Viral Kinetics Model of SARS-CoV-2 Infection Informs Drug Discovery, Clinical Dose, and Regimen Selection.

Quantitative systems pharmacology (QSP) has been an important tool to project safety and efficacy of novel or repurposed therapies for the SARS-CoV-2 virus. Here, we present a QSP modeling framework to predict response to antiviral therapeutics with three mechanisms of action (MoA): cell entry inhibitors, anti-replicatives, and neutralizing biologics. We parameterized three distinct model structures describing virus-host interaction by fitting to published viral kinetics data of untreated COVID-19 patients. The models were used to test theoretical behaviors and map therapeutic design criteria of the different MoAs, identifying the most rapid and robust antiviral activity from neutralizing biologic and anti-replicative MoAs. We found good agreement between model predictions and clinical viral load reduction observed with anti-replicative nirmatrelvir/ritonavir (Paxlovid®) and neutralizing biologics bamlanivimab and casirivimab/imdevimab (REGEN-COV®), building confidence in the modeling framework to inform a dose selection. Finally, the model was applied to predict antiviral response with ensovibep, a novel DARPin therapeutic designed as a neutralizing biologic. We developed a new in silico measure of antiviral activity, area under the curve (AUC) of free spike protein concentration, as a metric with larger dynamic range than viral load reduction. By benchmarking to bamlanivimab predictions, we justified dose levels of 75, 225, and 600 mg ensovibep to be administered intravenously in a Phase 2 clinical investigation. Upon trial completion, we found model predictions to be in good agreement with the observed patient data. These results demonstrate the utility of this modeling framework to guide the development of novel antiviral therapeutics.

Influence of survival, promotion, and growth on pattern formation in zebrafish skin.

The coloring of zebrafish skin is often used as a model system to study biological pattern formation. However, the small number and lack of movement of chromatophores defies traditional Turing-type pattern generating mechanisms. Recent models invoke discrete short-range competition and long-range promotion between different pigment cells as an alternative to a reaction-diffusion scheme. In this work, we propose a lattice-based "Survival model," which is inspired by recent experimental findings on the nature of long-range chromatophore interactions. The Survival model produces stationary patterns with diffuse stripes and undergoes a Turing instability. We also examine the effect that domain growth, ubiquitous in biological systems, has on the patterns in both the Survival model and an earlier "Promotion" model. In both cases, domain growth alone is capable of orienting Turing patterns above a threshold wavelength and can reorient the stripes in ablated cells, though the wavelength for which the patterns orient is much larger for the Survival model. While the Survival model is a simplified representation of the multifaceted interactions between pigment cells, it reveals complex organizational behavior and may help to guide future studies.

The smallest chimera: Periodicity and chaos in a pair of coupled chemical oscillators.

Symmetrically coupled identical oscillators were once believed to support only totally synchronous or totally asynchronous states. More recently, chimera states, in which a subset of oscillators behaves coherently while the other subset exhibits disorder, have been found in large arrays of oscillators, coupled either locally or globally. We demonstrate for the first time the existence of a chimera state with only two diffusively coupled identical oscillators, one behaving nearly periodically (coherently) and the other chaotically (incoherently). We attribute this behavior to a "master-slave" interaction, which arises via a symmetry-breaking canard explosion.

Kinetic Analysis of Nanostructures Formed by Enzyme-Instructed Intracellular Assemblies against Cancer Cells.

Recent studies have demonstrated that enzyme-instructed self-assembly (EISA) in extra- or intracellular environments can serve as a multistep process for controlling cell fate. There is little knowledge, however, about the kinetics of EISA in the complex environments in or around cells. Here, we design and synthesize three dipeptidic precursors (ld-1-SO3, dl-1-SO3, dd-1-SO3), consisting of diphenylalanine (l-Phe-d-Phe, d-Phe-l-Phe, d-Phe-d-Phe, respectively) as the backbone, which are capped by 2-(naphthalen-2-yl)acetic acid at the N-terminal and by 2-(4-(2-aminoethoxy)-4-oxobutanamido)ethane-1-sulfonic acid at the C-terminal. On hydrolysis by carboxylesterases (CES), these precursors result in hydrogelators, which self-assemble in water at different rates. Whereas all three precursors selectively kill cancer cells, especially high-grade serous ovarian carcinoma cells, by undergoing intracellular EISA, dl-1-SO3 and dd-1-SO3 exhibit the lowest and the highest activities, respectively, against the cancer cells. This trend inversely correlates with the rates of converting the precursors to the hydrogelators in phosphate-buffered saline. Because CES exists both extra- and intracellularly, we use kinetic modeling to analyze the kinetics of EISA inside cells and to calculate the cytotoxicity of each precursor for killing cancer cells. Our results indicate that (i) the stereochemistry of the precursors affects the morphology of the nanostructures formed by the hydrogelators, as well as the rate of enzymatic conversion; (ii) decreased extracellular hydrolysis of precursors favors intracellular EISA inside the cells; (iii) the inherent features ( e.g., self-assembling ability and morphology) of the EISA molecules largely dictate the cytotoxicity of intracellular EISA. As the kinetic analysis of intracellular EISA, this work elucidates how the stereochemistry modulates EISA in the complex extra- and/or intracellular environment for developing anticancer molecular processes. Moreover, it provides insights for understanding the kinetics and cytotoxicity of aggregates of aberrant proteins or peptides formed inside and outside cells.

Stationary spots and stationary arcs induced by advection in a one-activator, two-inhibitor reactive system.

This paper studies the spatiotemporal dynamics of a reaction-diffusion-advection system corresponding to an extension of the Oregonator model, which includes two inhibitors instead of one. We show that when the reaction-diffusion, two-dimensional problem displays stationary patterns the addition of a plug flow can induce the emergence of new types of stationary structures. These patterns take the form of spots or arcs, the size and the spacing of which can be controlled by the flow.