GPUs simulate molecular processes during swine flu drug treatment

Professor Adrian Mulholland and Dr Christopher Woods from Bristol's School of Chemistry, together with colleagues in Thailand, used graphics processing units (GPUs) to simulate the molecular processes that take place when these drugs are used to treat the H1N1-2009 strain of influenza - commonly known as 'swine flu'.

Their results, published today [29 May] in Biochemistry, provide new insight that could lead to the development of the next generation of antiviral treatments for flu.

H1N1-2009 is a new, highly adaptive virus derived from different gene segments of swine, avian, and human influenza. Within a few months of its appearance in early 2009, the H1N1-2009 strain caused the first flu pandemic of the 21st-century.

The antiviral drugs Relenza and Tamiflu, which target the neuraminidase (NA) enzyme, successfully treated the infection but widespread use of these drugs has led to a series of mutations in NA that reduce the drugs' effectiveness.

Clinical studies indicate that the double mutant of swine flu NA known as IRHY2 reduced the effectiveness of Relenza by 21 times and Tamiflu by 12,374 times - that is, to the point where it has become an ineffective treatment.

To understand why the effectiveness of Relenza and Tamiflu is so seriously reduced by the occurrence of this mutation, the researchers performed long-timescale molecular dynamics (MD) simulations using GPUs.

Professor Mulholland said: "Our simulations showed that IRHY became resistant to Tamiflu due to the loss of key hydrogen bonds between the drug and residues in a part of the NA's structure known as the '150-loop'.

"This allowed NA to change from a closed to an open conformation. Tamiflu binds weakly with the open conformation due to poor electrostatic interactions between the drug and the active site, thus rendering the drug ineffective."

These findings suggest that drug resistance could be overcome by increasing hydrogen bond interactions between NA inhibitors and residues in the 150-loop, with the aim of maintaining the closed conformation.

The research was supported by the Engineering and Physical Sciences Research Council (EPSRC) through a Leadership Fellowship grant to Professor Mulholland and a software development grant to Professor Mulholland and Dr Woods.