Two bio articles related to HPC are making their way around the interwebs this week. The first is about using supercomputers to identify molecular structures with the potential to have value as new medicines. From Physorg.com
Previous methods to identify these molecules have emphasized searching for fragments that can attach to one hot spot at a time. Finding structures that attach to all of the required hot spots is tedious, time-consuming and error-prone.
Ohio State University researchers, however, have used computer simulations to identify molecular fragments that attach simultaneously to multiple hot spots on proteins. The technique is a new way to tackle the fragment-based design strategy.
“We use the massive computing power available to us to find only the good fragments and link them together,” said Chenglong Li, assistant professor of medicinal chemistry and pharmacognosy at Ohio State and senior author of a study detailing this work.
…”My method reconstructed what pharmaceutical companies have already done,” he said. “In the future, we’ll apply this technique to protein targets for diseases that remain challenging to treat with currently available therapies.”
Then, ScienceBlog.com reports that researchers at the Virginia Bioinformatics Institute (VBI) and the Department of Computer Science at Virginia Tech are using HPC to find small genes that have been missed by scientists as they identify DNA sequences
Using an ephemeral supercomputer made up of computers from across the world, the mpiBLAST computational tool used by the researchers took only 12 hours instead of the 90 years it would have required if the work were performed on a standard personal computer.
The new study, reported in the journal BMC Bioinformatics, is the first large-scale attempt to identify undetected genes of microbes in the burgeoning GenBank DNA sequence repository that contains over 100 billion bases of DNA sequence. The genes uncovered may have important functions in the cell, but those functions need to be established by further experiment.
…João Setubal, associate professor at the Virginia Bioinformatics Institute and the Department of Computer Science at Virginia Tech, commented: “Scientists have known for a long time that publicly available databases of genomes have inconsistencies, errors, and gaps. Some genes are labeled with the wrong function and for others the function is unknown. But nobody had done a systematic study to verify how many genes were simply undetected. This is what we did in our study — discover the number of microbial genes that are under the radar.”
You can read the full paper describing that work here.
