Researchers at University of California, San Diego have developed a new tool that may help in screening for new drugs and studying natural compounds.

The team believes that the tool may aid drug discovery researchers who need to know as much as possible and as quickly as possible about the natural products with antibiotic, antiviral and other pharmacologically interesting properties that they are probing.

A new combination of experimental and computational protocols can cut the time it takes to determine the structure of peptides derived from natural compounds from six months or a year to as little as one day.

According to the researchers, it is currently difficult, time consuming and costly to determine the molecular structure of a class of natural compounds called nonribosomal peptides (NRPs) that are intensely studied for their drug potential.

"Non-ribosomal peptides evolved over millions of years and often serve chemical defence and communication purposes for the organisms that manufacture them," said Nuno Bandiera, first author, a UCSD postdoctoral researcher and successful Ph.D. candidate from the computer science department at UCSD's Jacobs School of Engineering.

The new tool is a quick, automated and inexpensive way to determine the structure of NRPs.

If we suppose NRP structure to be a cyclic string of beads, then the new algorithms both decipher the mass of each bead based on the mass spectrometry and determine the order of the beads within the ring - crucial pieces of information for uncovering both the structure of the molecule and its pharmacological activities.

The authors said that the work might facilitate biosynthetic engineering efforts to reprogram E. coli strains in order to turn them into NRP assembly lines.

"This work removes a particularly troublesome bottleneck in the drug discovery pipeline for this class of therapeutics," said Pieter Dorrestein, assistant professor in the Skaggs School of Pharmacy and Pharmaceutical Sciences and the Departments of Pharmacology, Chemistry and Biochemistry.

"We have shown a way to quickly, structurally characterize non-ribosomal peptides. Our next step is to replicate our findings with newly discovered, potentially therapeutic peptides," he added.

The algorithms make use of data on the weights of the various NRP ring fragments collected at each stage using mass spectrometry.

"Our Recomb 2008 paper represents the first demonstration of de novo sequencing of nonribosomal peptides. Without knowing the structure of the original compound, we can determine it," said Pavel Pevzner, computer science professor, co-author and director of UCSD's Centre for Algorithmic and Systems Biology.

The study was presented at RECOMB 2008 (Research in Computational Molecular Biology) on March 31 in Singapore.