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Results for “biophysics”

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At least 235 records · Page 13Linked to original sources

bioRxiv2026

Biophysical resetting of specialization drives evolutionary diversification of a metabolic network

Organisms must integrate external inputs whose availability they do not control into internal functions that require precision. Birds exemplify this challenge: they cannot synthesize carotenoids, yet closely integrate diet-derived carotenoids into vision, pigmentation and yolk provisioning, raising the question of how unpredictability of external supply coevolves with precision of internal use. Here we analyze 32 core carotenogenesis proteins across 172 bird species and show that the resolution is a biophysical bow-tie: ordered, self-attracting complexes of absorption and enzymatic conversion proteins are linked by a hub of disordered, phase-separating and self-avoiding carriers that consistently resets the propagation of specialization. Across species, the specialization-resetting properties of these carriers and not the changes in conserved absorption or enzymatic complexes drive metabolic network diversification by inducing metabolic branching rather than by accumulating dietary carotenoid-specific paths. By decoupling the upstream origin of inputs from their downstream routing, this biophysical bow-tie architecture explains three defining features of avian carotenogenesis: physiological sensitivity, openness to novel inputs, and the internalization of control required for precise internal functions. Non-specific carriers thus produce specific outcomes, sustaining the connectivity and remarkable diversification of a metabolic network built entirely on an unpredictable external resource.

evolutionary biology↗

bioRxiv2026

Slow Ionic Dynamics Reshape Bistability in a Biophysical Mean-Field Model of Brain Activity

Brain states such as sleep, seizures, and resting wakefulness are often described in terms of transitions between distinct population states. Biophysically inspired mean-field models that couple neuronal firing statistics to slow ionic homeostasis provide a mechanistic bridge between detailed single-neuron physiology and macroscopic brain activity. Here we examine this issue in a biophysical mean-field model of cortical populations driven by potassium exchange and compare its dynamical repertoire with a matched spiking network across six physiological and pathological regimes. The fast subsystem contains a substantial region in which low- and high-activity fixed points coexist, but this conditional bistability is not inherited by the physiological resting branch of the complete slow-fast system. A generic fast-slow calculation identifies how feedback through a dynamical ionic variable changes the stability conditions of the fast subsystem, and an exact equilibrium reduction of the KIonEx-MF equations yields a single equilibrium on the physiological resting branch over the range examined. This resting state is excitable: perturbations generate intermittent synchronized events in both the mean-field and spiking-network descriptions. The results show how slow ionic dynamics can reshape conclusions drawn from a frozen fast subsystem and provide noise-driven excitability as an alternative route to spontaneous population transitions.

neuroscience↗

bioRxiv2016

Biophysical properties of human β-cardiac myosin with converter mutations that cause hypertrophic cardiomyopathy

Hypertrophic cardiomyopathy (HCM) affects 1 in 500 individuals and is an important cause of arrhythmias and heart failure. Clinically, HCM is characterized as causing hyper-contractility, and therapies are aimed toward controlling the hyperactive physiology. {beta}-cardiac myosin comprises ~40 percent of genetic mutations associated with HCM and the converter domain of myosin is a hot spot for HCM-causing mutations, but the underlying primary effects of these mutations on myosin's biomechanical function remain elusive. We hypothesize that these mutations affect the biomechanical properties of myosin, such as increasing its intrinsic force and/or its duty ratio and therefore the ensemble force of the sarcomere. Using recombinant human {beta}-cardiac myosin, we characterize the molecular effects of three severe HCM-causing converter domain mutations R719W, R723G and G741R. Contrary to our hypothesis, the intrinsic forces of R719W and R723G mutant myosins are decreased compared to wild type, and unchanged for G741R. Actin and regulated thin filament gliding velocities are ~15 percent faster for R719W and R723G myosin, while there is no change in velocity for G741R. ATPase activities and the load-dependent velocity change profiles of all three mutant proteins are very similar to wild type. These results indicate that the net biomechanical properties of human {beta}-cardiac myosin carrying these converter domain mutations are very similar to wild type or even slightly hypo-contractile, leading us to consider an alternative mechanism for the clinically observed hyper-contractility. Future work includes how these mutations affect protein interactions within the sarcomere that increase the availability of myosin heads participating in force production.\n\nOne Sentence Summary: Biophysical analysis of human {beta} -cardiac myosin with converter domain HCM mutations reveal minimal changes compared to wild type myosin to slightly hypo-contractile profiles in ensemble force production, in contrast to the clinically observed hyper-contractility, leading to a speculative alternative mechanism involving availability of myosin heads participating in the sarcomere.

