The research findings are significant in view of the HIV virus's ability to elude specifically designed medicines by mutating rapidly. The new model, developed under the supervision of the University of Amsterdam's (UvA) Computational Science professor Peter Sloot, provides insight into the effects of these mutations on HIV medication. This will allow for medicines to be more effectively tailored to individual patients, as it improves our insight into resistance against specific medications.
The findings are the result of a complex long-term collaboration between virologists, doctors, information specialists, mathematicians and computational scientists. In order to understand how medicines block the HIV virus in human cells, the scientists developed new computer simulation models to study the infection at the molecular and cellular levels.
The vast computing capacity needed to make such precise calculations required the combined power of supercomputers in Europe and the United States. The resulting calculations of the medicine's "binding affinity" with the various viral proteins can be used to determine its effectiveness in individual patients. The computer simulations also provide insight into the way in which the patient-specific virus penetrates the cell as well as the immune system's subsequent response. The development of new computer algorithms allowed Peter Sloot's research group to link this information to existing medical databases, resulting in a unique method of determining the most effective HIV medication for each individual patient.
The new computer simulations developed as part of the ViroLab project were successfully tested at five European university hospitals. A follow-up study is currently being conducted to assess how these computer simulations can help predict the global spread of the HIV virus. This involves linking molecular data with sexual contact network models and information from the medical literature and patient databases.