Unified regression model of binding equilibria in crowded environments

Deathdaily: A Python Package Index for predicting the number of daily COVID-19 deaths

This paper presents a new open-source program called deathdaily for predicting the number of daily COVID-19 deaths in the next 7 days. The predictions can be used by policymakers to determine whether current policies should be strengthened/mitigated or new policies should be challenged to mitigate the COVID-19 pandemic. Although vaccines have been mitigating the pandemic initially, the recent resurgence with new variants has been observed in many vaccinated countries. This paper shows how to use deathdaily to detect symptoms of resurgence. The proposed deathdaily is available in public and can be installed by a Python package manager PyPI. The deathdaily has been downloaded by 15,964 users worldwide, according to https://pepy.tech/project/deathdaily. The fact shows that the applicability, practicality, and usefulness of the proposed program have been duly evaluated.

Mechanical, nanomorphological and biological reconstruction of early‑stage apoptosis in HeLa cells induced by cytochalasin B

There is a growing interest in the fact that mechanical signals may be as important as biological signals in evaluating cell viability. To investigate the alterations in biomechanics, nanomorphology and biological apoptotic signals during early apoptosis, an apoptosis model was established for cervical cancer HeLa cells induced by cytochalasin B (CB). The cellular mechanical properties, geometry, morphology and expression of key apoptotic proteins were systematically analyzed. The findings indicated a marked decline in cellular elastic modulus and volume and a considerable increase in surface roughness occurring prior to the activation of biological apoptosis signals (such as phosphatidylserine exposure or activation of CD95/Fas). Moreover, the depolymerization of filamentous actin aggravated the intracellular crowding degree, which induced the redistribution of different-sized protein molecules and protrusions across the cell membrane arising from excluded volume interactions. Statistical analysis revealed that the disassembly of the actin cytoskeleton was negatively correlated with the cellular elastic modulus and volume, but was positively correlated with surface roughness and CD95/Fas activation. The results of the present study suggest that compared with biological signals, mechanical and geometrical reconstruction is more sensitive during apoptosis and the increase in cell surface roughness arises from the redistribution of biophysical molecules. These results contribute to our in-depth understanding of the apoptosis mechanisms of cancer cells mediated by cytochalasin B.

A coarse-grained model for the simulations of biomolecular interactions in cellular environments

The interactions of bio-molecules constitute the key steps of cellular functions. However, in vivo binding properties differ significantly from their in vitro measurements due to the heterogeneity of cellular environments. Here we introduce a coarse-grained model based on rigid-body representation to study how factors such as cellular crowding and membrane confinement affect molecular binding. The macroscopic parameters such as the equilibrium constant and the kinetic rate constant are calibrated by adjusting the microscopic coefficients used in the numerical simulations. By changing these model parameters that are experimentally approachable, we are able to study the kinetic and thermodynamic properties of molecular binding, as well as the effects caused by specific cellular environments. We investigate the volumetric effects of crowded intracellular space on bio-molecular diffusion and diffusion-limited reactions. Furthermore, the binding constants of membrane proteins are currently difficult to measure. We provide quantitative estimations about how the binding of membrane proteins deviates from soluble proteins under different degrees of membrane confinements. The simulation results provide biological insights to the functions of membrane receptors on cell surfaces. Overall, our studies establish a connection between the details of molecular interactions and the heterogeneity of cellular environments.

Reaching new levels of realism in modeling biological macromolecules in cellular environments

An increasing number of studies are aimed at modeling cellular environments in a comprehensive and realistic fashion. A major challenge in these efforts is how to bridge spatial and temporal scales over many orders of magnitude. Furthermore, there are additional challenges in integrating different aspects ranging from questions about biomolecular stability in crowded environments to the description of reactive processes on cellular scales. In this review, recent studies with models of biomolecules in cellular environments at different levels of detail are discussed in terms of their strengths and weaknesses. In particular, atomistic models, implicit representations of cellular environments, coarse-grained and spheroidal models of biomolecules, as well as the inclusion of reactive processes via reaction-diffusion models are described. Furthermore, strategies for integrating the different models into a comprehensive description of cellular environments are discussed.

Three-dimensional stochastic off-lattice model of binding chemistry in crowded environments

Molecular crowding is one of the characteristic features of the intracellular environment, defined by a dense mixture of varying kinds of proteins and other molecules. Interaction with these molecules significantly alters the rates and equilibria of chemical reactions in the crowded environment. Numerous fundamental activities of a living cell are strongly influenced by the crowding effect, such as protein folding, protein assembly and disassembly, enzyme activity, and signal transduction. Quantitatively predicting how crowding will affect any particular process is, however, a very challenging problem because many physical and chemical parameters act synergistically in ways that defy easy analysis. To build a more realistic model for this problem, we extend a prior stochastic off-lattice model from two-dimensional (2D) to three-dimensional (3D) space and examine how the 3D results compare to those found in 2D. We show that both models exhibit qualitatively similar crowding effects and similar parameter dependence, particularly with respect to a set of parameters previously shown to act linearly on total reaction equilibrium. There are quantitative differences between 2D and 3D models, although with a generally gradual nonlinear interpolation as a system is extended from 2D to 3D. However, the additional freedom of movement allowed to particles as thickness of the simulation box increases can produce significant quantitative change as a system moves from 2D to 3D. Simulation results over broader parameter ranges further show that the impact of molecular crowding is highly dependent on the specific reaction system examined.