Biophysics↗

bioRxiv2017

Biophysical determinants of mutational robustness in a viral molecular fitness landscape

Biophysical interactions between proteins and peptides are key determinants of genotype-fitness landscapes, but an understanding of how molecular structure and residue-level energetics at protein-peptide interfaces shape functional landscapes remains elusive. Combining information from yeast-based library screening, next-generation sequencing and structure-based modeling, we report comprehensive sequence-energetics-function mapping of the specificity landscape of the Hepatitis C Virus (HCV) NS3/4A protease, whose function -- site-specific cleavages of the viral polyprotein -- is a key determinant of viral fitness. We elucidate the cleavability of 3.2 million substrate variants by the HCV protease and find extensive clustering of cleavable and uncleavable motifs in sequence space indicating mutational robustness, and thereby providing a plausible molecular mechanism to buffer the effects of low replicative fidelity of this RNA virus. Specificity landscapes of known drug-resistant variants are similarly clustered. Our results highlight the key and constraining role of molecular-level energetics in shaping plateau-like fitness landscapes from quasispecies theory.

biophysics↗

bioRxiv2020

The control of acidity in tumor cells: a biophysical model

Acidosis of the tumor microenvironment leads to cancer invasion, progression and resistance to therapies. We present a biophysical model that describes how tumor cells regulate intracellular and extracellular acidity while they grow in a microenvironment characterized by increasing acidity and hypoxia. The model takes into account the dynamic interplay between glucose and O2 consumption with lactate and CO2 production and connects these processes to H+ and [Formula] fluxes inside and outside cells. We have validated the model with independent experimental data and used it to investigate how and to which extent tumor cells can survive in adverse micro-environments characterized by acidity and hypoxia. The simulations show a dominance of the H+ exchanges in well-oxygenated regions, and of [Formula] exchanges in the inner hypoxic regions where tumor cells are known to acquire malignant phenotypes. The model also includes the activity of the enzyme Carbonic Anhydrase 9 (CA9), a known marker of tumor aggressiveness, and the simulations demonstrate that CA9 acts as a nonlinear pHi equalizer at any O2 level in cells that grow in acidic extracellular environments. SIGNIFICANCEThe activity of cancer cells in solid tumors affects the surrounding environment in many ways, and an elevated acidity is a common feature of the tumor microenvironment. In this paper we propose a model of intracellular/extracellular acidity that is linked to cellular metabolism and includes all the main molecular players. The model is reliable, robust and validated with experimental data and can be used as an essential building block of more comprehensive in silico research on solid tumors.

biophysics↗

bioRxiv2020

Estimating the Probability of Cellular Arrhythmias with Simplified Statistical Models that Account for Experimentally Observed Uncertainty in Underlying Biophysical Mechanisms

