Prediction of HIV integrase resistance mutation using in silico approaches.

The Antiretroviral Therapy (ART) has been providing better treatment for the Human Immunodeficiency Virus 1 (HIV) infection, by reducing its viral load to undetectable levels and recovering the immune system. However, new HIV mutations could induce drug resistance to ART, increasing the viral load and disruption of immune system. One of these drugs is Dolutegravir (DTG), which inhibits HIV integrase (INT) activity. Our objective was to predict novel HIV mutations related to DTG resistance using in silico approaches in order to stablish a framework of searching for new HIV drug-resistant mutations. To this end, we modelled the INT structure and produced a mutational profile to investigate hotspots that may affect INT. Being the Y226K mutation the most frequent (0.3) and with a higher ΔΔG (+2.07), we selected to test the framework. To ratify the impact of Y226K, we docked the mutant INT with the DTG and compared the results with the Wild Type (WT) with known drug-resistant mutations. Moreover, we performed molecular dynamics simulations and calculated the binding energy along the time-course. When we compared the energies of the systems, the Y226K complex showed less binding affinity (ΔΔG = 104.88) than the other mutated complexes compared with the WT, the Y226K complex showed even less binding affinity (ΔΔG = 104.88). This variant somehow impedes the attachment of DTG to INT, indicating this mutant as possible resistance mutation.