Molecular Determinants of Epistasis in HIV-1 Protease: Elucidating the Interdependence of L89V and L90M Mutations in Resistance

Abstract

Protease inhibitors have the highest potency among antiviral therapies against HIV-1 infections, yet the virus can evolve resistance. Darunavir (DRV), currently the most potent Food and Drug Administration-approved protease inhibitor, retains potency against single-site mutations. However, complex combinations of mutations can confer resistance to DRV. While the interdependence between mutations within HIV-1 protease is key for inhibitor potency, the molecular mechanisms that underlie this control remain largely unknown. In this study, we investigated the interdependence between the L89V and L90M mutations and their effects on DRV binding. These two mutations have been reported to be positively correlated with one another in HIV-1 patient-derived protease isolates, with the presence of one mutation making the probability of the occurrence of the second mutation more likely. The focus of our investigation is a patient-derived isolate, with 24 mutations that we call “KY”; this variant includes the L89V and L90M mutations. Three additional KY variants with back-mutations, KY­(V89L), KY­(M90L), and the KY­(V89L/M90L) double mutation, were used to experimentally assess the individual and combined effects of these mutations on DRV inhibition and substrate processing. The enzymatic assays revealed that the KY­(V89L) variant, with methionine at residue 90, is highly resistant, but its catalytic function is compromised. When a leucine to valine mutation at residue 89 is present simultaneously with the L90M mutation, a rescue of catalytic efficiency is observed. Molecular dynamics simulations of these DRV-bound protease variants reveal how the L90M mutation induces structural changes throughout the enzyme that undermine the binding interactions.

Viral proteases: Structure, mechanism and inhibition

“…1 F). [7] , [8] , [9] , [10] , [11] , [12] , [13] , [14] , [15] , [16] , [17] , [18] , [19] . Recent studies combining parallel molecular dynamics simulations and machine learning have provided insights into how remote changes can confer resistance and which interactions are most indicative of these changes [7] , [20] .…”

Multiple Molecular Dynamics Simulations and Energy Analysis Unravel the Dynamic Properties and Binding Mechanism of Mutants HIV-1 Protease with DRV and CA-p2

“…Human immunodeficiency virus (HIV) destroys the immune system, bringing about AIDS ( 1 – 3 ). At present, highly active antiretroviral therapy (HAART) consisting of several small molecule drugs is currently the most effective treatment method ( 4 , 5 ). At different stages of its life cycle, the drugs can target and attack the virus, thereby preventing its replication and reducing damage to the immune system ( 6 , 7 ).…”

Deciphering Complex Mechanisms of Resistance and Loss of Potency through Coupled Molecular Dynamics and Machine Learning

“…Resistance to DRV still emerges through accumulation of multiple mutations both proximal and distal from the active site. [11][12][13][14] Elucidating the resistance mechanism for very potent inhibitors, such as the HIV-1 protease inhibitor DRV, provides insights into how amino acid substitutions alter the structure, dynamics and function of a therapeutic target. 15,16 However the molecular mechanisms by which mutations, in particular those distal from the active site, confer resistance remains elusive.…”

“…The success of this strategy has been demonstrated not only in HIV-1 protease but also in other rapidly evolving viral targets. , The most recently FDA approved HIV-1 protease inhibitor darunavir (DRV) adheres to this strategy, resulting in a remarkably high barrier to resistance. Resistance to DRV still emerges through accumulation of multiple mutations both proximal and distal from the active site. − Elucidating the resistance mechanism for very potent inhibitors, such as the HIV-1 protease inhibitor DRV, provides insights into how amino acid substitutions alter the structure, dynamics, and function of a therapeutic target. , However, the molecular mechanisms by which combinations of mutations, in particular those involving mutations distal from the active site, confer resistance remain elusive.…”