Accessory mutations balance the marginal stability of the HIV-1 protease in drug resistance

Premature Activation of the HIV-1 Protease Is Influenced by Polymorphisms in the Hinge Region

HIV-1 protease inhibitors are an essential component of antiretroviral therapy. However, drug resistance is a pervasive issue motivating a persistent search for novel therapies. Recent reports found that when protease activates within the host cell's cytosol, it facilitates the pyroptotic killing of infected cells. This has led to speculation that promoting protease activation, rather than inhibiting it, could help to eradicate infected cells and potentially cure HIV-1 infection. Here, we used a nanoscale flow cytometry-based assay to characterize protease resistance mutations and polymorphisms. We quantified protease activity, viral concentration, and premature protease activation and confirmed previous findings that major resistance mutations generally destabilize the protease structure. Intriguingly, we found evidence that common polymorphisms in the hinge domain of protease can influence its susceptibility to premature activation. This suggests that viral heterogeneity could pose a considerable challenge for therapeutic strategies aimed at inducing premature protease activation in the future.

The evolution of the HIV-1 protease folding stability

The evolution of structural proteins is generally constrained by the folding stability. However, little is known about the particular capacity of viral proteins to accommodate mutations that can potentially affect the protein stability and, in general, the evolution of the protein stability over time. As an illustrative model case, here, we investigated the evolution of the stability of the human immunodeficiency virus (HIV-1) protease (PR), which is a common HIV-1 drug target, under diverse evolutionary scenarios that include (1) intra-host virus evolution in a cohort of seventy-five patients sampled over time, (2) intra-host virus evolution sampled before and after specific PR-based treatments, and (3) inter-host evolution considering extant and ancestral (reconstructed) PR sequences from diverse HIV-1 subtypes. We also investigated the specific influence of currently known HIV-1 PR resistance mutations on the PR folding stability. We found that the HIV-1 PR stability fluctuated over time within a constant and wide range in any studied evolutionary scenario, accommodating multiple mutations that partially affected the stability while maintaining activity. We did not identify relationships between change of PR stability and diverse clinical parameters such as viral load, CD4⁺ T-cell counts, and a surrogate of time from infection. Counterintuitively, we predicted that nearly half of the studied HIV-1 PR resistance mutations do not significantly decrease stability, which, together with compensatory mutations, would allow the protein to adapt without requiring dramatic stability changes. We conclude that the HIV-1 PR presents a wide structural plasticity to acquire molecular adaptations without affecting the overall evolution of stability.

Viral proteases as therapeutic targets

Some medically important viruses-including retroviruses, flaviviruses, coronaviruses, and herpesviruses-code for a protease, which is indispensable for viral maturation and pathogenesis. Viral protease inhibitors have become an important class of antiviral drugs. Development of the first-in-class viral protease inhibitor saquinavir, which targets HIV protease, started a new era in the treatment of chronic viral diseases. Combining several drugs that target different steps of the viral life cycle enables use of lower doses of individual drugs (and thereby reduction of potential side effects, which frequently occur during long term therapy) and reduces drug-resistance development. Currently, several HIV and HCV protease inhibitors are routinely used in clinical practice. In addition, a drug including an inhibitor of SARS-CoV-2 main protease, nirmatrelvir (co-administered with a pharmacokinetic booster ritonavir as Paxlovid®), was recently authorized for emergency use. This review summarizes the basic features of the proteases of human immunodeficiency virus (HIV), hepatitis C virus (HCV), and SARS-CoV-2 and discusses the properties of their inhibitors in clinical use, as well as development of compounds in the pipeline.

