Crowding induced switching of polymer translocation by the amalgamation of entropy and osmotic pressure.

The translocation of polymers is omnipresent in inherently crowded biological systems. We investigate the dynamics of polymer translocation through a pore in free and crowded environments using Langevin dynamics simulation. We observed a location-dependent translocation rate of monomers showcasing counterintuitive behavior in stark contrast to the bead velocity along the polymer backbone. The free energy calculation of asymmetrically placed polymers indicates a critical number of segments to direct receiver-side translocation. For one-sided crowding, we have identified a critical crowding size revealing a nonzero probability of translocation toward the crowded-side. Moreover, we have observed that shifting the polymer toward the crowded-side compensates for one-sided crowding, yielding an equal probability akin to a crowder-free system. In two-sided crowding, a slight variation in crowder size and packing fraction induces a polymer to switch its translocation direction. These conspicuous yet counter-intuitive phenomena are rationalized by minimalistic theoretical arguments based on osmotic pressure and radial entropic forces.

Insights into the microevolution of SARS-ACE2 interactions: in silico analysis of glycosylation and SNP pattern.

The prefatory protein-glycan interaction and stabilizing protein-protein interaction of severe acute respiratory syndrome viruses with angiotensin-converting enzyme 2 play a significant role in complex formation thereby promoting endocytosis. The microevolution of SARS-CoV-2 over a period of time has a significant role in increasing the affinity of receptor-binding domain against angiotensin converting-enzyme 2. In this study, we have corroborated the vitality of acquired SNPs over a period of time with increased affinity by using docking studies. The results indicate that the virus modulates the undesirable glycosylation sites by a series of substitution and deletion mutations. It uses bulky residues such as Tyr/Phe for dynamic arrest for quick stabilization of the complex, and Lys residues for stabilizing via hydrogen bond formation besides increasing the binding affinity to ease the cell entry.Communicated by Ramaswamy H. Sarma.

Kinetics of Nanomedicine in Tumor Spheroid as an In Vitro Model System for Efficient Tumor-Targeted Drug Delivery With Insights From Mathematical Models.

Numerous strategies have been developed to treat cancer conventionally. Most importantly, chemotherapy shows its huge promise as a better treatment modality over others. Nonetheless, the very complex behavior of the tumor microenvironment frequently impedes successful drug delivery to the tumor sites that further demands very urgent and effective distribution mechanisms of anticancer drugs specifically to the tumor sites. Hence, targeted drug delivery to tumor sites has become a major challenge to the scientific community for cancer therapy by assuring drug effects to selective tumor tissue and overcoming undesired toxic side effects to the normal tissues. The application of nanotechnology to the drug delivery system pays heed to the design of nanomedicine for specific cell distribution. Aiming to limit the use of traditional strategies, the adequacy of drug-loaded nanocarriers (i.e., nanomedicine) proves worthwhile. After systemic blood circulation, a typical nanomedicine follows three levels of disposition to tumor cells in order to exhibit efficient pharmacological effects induced by the drug candidates residing within it. As a result, nanomedicine propounds the assurance towards the improved bioavailability of anticancer drug candidates, increased dose responses, and enhanced targeted efficiency towards delivery and distribution of effective therapeutic concentration, limiting toxic concentration. These aspects emanate the proficiency of drug delivery mechanisms. Understanding the potential tumor targeting barriers and limiting conditions for nanomedicine extravasation, tumor penetration, and final accumulation of the anticancer drug to tumor mass, experiments with in vivo animal models for nanomedicine screening are a key step before it reaches clinical translation. Although the study with animals is undoubtedly valuable, it has many associated ethical issues. Moreover, individual experiments are very expensive and take a longer time to conclude. To overcome these issues, nowadays, multicellular tumor spheroids are considered a promising in vitro model system that proposes better replication of in vivo tumor properties for the future development of new therapeutics. In this review, we will discuss how tumor spheroids could be used as an in vitro model system to screen nanomedicine used in targeted drug delivery, aiming for better therapeutic benefits. In addition, the recent proliferation of mathematical modeling approaches gives profound insight into the underlying physical principles and produces quantitative predictions. The hierarchical tumor structure is already well decorous to be treated mathematically. To study targeted drug delivery, mathematical modeling of tumor architecture, its growth, and the concentration gradient of oxygen are the points of prime focus. Not only are the quantitative models circumscribed to the spheroid, but also the role of modeling for the nanoparticle is equally inevitable. Abundant mathematical models have been set in motion for more elaborative and meticulous designing of nanomedicine, addressing the question regarding the objective of nanoparticle delivery to increase the concentration and the augmentative exposure of the therapeutic drug molecule to the core. Thus, to diffuse the dichotomy among the chemistry involved, biological data, and the underlying physics, the mathematical models play an indispensable role in assisting the experimentalist with further evaluation by providing the admissible quantitative approach that can be validated. This review will provide an overview of the targeted drug delivery mechanism for spheroid, using nanomedicine as an advantageous tool.

