Hepatitis C Therapeutics
The hepatitis C virus (HCV) genome consists of a small enveloped single-stranded RNA with a single open reading frame that produces one protein product, which is subsequently processed into active proteins. Its 5´ untranslated region (UTR) possesses an internal ribosome entry site (IRES) with a specific secondary structure that facilitates viral protein synthesis.
Jennifer A. Doudna, Ph.D., Howard Hughes Medical Institute investigator and professor of molecular and cell biology and chemistry at the University of California, Berkeley, studies HCV protein synthesis. “We have performed mutational analyses and determined crystallographic structures of functional parts of the IRES. We want to understand how the virus uses the IRES to control protein expression.
“The IRES contains a characteristic structure called a pseudoknot. If we can understand how this piece engages the ribosome, we may be able to develop a therapeutic to block that process.”
To better define the ribosomal binding site of the IRES, Dr. Doudna and colleagues created a series of RNA mutants of the IRES domain and tested their ability to interact with ribosomes.
“We utilized a rabbit reticulocyte lysate system to assess the effect of our mutants on translation.” Her laboratory also performed ribosomal toeprinting experiments that monitor how the viral RNA structure changes after binding the ribosome. The assay is based on inhibition of nucleotide elongation using reverse transcription.
“We found the pseudoknot conformation positions the RNA into the binding cleft of the ribosome and that the global structure contributes to its overall activity. Based on these findings, we next performed proof-of-principle experiments utilizing antisense 2´-O-methyl oligonucleotides to see if we could block this activity. Three of four 2´-O-methyl oligos showed potent inhibition of viral protein synthesis.”
Dr. Doudna’s laboratory is now also pursuing small molecule inhibitors that bind to the pseudoknot. “As we better understand how its structure contributes to its function, we will be looking at more targeted compounds to interfere with the pseudoknot.”
Most RNAs undergo extensive folding to form sophisticated based-paired secondary structures that become an integral part of cellular gene-expression machinery. Accurately deducing these structures is no small matter, yet this is a critical aspect of understanding structure/function.
“Structure is function,” noted Bruce A. Shapiro, Ph.D., principle investigator, Center for Cancer Research Nanobiology Program, National Cancer Institute-Frederick. “Predicting RNA structure in a rapid and accurate way remains a challenge.
“Several years ago, Kevin Weeks and colleagues at the University of North Carolina, Chapel Hill developed a methodology called SHAPE (Selective 2´-Hydroxyl Acylation analyzed by Primer Extension). This method provides quantitative nucleotide resolution data that can be utilized to determine RNA secondary structure.”
The problem, according to Dr. Shapiro, is how to interpret the data. “A low signal indicates that there is base-pairing, but it doesn’t disclose the base-pairing partner or the type of base pair.
“In order to better understand the complexities of SHAPE, we utilized seven RNAs taken from the Protein Data Bank whose structure had already been solved. We prepared the RNAs by in vitro transcription, and folded the RNA into its native structure. This was followed by chemical modification of the RNAs with N-methyl-7-nitroisatoic anhydride (NMIA).
“Subsequently these sequences were subjected to primer extension. Due to stops in primer extension caused by NMIA-modified unpaired nucleotides, one is able to obtain bands on gels indicating the positions of these stops. The intensities of these bands are then converted to SHAPE values.”
Dr. Shapiro and his colleagues arrived at several conclusions. “First, the SHAPE signal is impacted to a large extent by the base-pairing state of a residue. We also found significant correlations with base-pair stacking. By comparing the known structures with the SHAPE data, we developed a method that converts raw SHAPE values into probabilities of base pairing.”
Overall the new methodology enhances understanding of the SHAPE methodology and could be particularly important for pharmaceutical applications.
“One could imagine applying this enhanced SHAPE analysis to help in the development of therapeutics that target specific RNAs that are involved in disease processes. Although we are still developing predictive methods, ultimately such probabilistic models will aid the interpretation of RNA structure for basic science as well as pharmaceutical development.”