Flu virus key machine: First complete view of structure revealed

The structure, obtained by scientists at the European Molecular Biology Laboratory (EMBL) in Grenoble, France, allows researchers to finally understand how the machine works as a whole. Published in two papers in Nature, the work could prove instrumental in designing new drugs to treat serious flu infections and combat flu pandemics. The machine in question, the influenza virus polymerase, carries out two vital tasks for the virus. It makes copies of the virus' genetic material. The viral RNA to package into new viruses that can infect other cells; and it reads out the instructions in that genetic material to make viral messenger RNA, which directs the infected cell to produce the proteins the virus needs. Scientistsincluding Cusack and collaborators had been able to determine the structure of several parts of the polymerase in the past."The flu polymerase was discovered 40 years ago, so there are hundreds of papers out there trying to fathom how it works. But only now that we have the complete structure can we really begin to understand it," says Stephen Cusack, head of EMBL Grenoble, who led the work.

The complete structure allows researchers to understand how the polymerase uses host cell RNA (red) to kick-start the production of viral messenger RNA.

Using X-ray crystallography, performed at the European Synchrotron Radiation Facility (ESRF) in Grenoble, Cusack and colleagues were able to determine the atomic structure of the whole polymerase from two strains of influenza: influenza B, one of the strains that cause seasonal flu in humans, but which evolves slowly and therefore isn't considered a pandemic threat; and the strain of influenza A. The fast-evolving strain that affects humans, birds and other animals and can cause pandemics that infects bats.

"The high-intensity X-ray beamlines at the ESRF, equipped with state-of-the-art Dectris detectors, were crucial for getting high quality crystallographic data from the weakly diffracting and radiation sensitive crystals of the large polymerase complex," says Cusack.

The structures reveal how the polymerase specifically recognises and binds to the viral RNA, rather than just any available RNA, and how that binding activates the machine. They also show that the three component proteins that make up the polymerase are very intertwined, which explains why it has been very difficult to piece together how this machine works based on structures of individual parts. 

Although the structures of both viruses' polymerases were very similar, the scientists found one key difference, which showed that one part of the machine can swivel around to a large degree. That ability to swivel explains exactly how the polymerase uses host cell RNA to kick-start the production of viral proteins. The swivelling component takes the necessary piece of host cell RNA and directs it into a slot leading to

the machine's heart, where it triggers the production of viral messenger RNA.

Now that they know exactly where each atom fits in this key viral machine, researchers aiming to design drugs to stop influenza in its tracks have a much wider range of potential targets at their disposal -- like would-be saboteurs who gain access to the whole production plant instead of just sneaking looks through the windows. And because this is such a fundamental piece of the viral machinery, not only are the versions in the different influenza strains very similar to each other, but they also hold many similarities to their counterparts in related viruses such as lassa, hanta, rabies or ebola.

The EMBL scientists aim to explore the new insights this structure provides for drug design, as well as continuing to try to determine the structure of the human version of influenza A, because although the bat version is close enough that it already provides remarkable insights, ultimately fine-tuning drugs for treating people would benefit from/require knowledge of the version of the virus that infects humans. And, since this viral machine has to be flexible and change shape to carry out its different tasks, Cusack and colleagues also want to get further snapshots of the polymerase in different states.

Rheumatoid arthritis (RA) research shows potential of large-scale genetic studies for drug discovery

The results of the largest international study to date into the genetic basis of rheumatoid arthritis shed light on the biology of the disease and provide evidence that large-scale genetic studies can assist in the identification of new drugs for complex disorders such as rheumatoid arthritis.

The study, conducted by Dr. Robert M. Plenge from the Harvard Medical School and the Broad Institute in the USA and Dr. Yukinori Okada from the RIKEN Center for Integrative Medical Sciences in Japan, collaborating with colleagues from 70 institutions worldwide, is published in the journal Nature.

Genome-wide association studies are a method employed by scientists to identify the genes contributing to human disease. The current Nature study is the first to demonstrate that integrating the information provided by genome-wide association studies with existing datasets of genomic and biological information, such as drug targets, can assist in the discovery of drugs to cure human disease.

Rheumatoid arthritis is an autoimmune disease leading to inflammation of the joints and affecting 0.5-1% of adults in the developed world. The disease is thought to be caused by a complex combination of genetic and environmental factors and several genes have been shown to be associated with the disease. However, most of the findings were based on single population studies, and no large-scale trans-ethnic study had been carried out to date.

Figure a) Showing RA

Figure b) Showing Bioinformatics Process for Drug Discovery of RA

The international team performed a genome-wide association study meta-analysis on a total of over 100,000 subjects of European and Asian descent -- 29,880 rheumatoid arthritis patients and 73,758 controls -- by analysing around 10 million genetic variants called single nucleotide polymorphism (SNPs). They identified 42 new regions in the genome (loci) that are associated with rheumatoid arthritis, bringing the total number of known rheumatoid arthritis loci to 101.

By conducting bioinformatics studies integrating existing datasets with this new information, the researchers were able to pinpoint 98 genes in these 101 loci that could potentially contribute to the onset of rheumatoid arthritis. By integrating their findings with existing drug databases they demonstrate that these genes indeed possess many overlapping regions with the genes targeted by approved rheumatoid arthritis drugs -- although this wasn't known when the drugs were developed. The team identifies existing drugs used to treat cancer that also target rheumatoid arthritis genes and could potentially be used as therapy for the disease, such as CDK4/6 inhibitors.

The bioinformatics study also reveals that there is significant overlap between the genes involved in rheumatoid arthritis, human primary immunodeficiency disorders and blood cancers.

"This study sheds light on the fundamental genes, pathways and cell types that contribute to the onset of rheumatoid arthritis and provides evidence that the genetics of rheumatoid arthritis can provide important information for drug discovery," conclude the authors.