Rational design of LEDGINs as first allosteric integrase inhibitors for the treatment of HIV infection

Sulforaphane prevents the reactivation of HIV-1 by suppressing NFκB signaling

Despite more than 20 years of combination antiretroviral therapy (cART), complete eradication of HIV remains a daunting task. While cART has been very effective in limiting new cycles of infection and keeping viral load below detectable levels with partial restoration of immune functions, it cannot provide a cure. Evidently, the interruption of cART leads to a quick rebound of the viral load within a few weeks. These consistent observations have revealed HIV ability to persist as an undetectable latent reservoir in a variety of tissues that remain insensitive to antiretroviral therapies. The 'Block-and-Lock' approach to drive latent cells into deep latency has emerged as a viable strategy to achieve a functional cure. It entails the development of latency-promoting agents with anti-HIV functions. Recent reports have suggested sulforaphane (SFN), an inducer of NRF-2 (nuclear erythroid 2-related factor 2)-mediated antioxidative signaling, to possess anti-HIV properties by restricting HIV replication at the early stages. However, the effect of SFN on the expression of integrated provirus remains unexplored. We have hypothesized that SFN may promote latency and prevent reactivation. Our results indicate that SFN can render latently infected monocytes and CD4+ T cells resistant to reactivation. SFN treatments antagonized the effects of known latency reactivating agents, tumor necrosis pactor (TNF-α), and phorbol 12-myristate 13-acetate (PMA), and caused a significant reduction in HIV transcription, viral RNA copies, and p24 levels. Furthermore, this block of reactivation was found to be mediated by SFN-induced NRF-2 signaling that specifically decreased the activation of NFκB signaling and thus restricted the HIV-1 promoter (5'LTR) activity. Overall, our study provides compelling evidence to highlight the latency-promoting potential of SFN which could be used in the 'Block-and-Lock' approach to achieve an HIV cure.

HIV-1 Maturation: Lessons Learned from Inhibitors

Since the emergence of HIV and AIDS in the early 1980s, the development of safe and effective therapies has accompanied a massive increase in our understanding of the fundamental processes that drive HIV biology. As basic HIV research has informed the development of novel therapies, HIV inhibitors have been used as probes for investigating basic mechanisms of HIV-1 replication, transmission, and pathogenesis. This positive feedback cycle has led to the development of highly effective combination antiretroviral therapy (cART), which has helped stall the progression to AIDS, prolong lives, and reduce transmission of the virus. However, to combat the growing rates of virologic failure and toxicity associated with long-term therapy, it is important to diversify our repertoire of HIV-1 treatments by identifying compounds that block additional steps not targeted by current drugs. Most of the available therapeutics disrupt early events in the replication cycle, with the exception of the protease (PR) inhibitors, which act at the virus maturation step. HIV-1 maturation consists of a series of biochemical changes that facilitate the conversion of an immature, noninfectious particle to a mature infectious virion. These changes include proteolytic processing of the Gag polyprotein by the viral protease (PR), structural rearrangement of the capsid (CA) protein, and assembly of individual CA monomers into hexamers and pentamers that ultimately form the capsid. Here, we review the development and therapeutic potential of maturation inhibitors (MIs), an experimental class of anti-HIV-1 compounds with mechanisms of action distinct from those of the PR inhibitors. We emphasize the key insights into HIV-1 biology and structure that the study of MIs has provided. We will focus on three distinct groups of inhibitors that block HIV-1 maturation: (1) compounds that block the processing of the CA-spacer peptide 1 (SP1) cleavage intermediate, the original class of compounds to which the term MI was applied; (2) CA-binding inhibitors that disrupt capsid condensation; and (3) allosteric integrase inhibitors (ALLINIs) that block the packaging of the viral RNA genome into the condensing capsid during maturation. Although these three classes of compounds have distinct structures and mechanisms of action, they share the ability to block the formation of the condensed conical capsid, thereby blocking particle infectivity.

An Isoquinoline Scaffold as a Novel Class of Allosteric HIV-1 Integrase Inhibitors

Allosteric HIV-1 integrase inhibitors (ALLINIs) are a new class of potential antiretroviral therapies with a unique mechanism of action and drug resistance profile. To further extend this class of inhibitors via a scaffold hopping approach, we have synthesized a series of analogues possessing an isoquinoline ring system. Lead compound 6l binds in the v-shaped pocket at the IN dimer interface and is highly selective for promoting higher-order multimerization of inactive IN over inhibiting IN-LEDGF/p75 binding. Importantly, 6l potently inhibited HIV-1_NL4-3 (A128T IN), which confers marked resistance to archetypal quinoline-based ALLINIs. Thermal degradation studies indicated that at elevated temperatures the acetic acid side chain of specific isoquinoline derivatives undergo decarboxylation reactions. This reactivity has implications for the synthesis of various ALLINI analogues.

Recent computational advances in the identification of allosteric sites in proteins

Allosteric modulators have the potential to fine-tune protein functional activity. Therefore, the targeting of allosteric sites, as a strategy in drug design, is gaining increasing attention. Currently, it is not trivial to find and characterize new allosteric sites by experimental approaches. Alternatively, computational approaches are useful in helping researchers analyze and select potential allosteric sites for drug discovery. Here, we review state-of-the-art computational approaches directed at predicting putative allosteric sites in proteins, along with examples of successes in identifying allosteric sites utilizing these methods. We also discuss the challenges in developing reliable methods for predicting allosteric sites and tactics to resolve demanding tasks.