Genome organization via loop extrusion, insights from polymer physics models.

Understanding how genomes fold and organize is one of the main challenges in modern biology. Recent high-throughput techniques like Hi-C, in combination with cutting-edge polymer physics models, have provided access to precise information on 3D chromosome folding to decipher the mechanisms driving such multi-scale organization. In particular, structural maintenance of chromosome (SMC) proteins play an important role in the local structuration of chromatin, putatively via a loop extrusion process. Here, we review the different polymer physics models that investigate the role of SMCs in the formation of topologically associated domains (TADs) during interphase via the formation of dynamic loops. We describe the main physical ingredients, compare them and discuss their relevance against experimental observations.

How epigenome drives chromatin folding and dynamics, insights from efficient coarse-grained models of chromosomes.

The 3D organization of chromosomes is crucial for regulating gene expression and cell function. Many experimental and polymer modeling efforts are dedicated to deciphering the mechanistic principles behind chromosome folding. Chromosomes are long and densely packed-topologically constrained-polymers. The main challenges are therefore to develop adequate models and simulation methods to investigate properly the multi spatio-temporal scales of such macromolecules. Here, we proposed a generic strategy to develop efficient coarse-grained models for self-avoiding polymers on a lattice. Accounting accurately for the polymer entanglement length and the volumic density, we show that our simulation scheme not only captures the steady-state structural and dynamical properties of the system but also tracks the same dynamics at different coarse-graining. This strategy allows a strong power-law gain in numerical efficiency and offers a systematic way to define reliable coarse-grained null models for chromosomes and to go beyond the current limitations by studying long chromosomes during an extended time period with good statistics. We use our formalism to investigate in details the time evolution of the 3D organization of chromosome 3R (20 Mbp) in drosophila during one cell cycle (20 hours). We show that a combination of our coarse-graining strategy with a one-parameter block copolymer model integrating epigenomic-driven interactions quantitatively reproduce experimental data at the chromosome-scale and predict that chromatin motion is very dynamic during the cell cycle.

Interactions of rod-like particles on responsive elastic sheets.

What are the physical laws of the mutual interactions of objects bound to cell membranes, such as various membrane proteins or elongated virus particles? To rationalise this, we here investigate by extensive computer simulations mutual interactions of rod-like particles adsorbed on the surface of responsive elastic two-dimensional sheets. Specifically, we quantify sheet deformations as a response to adhesion of such filamentous particles. We demonstrate that tip-to-tip contacts of rods are favoured for relatively soft sheets, while side-by-side contacts are preferred for stiffer elastic substrates. These attractive orientation-dependent substrate-mediated interactions between the rod-like particles on responsive sheets can drive their aggregation and self-assembly. The optimal orientation of the membrane-bound rods is established via responding to the elastic energy profiles created around the particles. We unveil the phase diagramme of attractive-repulsive rod-rod interactions in the plane of their separation and mutual orientation. Applications of our results to other systems featuring membrane-associated particles are also discussed.

