LA JOLLA, Calif.— Researchers have invented computational tools to decode and rapidly determine whether natural compounds collected in oceans and forests are new—or if these pharmaceutically promising compounds have already been described and are therefore not patentable.
This University of California, San Diego advance will finally enable scientists to rapidly characterize ring-shaped nonribosomal peptides (NRPs)—a class of natural compounds of intense interest due to their potential to yield or inspire new pharmaceuticals. The study will be published in the July 13 online issue of
Nature Methods.
“These advances will speed the process by which we discover and describe new and biologically active molecules from organisms such as marine cyanobacteria, also known as blue-green algae. This, in turn, will accelerate the timeline for bringing new experimental therapies into clinical application,” said William Gerwick, an author on the paper and a professor with the UC San Diego Scripps Institution of Oceanography Center for Marine Biotechnology and Biomedicine and the UCSD Skaggs School of Pharmacy and Pharmaceutical Sciences.
Nonribosomal peptides (NRPs) often serve as chemical defenses for the bacteria that manufacture them. Starting from penicillin, NRPs have an unparalleled track record in pharmacology: most anti-cancer and anti-microbial agents are natural products or their derivatives. However, it is currently difficult, time-consuming and costly to determine the molecular structure of NRPs which, by definition, are not directly inscribed in the genomes of the organisms that produce them.
“NRPs are one of the last bastions of pharmacologically important biological compounds that remain virtually untouched by computational research. As a result, it is currently one of the most painfully slow processes, it is a real bottleneck that we have now removed,” said Pavel Pevzner, a computer science professor at UC San Diego’s Jacobs School of Engineering and the corresponding author on the Nature Methods paper.
Researchers can now separate known compounds from those that are unknown.
“If I collect 1,000 ocean compounds, why waste time with compounds that are already known or patented?” added Nuno Bandeira, co-lead author on the paper, director of UC San Diego’s Center for Computational Mass Spectrometry (CCMS) and a researcher at the UC San Diego division of Calit2, the California Institute of Telecommunications and Information Technology.
“Our algorithms can tell natural product researchers what their compounds are. Manual annotations should be something of the past,” said Julio Ng, a co-lead author on the
Nature Methods paper and a doctoral student in Bioinformatics at UC San Diego.
Two complementary processes are used to glean insights from data generated from the mass spectrometers that break the cyclic peptides into smaller and smaller linear pieces. First, the authors present new algorithms that computers use to piece these peptide fragments back together in order to determine the chemical structure of a cyclic NRP. This is called “De Novo sequencing of NRPs.” Second, the researchers created “dereplication” tools for moving the other direction: taking the chemical structures of known NRPs and other related information and determining what the data signature would look like if a mass spectrometer had blown the compound part.
By using these two approaches, the researchers have created tools that enable researchers to both characterize the compound they have isolated and check to see if it, or something similar, has been previously described. With dereplication, researchers can leverage known information and are not forced to start from scratch each time a new compound needs to be identified.
“This new study has shown that marine cyanobacteria are incredible sources of new molecules that may have medical value, especially in cancer, infectious diseases and neurological disorders,” said Gerwick.