Predicting viral drug resistance is a major medical concern. The importance of this problem stimulates the continuous development of experimental and new computational approaches. The use of computational approaches allows researchers to increase the effectiveness of therapy and to reduce the time and cost involved when prescribed antiretroviral therapy is ineffective in the treatment of human immunodeficiency virus type 1 (HIV-1) infection.

This video demonstrates the use of the web service to predict HIV drug resistance. The input data are amino acid sequences of HIV-1 reverse transcriptase and protease in FASTA format. The class of enzyme inhibitor to be used for predicting drug resistance should be selected from the Drug's type box. The results are provided using the 'Get results' button. The results are provided as a table with the sequence identifiers followed by the drug name and the drug sensitivity information in the form of two variants "sensitive" or "resistant".