Short communication: Phenotypic protease inhibitor resistance and cross-resistance in the clinic from 2006 to 2008 and mutational prevalences in HIV from patients with discordant tipranavir and darunavir susceptibility phenotypes

Inherently interpretable position-aware convolutional motif kernel networks for biological sequencing data

Artificial neural networks show promising performance in detecting correlations within data that are associated with specific outcomes. However, the black-box nature of such models can hinder the knowledge advancement in research fields by obscuring the decision process and preventing scientist to fully conceptualize predicted outcomes. Furthermore, domain experts like healthcare providers need explainable predictions to assess whether a predicted outcome can be trusted in high stakes scenarios and to help them integrating a model into their own routine. Therefore, interpretable models play a crucial role for the incorporation of machine learning into high stakes scenarios like healthcare. In this paper we introduce Convolutional Motif Kernel Networks, a neural network architecture that involves learning a feature representation within a subspace of the reproducing kernel Hilbert space of the position-aware motif kernel function. The resulting model enables to directly interpret and evaluate prediction outcomes by providing a biologically and medically meaningful explanation without the need for additional post-hoc analysis. We show that our model is able to robustly learn on small datasets and reaches state-of-the-art performance on relevant healthcare prediction tasks. Our proposed method can be utilized on DNA and protein sequences. Furthermore, we show that the proposed method learns biologically meaningful concepts directly from data using an end-to-end learning scheme.

Protease Inhibitors for the Treatment of HIV/AIDS: Recent Advances and Future Challenges

Acquired Immunodeficiency Syndrome (AIDS) is a chronic disease characterized by multiple life-threatening illnesses caused by a retro-virus, Human Immunodeficiency Virus (HIV). HIV infection slowly destroys the immune system and increases the risk of various other infections and diseases. Although, there is no immediate cure for HIV infection/AIDS, several drugs targeting various cruxes of HIV infection are used to slow down the progress of the disease and to boost the immune system. One of the key therapeutic strategies is Highly Active Antiretroviral Therapy (HAART) or ' AIDS cocktail' in a general sense, which is a customized combination of anti-retroviral drugs designed to combat the HIV infection. Since HAART's inception in 1995, this treatment was found to be effective in improving the life expectancy of HIV patients over two decades. Among various classes of HAART treatment regimen, Protease Inhibitors (PIs) are known to be widely used as a major component and found to be effective in treating HIV infection/AIDS. For the past several years, a variety of protease inhibitors have been reported. This review outlines the drug design strategies of PIs, chemical and pharmacological characteristics of some mechanism-based inhibitors, summarizes the recent developments in small molecule based drug discovery with HIV protease as a drug target. Further discussed are the pharmacology, PI drug resistance on HIV PR, adverse effects of HIV PIs and challenges/impediments in the successful application of HIV PIs as an important class of drugs in HAART regimen for the effective treatment of AIDS.

Consistent Prediction of Mutation Effect on Drug Binding in HIV-1 Protease Using Alchemical Calculations

Despite a large number of antiretroviral drugs targeting HIV-1 protease for inhibition, mutations in this protein during the course of patient treatment can render them inefficient. This emerging resistance inspired numerous computational studies of the HIV-1 protease aimed at predicting the effect of mutations on drug binding in terms of free binding energy Δ G, as well as in mechanistic terms. In this study, we analyze ten different protease-inhibitor complexes carrying major resistance-associated mutations (RAMs) G48V, I50V, and L90M using molecular dynamics simulations. We demonstrate that alchemical free energy calculations can consistently predict the effect of mutations on drug binding. By explicitly probing different protonation states of the catalytic aspartic dyad, we reveal the importance of the correct choice of protonation state for the accuracy of the result. We also provide insight into how different mutations affect drug binding in their specific ways, with the unifying theme of how all of them affect the crucial drug binding regions of the protease.

Elucidating the Interdependence of Drug Resistance from Combinations of Mutations

HIV-1 protease is responsible for the cleavage of 12 nonhomologous sites within the Gag and Gag-Pro-Pol polyproteins in the viral genome. Under the selective pressure of protease inhibition, the virus evolves mutations within (primary) and outside of (secondary) the active site, allowing the protease to process substrates while simultaneously countering inhibition. The primary protease mutations impede inhibitor binding directly, while the secondary mutations are considered accessory mutations that compensate for a loss in fitness. However, the role of secondary mutations in conferring drug resistance remains a largely unresolved topic. We have shown previously that mutations distal to the active site are able to perturb binding of darunavir (DRV) via the protein's internal hydrogen-bonding network. In this study, we show that mutations distal to the active site, regardless of context, can play an interdependent role in drug resistance. Applying eigenvalue decomposition to collections of hydrogen bonding and van der Waals interactions from a series of molecular dynamics simulations of 15 diverse HIV-1 protease variants, we identify sites in the protease where amino acid substitutions lead to perturbations in nonbonded interactions with DRV and/or the hydrogen-bonding network of the protease itself. While primary mutations are known to drive resistance in HIV-1 protease, these findings delineate the significant contributions of accessory mutations to resistance. Identifying the variable positions in the protease that have the greatest impact on drug resistance may aid in future structure-based design of inhibitors.

