Computational Models of HIV-1 Resistance to Gene Therapy Elucidate Therapy Design Principles

Gene therapy is an emerging alternative to conventional anti-HIV-1 drugs, and can potentially control the virus while alleviating major limitations of current approaches. Yet, HIV-1's ability to rapidly acquire mutations and escape therapy presents a critical challenge to any novel treatment paradigm. Viral escape is thus a key consideration in the design of any gene-based technique. We develop a computational model of HIV's evolutionary dynamics in vivo in the presence of a genetic therapy to explore the impact of therapy parameters and strategies on the development of resistance. Our model is generic and captures the properties of a broad class of gene-based agents that inhibit early stages of the viral life cycle. We highlight the differences in viral resistance dynamics between gene and standard antiretroviral therapies, and identify key factors that impact long-term viral suppression. In particular, we underscore the importance of mutationally-induced viral fitness losses in cells that are not genetically modified, as these can severely constrain the replication of resistant virus. We also propose and investigate a novel treatment strategy that leverages upon gene therapy's unique capacity to deliver different genes to distinct cell populations, and we find that such a strategy can dramatically improve efficacy when used judiciously within a certain parametric regime. Finally, we revisit a previously-suggested idea of improving clinical outcomes by boosting the proliferation of the genetically-modified cells, but we find that such an approach has mixed effects on resistance dynamics. Our results provide insights into the short- and long-term effects of gene therapy and the role of its key properties in the evolution of resistance, which can serve as guidelines for the choice and optimization of effective therapeutic agents

A Scientific Roadmap for Antibiotic Discovery: A Sustained and Robust Pipeline of New Antibacterial Drugs and Therapies is Critical to Preserve Public Health

In recent decades, the discovery and development of new antibiotics have slowed dramatically as scientific barriers to drug discovery, regulatory challenges, and diminishing returns on investment have led major drug companies to scale back or abandon their antibiotic research. Consequently, antibiotic discovery—which peaked in the 1950s—has dropped precipitously. Of greater concern is the fact that nearly all antibiotics brought to market over the past 30 years have been variations on existing drugs. Every currently available antibiotic is a derivative of a class discovered between the early 1900s and 1984.At the same time, the emergence of antibiotic-resistant pathogens has accelerated, giving rise to life-threatening infections that will not respond to available antibiotic treatment. Inevitably, the more that antibiotics are used, the more that bacteria develop resistance—rendering the drugs less effective and leading public health authorities worldwide to flag antibiotic resistance as an urgent and growing public health threat

The Structural Basis for the Interdependence of Drug Resistance in the HIV-1 Protease

The human immunodeficiency virus type 1 (HIV-1) protease (PR) is a critical drug target as it is responsible for virion maturation. Mutations within the active site (1°) of the PR directly interfere with inhibitor binding while mutations distal to the active site (2°) to restore enzymatic fitness. Increasing mutation number is not directly proportional to the severity of resistance, suggesting that resistance is not simply additive but that it is interdependent. The interdependency of both primary and secondary mutations to drive protease inhibitor (PI) resistance is grossly understudied. To structurally and dynamically characterize the direct role of secondary mutations in drug resistance, I selected a panel of single-site mutant protease crystal structures complexed with the PI darunavir (DRV). From these studies, I developed a network hypothesis that explains how mutations outside the active site are able to perpetuate changes to the active site of the protease to disrupt inhibitor binding. I then expanded the panel to include highly mutated multi-drug resistant variants. To elucidate the interdependency between primary and secondary mutations I used statistical and machine-learning techniques to determine which specific mutations underlie the perturbations of key inter-molecular interactions. From these studies, I have determined that mutations distal to the active site are able to perturb the global PR hydrogen bonding patterns, while primary and secondary mutations cooperatively perturb hydrophobic contacts between the PR and DRV. Discerning and exploiting the mechanisms that underlie drug resistance in viral targets could proactively ameliorate both current treatment and inhibitor design for HIV-1 targets

Immunogens and Antigen Processing: Report from a Global HIV Vaccine Enterprise Working Group

The Global HIV Vaccine Enterprise convened a meeting of a Working Group in July 2009 to discuss recent progress in rational design of the components of an HIV vaccine, such as inserts, vectors and adjuvants,and in understanding antigen processing and presentation to T and B cells. This Report summarizes the key points of that discussion, and subsequent discussions with the Chairs of the other Enterprise Working Groups, the Enterprise Science Committee, the Enterprise Council and the broader scientific community during open sessions at scientific conferences

HIV Reservoirs and Immune Surveillance Evasion Cause the Failure of Structured Treatment Interruptions: A Computational Study

Continuous antiretroviral therapy is currently the most effective way to treat HIV infection. Unstructured interruptions are quite common due to side effects and toxicity, among others, and cannot be prevented. Several attempts to structure these interruptions failed due to an increased morbidity compared to continuous treatment. The cause of this failure is poorly understood and often attributed to drug resistance. Here we show that structured treatment interruptions would fail regardless of the emergence of drug resistance. Our computational model of the HIV infection dynamics in lymphoid tissue inside lymph nodes, demonstrates that HIV reservoirs and evasion from immune surveillance themselves are sufficient to cause the failure of structured interruptions. We validate our model with data from a clinical trial and show that it is possible to optimize the schedule of interruptions to perform as well as the continuous treatment in the absence of drug resistance. Our methodology enables studying the problem of treatment optimization without having impact on human beings. We anticipate that it is feasible to steer new clinical trials using computational models

