Mechanisms of Receptor/Coreceptor-Mediated Entry of Enveloped Viruses

Nowak, Sarah A.; Chou, Tom

doi:10.1016/j.bpj.2009.01.018

Cited by 31 publications

(28 citation statements)

References 58 publications

(57 reference statements)

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“…In addition, as shown below, because the endosomal escape time depends on the concentration of proteases in the endosome, the escape rate is not time-independent; instead, it is an increasing function of time. Recently, using the virus-host interactions, new stochastic models have been developed at a molecular level to quantify the different viral entry stages, starting with the receptor binding at the cell surface, the virus internalization (17)(18)(19), and the free cytoplasmic trafficking to a nuclear pore (20)(21)(22)(23).…”

Section: Introductionmentioning

confidence: 99%

Modeling the Step of Endosomal Escape during Cell Infection by a Nonenveloped Virus

Lagache

Danos

Holcman

2012

Biophysical Journal

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Widely disparate viruses enter the host cell through an endocytic pathway and travel the cytoplasm inside an endosome. For the viral genetic material to be delivered into the cytoplasm, these viruses have to escape the endosomal compartment, an event triggered by the conformational changes of viral endosomolytic proteins. We focus here on small nonenveloped viruses such as adeno-associated viruses, which contain few penetration proteins. The first time a penetration protein changes conformation defines the slowest timescale responsible for the escape. To evaluate this time, we construct what to our knowledge is a novel biophysical model based on a stochastic approach that accounts for the small number of proteins, the endosomal maturation, and the protease activation dynamics. We show that the escape time increases with the endosomal size, whereas decreasing with the number of viral particles inside the endosome. We predict that the optimal escape probability is achieved when the number of proteases in the endosome is in the range of 250-350, achieved for three viral particles.

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Section: Introductionmentioning

confidence: 99%

Modeling the Step of Endosomal Escape during Cell Infection by a Nonenveloped Virus

Lagache

Danos

Holcman

2012

Biophysical Journal

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“…These transport times and probabilities can also be obtained using the Kramers method (Section II D 4 and [58,84]). The methods of this section can also be used for the calculation of FPT distributions [53,84,85]. The reader is referred to [4,86,87] for details; see also Section III B 1 below.…”

Section: Discrete Channel Representation: Forward Master Equation Methodsmentioning

confidence: 99%

“…It be extended to include co-receptor binding and viral exocytosys from the infected cells [85,122].…”

Section: Competition Between Viral Dissociation Endocytosis and Fusionmentioning

confidence: 99%

First‐Passage Processes in Cellular Biology

Iyer‐Biswas

Zilman

2016

Advances in Chemical Physics

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We first review fundamentals of the theory of stochastic processes. The system dynamics are specified by the set of its states, {S}, and the transitions between them, S → S , where S, S ∈ {S}. For example, the state S can denote the position of a Brownian particle, the numbers of molecules of different chemical species, or any other variable that characterizes the state of the system of interest. Here we restrict ourselves to processes for which the transition rates depend only on the system's instantaneous state, and not the entirety of its history. Such memoryless processes are known as Markovian and are applicable to a wide range of systems. We also assume that the transition rates do not explicitly depend on time, a condition known as stationarity. In this review we make the standard assumption that the transitions between the states are Poisson distributed random processes. In other words, the probability of transitioning from state S to state S in an infinitesimal interval, dt, is α(S, S )dt, where α(S, S ) is the transition rate.Examples. For a Brownian particle diffusing along a line, the state S is defined by the particle position; the transition rate is 2D/d 2 , where D is the diffusion coefficient and d is the step length. For a set of radioactive atoms undergoing decay with rate κ per atom, the state S is defined by the number, n, of atoms that have not decayed yet, and the transition rate from state n to state n − 1 is κ n. For a system with N reacting chemical species, the system state is defined by the concentrations of each reactant, (x 1 . . . x N ), and the transition rates are functions of these concentrations.B. Time evolution equation(s) for the system.We now summarize the equations that govern the dynamical evolution of the probability that the system is in state S at time t, which we denote by P (S, t). Typically, such equations are written in one of three formalisms: the Master Equation, the Fokker-Planck Equation, or the Stochastic Differential Equation; each is summarized below in turn. Details of the

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“…At this stage, there is a pore between the virus envelope and the host cell through which genetic material and other enzymes can pass (Figure 1C- iv ). There is evidence that exactly one envelope spike is required to initiate pore formation [45], but other analyses suggest fusion is a concerted effort that requires anywhere from 2 to 19 envelope spikes [46,47,48,49]. Following budding from the T-cell host, the trimer-of-heterodimers are the only HIV proteins displayed on the virus outer envelope.…”

Section: Virus-cell Fusion and Structural Biology Of Hivgp41mentioning

confidence: 99%

Computer-Aided Approaches for Targeting HIVgp41

Allen

Rizzo

2012

Biology

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Virus-cell fusion is the primary means by which the human immunodeficiency virus-1 (HIV) delivers its genetic material into the human T-cell host. Fusion is mediated in large part by the viral glycoprotein 41 (gp41) which advances through four distinct conformational states: (i) native, (ii) pre-hairpin intermediate, (iii) fusion active (fusogenic), and (iv) post-fusion. The pre-hairpin intermediate is a particularly attractive step for therapeutic intervention given that gp41 N-terminal heptad repeat (NHR) and C-terminal heptad repeat (CHR) domains are transiently exposed prior to the formation of a six-helix bundle required for fusion. Most peptide-based inhibitors, including the FDA-approved drug T20, target the intermediate and there are significant efforts to develop small molecule alternatives. Here, we review current approaches to studying interactions of inhibitors with gp41 with an emphasis on atomic-level computer modeling methods including molecular dynamics, free energy analysis, and docking. Atomistic modeling yields a unique level of structural and energetic detail, complementary to experimental approaches, which will be important for the design of improved next generation anti-HIV drugs.

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Mechanisms of Receptor/Coreceptor-Mediated Entry of Enveloped Viruses

Cited by 31 publications

References 58 publications

Modeling the Step of Endosomal Escape during Cell Infection by a Nonenveloped Virus

Modeling the Step of Endosomal Escape during Cell Infection by a Nonenveloped Virus

First‐Passage Processes in Cellular Biology

Computer-Aided Approaches for Targeting HIVgp41

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