Unique Flap Conformation in an HIV-1 Protease with High-Level Darunavir Resistance

Darunavir (DRV) is one of the most powerful protease inhibitors (PIs) for treating human immunodeficiency virus type-1 (HIV-1) infection and presents a high genetic barrier to the generation of resistant viruses. However, DRV-resistant HIV-1 infrequently emerges from viruses exhibiting resistance to other protease inhibitors. To address this resistance, researchers have gathered genetic information on DRV resistance. In contrast, few structural insights into the mechanism underlying DRV resistance are available. To elucidate this mechanism, we determined the crystal structure of the ligand-free state of a protease with high-level DRV resistance and six DRV resistance-associated mutations (including I47V and I50V), which we generated by in vitro selection. This crystal structure showed a unique curling conformation at the flap regions that was not found in the previously reported ligand-free protease structures. Molecular dynamics simulations indicated that the curled flap conformation altered the flap dynamics. These results suggest that the preference for a unique flap conformation influences DRV binding. These results provide new structural insights into elucidating the molecular mechanism of DRV resistance and aid to develop PIs effective against DRV-resistant viruses.

Prototypical Recombinant Multi-Protease-Inhibitor-Resistant Infectious Molecular Clones of Human Immunodeficiency Virus Type 1

The many genetic manifestations of HIV-1 protease inhibitor (PI) resistance present challenges to research into the mechanisms of PI resistance and the assessment of new PIs. To address these challenges, we created a panel of recombinant multi-PI-resistant infectious molecular clones designed to represent the spectrum of clinically relevant multi-PI-resistant viruses. To assess the representativeness of this panel, we examined the sequences of the panel's viruses in the context of a correlation network of PI resistance amino acid substitutions in sequences from more than 10,000 patients. The panel of recombinant infectious molecular clones comprised 29 of 41 study-defined PI resistance amino acid substitutions and 23 of the 27 tightest amino acid substitution clusters. Based on their phenotypic properties, the clones were classified into four groups with increasing cross-resistance to the PIs most commonly used for salvage therapy: lopinavir (LPV), tipranavir (TPV), and darunavir (DRV). The panel of recombinant infectious molecular clones has been made available without restriction through the NIH AIDS Research and Reference Reagent Program. The public availability of the panel makes it possible to compare the inhibitory activities of different PIs with one another. The diversity of the panel and the high-level PI resistance of its clones suggest that investigational PIs active against the clones in this panel will retain antiviral activity against most if not all clinically relevant PI-resistant viruses.

HIV-1 antiretroviral resistance: scientific principles and clinical applications

The efficacy of an antiretroviral (ARV) treatment regimen depends on the activity of the regimen's individual ARV drugs and the number of HIV-1 mutations required for the development of resistance to each ARV - the genetic barrier to resistance. ARV resistance impairs the response to therapy in patients with transmitted resistance, unsuccessful initial ARV therapy and multiple virological failures. Genotypic resistance testing is used to identify transmitted drug resistance, provide insight into the reasons for virological failure in treated patients, and help guide second-line and salvage therapies. In patients with transmitted drug resistance, the virological response to a regimen selected on the basis of standard genotypic testing approaches the responses observed in patients with wild-type viruses. However, because such patients are at a higher risk of harbouring minority drug-resistant variants, initial ARV therapy in this population should contain a boosted protease inhibitor (PI) - the drug class with the highest genetic barrier to resistance. In patients receiving an initial ARV regimen with a high genetic barrier to resistance, the most common reasons for virological failure are nonadherence and, potentially, pharmacokinetic factors or minority transmitted drug-resistant variants. Among patients in whom first-line ARVs have failed, the patterns of drug-resistance mutations and cross-resistance are often predictable. However, the extent of drug resistance correlates with the duration of uncontrolled virological replication. Second-line therapy should include the continued use of a dual nucleoside/nucleotide reverse transcriptase inhibitor (NRTI)-containing backbone, together with a change in the non-NRTI component, most often to an ARV belonging to a new drug class. The number of available fully active ARVs is often diminished with each successive treatment failure. Therefore, a salvage regimen is likely to be more complicated in that it may require multiple ARVs with partial residual activity and compromised genetic barriers of resistance to attain complete virological suppression. A thorough examination of the patient's ARV history and prior resistance tests should be performed because genotypic and/or phenotypic susceptibility testing is often not sufficient to identify drug-resistant variants that emerged during past therapies and may still pose a threat to a new regimen. Phenotypic testing is also often helpful in this subset of patients. ARVs used for salvage therapy can be placed into the following hierarchy: (i) ARVs belonging to a previously unused drug class; (ii) ARVs belonging to a previously used drug class that maintain significant residual antiviral activity; (iii) NRTI combinations, as these often appear to retain in vivo virological activity, even in the presence of reduced in vitro NRTI susceptibility; and rarely (iv) ARVs associated with previous virological failure and drug resistance that appear to have possibly regained their activity as a result of viral reversion to wild type. Understanding the basic principles of HIV drug resistance is helpful in guiding individual clinical decisions and the development of ARV treatment guidelines.