International researchers have developed a computer tool capable of proving a 3D view of genes, proteins and metabolites for improved insight into drug reactions. Findings were published in Nature Biotechnology.
Led by Bernhard Palsson, a professor of bioengineering at the University of California, San Diego (UCSD), a team of researchers developed the 3D tool to improve the understanding of disease causing mutations and develop new drug theories for diseases like cancer. In this study, the production and findings of the Recon3D tool were outlined.
Currently, analyzing the human metabolic network involved methods the sequence data of DNA in a linear fashion. However, because DNA is structured with coils, twists and folds, comprehensive research has not been completed. The Recon3D is able to integrate 3,288 open reading frames, which are stretches of DNA and RNA that contain protein-producing genes; 13,542 metabolic reactions; and the 3D structures of 4,140 metabolites and 12,890 proteins, making it the most comprehensive network reconstruction.
"This is the first resource to link all these different data types together in one place and has shown to be a very valuable tool for analyzing sequencing data," said Elizabeth Brunk, a postdoctoral researcher at UCSD and first author of the study.
In the study, researchers used Recon 3D to map single nucleotide polymorphisms (SNPs), associated with diseases like cancer. They were able to pinpoint where mutations occurred in proteins and found many of them within the same region. Additionally, researchers found harmful mutations were more likely to neighbor other mutations.
"It is wonderful to see how this international group of researchers came together to generate Recon3D, that accounts for 17 percent of the functionally annotated genes on the human genome," Palsson said. "Given the involvement of metabolism in most major diseases (cancer, nervous system, diabetes, etc.) and wellness, Recon3D is likely to help break new ground in human metabolic research."