Elasticity-Associated Functionality and Inhibition of the HIV Protease

HIV protease plays a critical role in the life cycle of the virus through the generation of mature and infectious virions. Detailed knowledge of the structure of the enzyme and its substrate has led to the development of protease inhibitors. However, the development of resistance to all currently available protease inhibitors has contributed greatly to the decreased success of antiretroviral therapy. When therapy failure occurs, multiple mutations are found within the protease sequence starting with primary mutations, which directly impact inhibitor binding, which can also negatively impact viral fitness and replicative capacity by decreasing the binding affinity of the natural substrates to the protease. As such, secondary mutations which are located outside of the active site region accumulate to compensate for the recurrently deleterious effects of primary mutations. However, the resistance mechanism of these secondary mutations is not well understood, but what is known is that these secondary mutations contribute to resistance in one of two ways, either through increasing the energetic penalty associated with bringing the protease into the closed conformation, or, through decreasing the stability of the protein/drug complex in a manner that increases the dissociation rate of the drug, leading to diminished inhibition. As a result, the elasticity of the enzyme-substrate complex has been implicated in the successful recognition and catalysis of the substrates which may be inferred to suggest that the elasticity of the enzyme/drug complex plays a role in resistance. A realistic representation of the dynamic nature of the protease may provide a more powerful tool in structure-based drug design algorithms.

Acquired HIV-1 Protease Conformational Flexibility Associated with Lopinavir Failure May Shape the Outcome of Darunavir Therapy after Antiretroviral Therapy Switch

Understanding the underlying molecular interaction during a therapy switch from lopinavir (LPV) to darunavir (DRV) is essential to achieve long-term virological suppression. We investigated the kinetic and structural characteristics of multidrug-resistant South African HIV-1 subtype C protease (HIV-1 PR) during therapy switch from LPV to DRV using enzyme activity and inhibition assay, fluorescence spectroscopy, and molecular dynamic simulation. The HIV-1 protease variants were from clinical isolates with a combination of drug resistance mutations; MUT-1 (M46I, I54V, V82A, and L10F), MUT-2 (M46I, I54V, L76V, V82A, L10F, and L33F), and MUT-3 (M46I, I54V, L76V, V82A, L90M, and F53L). Enzyme kinetics analysis shows an association between increased relative resistance to LPV and DRV with the progressive decrease in the mutant HIV-1 PR variants' catalytic efficiency. A direct relationship between high-level resistance to LPV and intermediate resistance to DRV with intrinsic changes in the three-dimensional structure of the mutant HIV-1 PR as a function of the multidrug-resistance mutation was observed. In silico analysis attributed these structural adjustments to the multidrug-resistance mutations affecting the LPV and DRV binding landscape. Though DRV showed superiority to LPV, as a lower concentration was needed to inhibit the HIV-1 PR variants, the inherent structural changes resulting from mutations selected during LPV therapy may dynamically shape the DRV treatment outcome after the therapy switch.

Evolution of drug resistance in HIV protease

BACKGROUND

Drug resistance is a critical problem limiting effective antiviral therapy for HIV/AIDS. Computational techniques for predicting drug resistance profiles from genomic data can accelerate the appropriate choice of therapy. These techniques can also be used to identify protease mutants for experimental studies of resistance and thereby assist in the development of next-generation therapies. Few studies, however, have assessed the evolution of resistance from genotype-phenotype data.

RESULTS

The machine learning produced highly accurate and robust classification of resistance to HIV protease inhibitors. Genotype data were mapped to the enzyme structure and encoded using Delaunay triangulation. Estimates of evolutionary relationships, based on this encoding, and using Minimum Spanning Trees, showed clusters of mutations that closely resemble the wild type. These clusters appear to evolve uniquely to more resistant phenotypes.

CONCLUSIONS

Using the triangulation metric and spanning trees results in paths that are consistent with evolutionary theory. The majority of the paths show bifurcation, namely they switch once from non-resistant to resistant or from resistant to non-resistant. Paths that lose resistance almost uniformly have far lower levels of resistance than those which either gain resistance or are stable. This strongly suggests that selection for stability in the face of a rapid rate of mutation is as important as selection for resistance in retroviral systems.