Inhibitors of hepatitis C virus entry may be potent ingredients of optimal drug combinations

Padmanabhan, Pranesh; Dixit, Narendra M.

doi:10.1073/pnas.1704531114

Cited by 12 publications

(10 citation statements)

References 11 publications

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“…A deeper understanding of E2 function and its interactions with SR-B1 and CD81 is likely to aid the design of candidate B-cell targeted vaccines. Moreover, an appreciation of pinch points in the HCV entry pathway may guide the use of entry inhibitor drugs in combination with direct-acting antivirals [16,17].…”

Section: Introductionmentioning

confidence: 99%

Building a mechanistic mathematical model of hepatitis C virus entry

et al. 2019

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The mechanism by which hepatitis C virus (HCV) gains entry into cells is a complex one, involving a broad range of host proteins. Entry is a critical phase of the viral lifecycle, and a potential target for therapeutic or vaccine-mediated intervention. However, the mechanics of HCV entry remain poorly understood. Here we describe a novel computational model of viral entry, encompassing the relationship between HCV and the key host receptors CD81 and SR-B1. We conduct experiments to thoroughly quantify the influence of an increase or decrease in receptor availability upon the extent of viral entry. We use these data to build and parameterise a mathematical model, which we then validate by further experiments. Our results are consistent with sequential HCV-receptor interactions, whereby initial interaction between the HCV E2 glycoprotein and SR-B1 facilitates the accumulation CD81 receptors, leading to viral entry. However, we also demonstrate that a small minority of viruses can achieve entry in the absence of SR-B1. Our model estimates the impact of the different obstacles that viruses must surmount to achieve entry; among virus particles attaching to the cell surface, around one third of viruses accumulate sufficient CD81 receptors, of which 4–8% then complete the subsequent steps to achieve productive infection. Furthermore, we make estimates of receptor stoichiometry; in excess of 10 receptors are likely to be required to achieve viral entry. Our model provides a tool to investigate the entry characteristics of HCV variants and outlines a framework for future quantitative studies of the multi-receptor dynamics of HCV entry.

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Section: Introductionmentioning

confidence: 99%

Building a mechanistic mathematical model of hepatitis C virus entry

et al. 2019

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“…The standard strategy to avert DAA failure is to increase the genetic barrier to resistance by including more DAAs in the drug cocktail [ 12 , 54 ]. In a recent set of studies, for instance, numerous DAA combinations were evaluated preclinically to identify the “best” candidates for clinical development and 3 DAA combinations were found to be more potent than 2 DAA combinations [ 54 – 56 ]. We suggest that an alternative strategy may often be feasible: improving IFN-responsiveness by adding IFN (or PR).…”

Section: Discussionmentioning

confidence: 99%

Modelling how responsiveness to interferon improves interferon-free treatment of hepatitis C virus infection

et al. 2018

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Direct-acting antiviral agents (DAAs) for hepatitis C treatment tend to fare better in individuals who are also likely to respond well to interferon-alpha (IFN), a surprising correlation given that DAAs target specific viral proteins whereas IFN triggers a generic antiviral immune response. Here, we posit a causal relationship between IFN-responsiveness and DAA treatment outcome. IFN-responsiveness restricts viral replication, which would prevent the growth of viral variants resistant to DAAs and improve treatment outcome. To test this hypothesis, we developed a multiscale mathematical model integrating IFN-responsiveness at the cellular level, viral kinetics and evolution leading to drug resistance at the individual level, and treatment outcome at the population level. Model predictions quantitatively captured data from over 50 clinical trials demonstrating poorer response to DAAs in previous non-responders to IFN than treatment-naïve individuals, presenting strong evidence supporting the hypothesis. Model predictions additionally described several unexplained clinical observations, viz., the percentages of infected individuals who 1) spontaneously clear HCV, 2) get chronically infected but respond to IFN-based therapy, and 3) fail IFN-based therapy but respond to DAA-based therapy, resulting in a comprehensive understanding of HCV infection and treatment. An implication of the causal relationship is that failure of DAA-based treatments may be averted by adding IFN, a strategy of potential use in settings with limited access to DAAs. A second, wider implication is that individuals with greater IFN-responsiveness would require shorter DAA-based treatment durations, presenting a basis and a promising population for response-guided therapy.

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“…Following previous studies on HIV-1 and HCV [18][19][20] , we therefore computed next the IIP values of the NAbs at D=100 µg/ml. We found that the IIP displayed a wide range, from (Fig.…”

Section: Iip Estimates the Nab Landscape And Benchmarksmentioning

confidence: 99%

“…1C). Drug combinations with higher IIP values have been shown to have better efficacies, with HIV-1 14,15 and hepatitis C virus (HCV) 18,19 . IIP has since been extended to antibodies and shown to predict the relative efficacies of HIV-1 and HCV antibodies 18,20 .…”

Section: Introductionmentioning

confidence: 99%

The quantitative landscape of the neutralizing antibody response to SARS-CoV-2

Padmanabhan

Desikan

Dixit

2020

Preprint

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Neutralizing antibodies (NAbs) appear promising interventions against SARS-CoV-2 infection. Over 100 NAbs have been identified so far and several are in clinical trials. Yet, which NAbs would be the most potent remains unclear. Here, we analysed reported in vitro dose-response curves (DRCs) of >70 NAbs and estimated corresponding 50% inhibitory concentrations, slope parameters, and instantaneous inhibitory potentials (IIPs), presenting a comprehensive quantitative landscape of NAb responses to SARS-CoV-2. NAbs with high IIPs are likely to be potent. To assess the applicability of the landscape in vivo, we analysed available DRCs of NAbs from individual patients and found that the responses closely resembled the landscape. Further, we created virtual patient plasma samples by randomly sampling NAbs from the landscape and found that they recapitulated plasma dilution assays from convalescent patients. The landscape thus offers a facile tool for benchmarking NAbs and would aid the development of NAb-based therapies for SARS-CoV-2 infection.

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Inhibitors of hepatitis C virus entry may be potent ingredients of optimal drug combinations

Cited by 12 publications

References 11 publications

Building a mechanistic mathematical model of hepatitis C virus entry

Building a mechanistic mathematical model of hepatitis C virus entry

Modelling how responsiveness to interferon improves interferon-free treatment of hepatitis C virus infection

The quantitative landscape of the neutralizing antibody response to SARS-CoV-2

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