The UK NGS played a key role in helping scientists simulate the efficacy of an HIV drug in blocking a key protein used by the virus. The experiment, by Peter Coveney, Ileana Stoica and Kashif Sadiq from the UCL Department of Chemistry, performed a sequence of simulation steps across the UK NGS and US TeraGrid.
The team ran a large number of simulations to predict how strongly the drug saquinavir would bind to three resistant mutants of HIV-1 protease and its original strain – or “wild-type” protease (one of the proteins produced by the virus to propagate itself). Saquinavir is a known inhibitor of HIV-1 protease as it blocks the maturation step of the HIV life cycle.
Several drugs have the ability to inhibit HIV-1 protease, but doctors currently have no direct way to match the right drug to the right strain, as the virus rapidly mutates in each patient to create a unique version. A long-held goal of physicians is to replace this “shotgun” strategy with individualized, patient-specific treatments custom-tailored to each person’s unique genotype. Peter Coveney said: “This study represents a first step towards the ultimate goal of ‘on-demand’ medical computing, where doctors could one day ‘borrow’ supercomputing time from the national grid to make critical decisions on life-saving treatments.”
Note: This research used UKLight between London and Chicago, leveraging the National Science Foundation’s TransLight/StarLight’s investment in transatlantic international connectivity.
URL:
Collaborators:
USA:
TeraGrid
UK:
University College London (UCL); National Grid Service (NGS)
