to determine a wide range of protein differences resulting from complex genetic adjustments.
The tool works on a systematic modeling of how genes are expressed and translated into proteins, which greatly expands the ability to detect diseases associated with diseases.
“So far there has been no practical way to deal with the tremendous complexity of the genetic and relaxed difference,” Zhu said.
To demonstrate its effectiveness, the team used the MB Jin Jin tool to analyze the genomic protein data from five tumors in the prostate, eight tumors in the kidneys, and 376 cellular strains.
They found that she succeeded in determining protein differences that could not have been discovered previously linked to genetic mutations, genes, and other molecular changes. It has also proven to be more sensitive and inclusive than previous roads, as he discovered four times more unique protein variables than ancient roads.
The researchers noted that one of the most interesting Mo Pep -Jin applications is immunotherapy, as it can identify the changing peptides of cancer that may be used as filters for new antigens, which is essential to developing cancerous vaccines and custom cellular treatments.
Dr. Paul Peter, Professor of Urology and Human Genetics at the David Given College of Medicine at the University of California Plos Angeles and Director of Cancer Data Science at the Johnson Comprehensive Cancer Center of the University of California Plos Angeles and co -author of the study, said “By facilitating the analysis of complex protein variables, Mo Pep Jin has the ability to develop research in the field of cancer and diseases Neurological degeneration and other areas in which the understanding of the diversity of proteins is very important.
He added, “It blocks the gap between genetic data and protein expression in the real world, which opens new horizons in careful medicine and beyond.”
The tool is available for free to researchers and can be combined with the functioning of current protein analysis, which makes it available for laboratories all over the world, according to researchers.