Mar 31 2008, 12:26 AM EST
EUREKALERT
Contact: Daniel Kane
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Determining the structure of unknown natural compounds is a slow and expensive part of drug screening and development but this may now change thanks to a new combination of experimental and computational protocols developed at the University of California, San Diego and presented at RECOMB 2008 (Research in Computational Molecular Biology) on March 31 in Singapore.
UC San Diego researchers have devised a way to 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. This advance may assist drug discovery researchers who need to know as much as possible as quickly as possible about the natural products with antibiotic, antiviral and other pharmacologically interesting properties that they are probing.
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.
To address this issue, UCSD researchers developed a quick, automated and inexpensive way to determine the structure of NRPs through an innovative collaboration between mass spectrometry experts at the UCSD Skaggs School of Pharmacy and Pharmaceutical Sciences and bioinformatics experts and computer scientists from UCSDs Jacobs School of Engineering.
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If you imagine the structure of an NRP as 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.
In addition to screening for new drugs and studying natural compounds, the authors say this work may aid biosynthetic engineering efforts to reprogram E. coli strains in order to turn them into NRP assembly lines, now that researchers have a rapid method for characterizing the resulting NRPs.
NRPs such as
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