Non-universal tracer diffusion in crowded media of non-inert obstacles.

We study the diffusion of a tracer particle, which moves in continuum space between a lattice of excluded volume, immobile non-inert obstacles. In particular, we analyse how the strength of the tracer-obstacle interactions and the volume occupancy of the crowders alter the diffusive motion of the tracer. From the details of partitioning of the tracer diffusion modes between trapping states when bound to obstacles and bulk diffusion, we examine the degree of localisation of the tracer in the lattice of crowders. We study the properties of the tracer diffusion in terms of the ensemble and time averaged mean squared displacements, the trapping time distributions, the amplitude variation of the time averaged mean squared displacements, and the non-Gaussianity parameter of the diffusing tracer. We conclude that tracer-obstacle adsorption and binding triggers a transient anomalous diffusion. From a very narrow spread of recorded individual time averaged trajectories we exclude continuous type random walk processes as the underlying physical model of the tracer diffusion in our system. For moderate tracer-crowder attraction the motion is found to be fully ergodic, while at stronger attraction strength a transient disparity between ensemble and time averaged mean squared displacements occurs. We also put our results into perspective with findings from experimental single-particle tracking and simulations of the diffusion of tagged tracers in dense crowded suspensions. Our results have implications for the diffusion, transport, and spreading of chemical components in highly crowded environments inside living cells and other structured liquids.

Deformation propagation in responsive polymer network films.

We study the elastic deformations in a cross-linked polymer network film triggered by the binding of submicron particles with a sticky surface, mimicking the interactions of viral pathogens with thin films of stimulus-responsive polymeric materials such as hydrogels. From extensive Langevin Dynamics simulations we quantify how far the network deformations propagate depending on the elasticity parameters of the network and the adhesion strength of the particles. We examine the dynamics of the collective area shrinkage of the network and obtain some simple relations for the associated characteristic decay lengths. A detailed analysis elucidates how the elastic energy of the network is distributed between stretching and compression modes in response to the particle binding. We also examine the force-distance curves of the repulsion or attraction interactions for a pair of sticky particles in the polymer network film as a function of the particle-particle separation. The results of this computational study provide new insight into collective phenomena in soft polymer network films and may, in particular, be applied to applications for visual detection of pathogens such as viruses via a macroscopic response of thin films of cross-linked hydrogels.

From chemosensing in microorganisms to practical biosensors.

Microorganisms like bacteria can sense concentrations of chemoattractants in their medium very accurately. They achieve this through interaction between the receptors on their cell surfaces and chemoattractant molecules (like sugar). Physical processes like diffusion set some limits on the accuracy of detection, which was discussed by Berg and Purcell in the late seventies. We re-examine their work in order to assess what insight it may offer for making efficient, practical biosensors. We model the functioning of a typical biosensor as a reaction-diffusion process in a confined geometry. Using available data first we characterize the system by estimating the kinetic constants for the binding and unbinding reactions between the chemoattractants and the receptors. Then we compute the binding flux for this system, which Berg and Purcell had discussed. Unlike in microorganisms where the interval between successive measurements determines the efficiency of the nutrient searching process, it turns out that biosensors depend on long time properties like signal saturation time, which we study in detail. We also develop a mean field description of the kinetics of the system.

Effect of intrinsic curvature on semiflexible polymers.

Recently many important biopolymers have been found to possess intrinsic curvature. Tubulin protofilaments in animal cells, FtsZ filaments in bacteria and double stranded DNA are examples. We examine how intrinsic curvature influences the conformational statistics of such polymers. We give exact results for the tangent-tangent spatial correlation function C(r)=, both in two and three dimensions. Contrary to expectation, C(r) does not show any oscillatory behavior, rather decays exponentially and the effective persistence length has strong length dependence for short polymers. We also compute the distribution function P(R) of the end to end distance R and show how curved chains can be distinguished from wormlike chains using loop formation probability.