Antiretroviral drug susceptibility of a hinge region variant of HIV-1 subtype C protease

A thesis submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg in fulfilment of the requirements for the degree of Doctor of Philosophy. Johannesburg, 28 May 2018.Since their discovery, protease inhibitors continue to be an essential component of antiretroviral treatment for human immunodeficiency virus type 1 (HIV-1). However, the development of resistance to protease inhibitors remains one of the most significant challenges in the fight for sustained viral suppression in those infected with HIV-1. Studies show that specific mutations arising within the HIV-1 gag and protease genes can lead to the development of resistance. In this research, a South African HIV-1 subtype C Gag-protease variant (W1201i) was investigated. This variant was considered due to the presence of a mutation and insertion (N37T↑V), located within the hinge region of the protease enzyme. Moreover, the variant displayed the following polymorphisms: Q7K, I13V, G16E, M36T, D60E, Q61E, I62V and M89L. Genotyping of W1201i Gag revealed a previously unreported MSQAG insertion between the CA/p2 and p2/NC cleavage sites. Additionally, a mutation and insertion (I372L↑M), and multiple polymorphisms (S369N, S371N, I373M and G377S) were discovered within the p2/NC cleavage site. Single-cycle phenotypic assays were performed to determine the drug susceptibility and replication capacity of the variant. The results show that the mutations present in the N37T↑V protease conferred a replicative advantage and reduced susceptibility to lopinavir, atazanavir and darunavir. Interestingly, the mutations in W1201i Gag were found to modulate both replication capacity and protease inhibitor susceptibility. In silico studies were performed to understand the physical basis for the observed variations. Molecular dynamics simulations showed that the N37T↑V protease displayed altered dynamics around the hinge and flap region and highlighted the amino acids responsible for the observed fluctuations. Furthermore, induced fit docking experiments showed that the variant bound the iv protease inhibitors with fewer favourable chemical interactions than the wild-type protease. Collectively, these data elucidate the biophysical basis for the selection of hinge region mutations and insertions by the HI virus and show that protease, as well as Gag, needs to be evaluated during resistance testing.EM201

Understanding resistance to combination chemotherapy

available in PMC 2014 April 04The current clinical application of combination chemotherapy is guided by a historically successful set of practices that were developed by basic and clinical researchers 50–60 years ago. Thus, in order to understand how emerging approaches to drug development might aid the creation of new therapeutic combinations, it is critical to understand the defining principles underlying classic combination therapy and the original experimental rationales behind them. One such principle is that the use of combination therapies with independent mechanisms of action can minimize the evolution of drug resistance. Another is that in order to kill sufficient cancer cells to cure a patient, multiple drugs must be delivered at their maximum tolerated dose – a condition that allows for enhanced cancer cell killing with manageable toxicity. In light of these models, we aim to explore recent genomic evidence underlying the mechanisms of resistance to the combination regimens constructed on these principles. Interestingly, we find that emerging genomic evidence contradicts some of the rationales of early practitioners in developing commonly used drug regimens. However, we also find that the addition of recent targeted therapies has yet to change the current principles underlying the construction of anti-cancer combinatorial regimens, nor have they made substantial inroads into the treatment of most cancers. We suggest that emerging systems/network biology approaches have an immense opportunity to impact the rational development of successful drug regimens. Specifically, by examining drug combinations in multivariate ways, next generation combination therapies can be constructed with a clear understanding of how mechanisms of resistance to multi-drug regimens differ from single agent resistance.Massachusetts Institute of Technology (Eisen and Chang Career Development Associate Professor of Biology)National Cancer Institute (U.S.) (NCI Integrative Cancer Biology Program (ICBP), #U54-CA112967-06)National Institutes of Health (U.S.) (NIH RO1-CA128803-04

Multivalent biological interactions for the detection and inhibition of HIV-1 protease

Several diseases including cancer and pathogen infection are mediated by protease activity. In HIV infection, the viral protease plays a central role in the virus lifecycle, which has made it a clear therapeutic target. The dominant approach for the treatment of HIV is heavily dependent on inhibitors of this enzyme, but no new drugs have reached the market since 2006. There is thus a need for new design principles for the development of anti-retroviral therapies. Traditional methods of HIV detection are also limited in their use at point-of-care in resource-limited settings due to their reliance on highly trained laboratory personnel, cold-chain transport and expensive reagents. This thesis examines the role of peptide-protein interactions for the inhibition and detection of HIV-1 protease. Phage display is used to isolate heptameric peptide sequences which interact specifically with the enzyme. These peptides are then utilised as sensors for the detection of the enzyme through Forster Resonance Energy Transfer (FRET). The inhibitory properties of the peptides, both in isolation and through multivalent conjugates are also investigated. Finally, insights into the nature of these peptide-protein interactions are explored through molecular docking and all-atom classical molecular dynamics simulations. The expression of recombinant HIV-1 protease in E. coli is also discussed. The peptide based systems described here are expected to be more stable to environmental effects than protein based therapies and it is hoped that this work will provide new pathways for the design of peptide-based therapeutics and diagnostics for protease related diseases which do not rely on traditional methods.Open Acces