Early after-depolarizations (EADs) are action potential (AP) repolarization abnormalities that can trigger lethal arrhythmias. Simulations using biophysically-detailed cardiac myocyte models can reveal how model parameters influence the probability of these cellular arrhythmias, however such analyses can pose a huge computational burden. We have previously developed a highly simplified approach in which logistic regression models (LRMs) map parameters of complex cell models to the probability of ectopic beats (EBs). Here, we extend this approach to predict the probability of early after-depolarizations (P(EAD)). We use the LRM to investigate how changes in parameters of the slow-activating delayed rectifier current (IKs) affect P(EAD) for 17 different Long QT syndrome type 1 (LQTS1) mutations. We compare P(EAD) for these 17 LQTS1 mutations with two other recently proposed model-based arrhythmia risk metrics. These three model-based risk metrics yield similar prediction performance; however, they all fail to predict relative clinical risk for a significant number of the 17 studied LQTS1 mutations. The consistent successes and failures of all three risk metrics suggest that important functional characteristics of LQTS1 mutations may not yet be fully known. Author summaryAn early after-depolarization (EAD) is an abnormal cellular electrical event which can trigger dangerous arrhythmias in the heart. We use our previously developed method to build a simple logistic regression model (LRM) that estimates the probability of EAD (P(EAD)) as a function of myocyte model parameters. Using this LRM along with two other recently published model-based arrhythmia risk predictors, we estimate risk of arrhythmia for 17 Long QT syndrome type 1 (LQTS1) mutations. Results show that all approaches have similar prediction performance in that there are a set of mutations whose relative clinical risk for arrhythmia are well estimated using these metrics, but that relative risk is consistently over- or under-estimated across all approaches for a significant number of other mutations. We believe this indicates that the functional characterization of the LQTS1 phenotype is incomplete.

biophysics↗

bioRxiv2020

A Minimal Biophysical Model of Combined Antibiotic Action

Phenomenological relations such as Ohms or Fouriers law have a venerable history in physics, but are still scarce in biology. This situation restrains predictive theory. Here, we build on bacterial "growth laws," which capture physiological feedback between translation and cell growth, to construct a minimal biophysical model for the combined action of ribosome-targeting antibiotics. Our model predicts drug interactions like antagonism or synergy solely from responses to individual drugs. We systematically refine the model by including direct physical interactions of different drugs on the ribosome. In a limiting case, our model provides a mechanistic underpinning for recent predictions of higher-order interactions derived using entropy maximization. It further makes parameter-free predictions for combined drug effects on cells carrying resistance genes and for drugs that mimic poor nutrient environments. We show experimentally that resistance genes can drastically alter drug interactions in notable agreement with our theoretical predictions. While minimal, the model is readily adaptable and opens the door to predicting interactions of second and higher-order in a broad range of biological systems.

biophysics↗

bioRxiv2020

A simple description of biological transmembrane potential from simple biophysical considerations: no equivalent circuits

Biological membranes mediate different physiological processes necessary for life. Ion movement around, into and out of cells, is arguably one of the most important of such processes, as it underlies electrical signalling and communication within and between cells. The difference between the electrical potentials inside and outside a biological membrane, called transmembrane potential, or membrane potential for short, is one of the main biophysical variables affecting ionic movement. Most of the equations that describe the change in membrane potential are based on analogies with resistive-capacitative electrical circuits, with conductance and capacitance proposed in classical studies as measures of the permeable and the impermeable properties of the membrane, respectively. However, the parts in ohmic circuits are not like the biological elements present in the spaces around and within biological membranes. This article presents a simple derivation for an equation describing local changes in transmembrane potential that is not based on electrical circuit analogies. In doing so, concepts like the so-called "membrane capacitance" are explained and generalized. Importantly, the classical model for the membrane potential based on an equivalent RC-circuit is recovered as particular case from the general derivation presented here. Modeling examples are presented to illustrate the use of the derivation and the effects of changing the way charges aggregate around the membrane as a function of the membrane potential.

biophysics↗

bioRxiv2020

A Biophysical Model for Plant Cell Plate Development

Plant cytokinesis, a fundamental process of plant life, involves de novo formation of a cell plate that partitions the cytoplasm of the dividing cell. Cell plate formation is directed by orchestrated delivery, fusion of cytokinetic vesicles, and membrane maturation to the form the nascent cell wall by the timely deposition of polysaccharides such as callose, cellulose, and crosslinking glycans. In contrast to the role of endomembrane protein regulators the role of polysaccharides, in cell plate development is poorly understood. Callose, a {beta}-1-3 glucan polymer, is transiently accumulated during cell plate expansion to be replaced by cellulose in mature stages. Based on the severity of cytokinesis defects in the absence of callose, it has been proposed that it stabilizes this membrane network structure. However, there is currently no theory to understand its role in cytokinesis. Here we extend the Helfrich free energy model for membranes including a phenomenological spreading force as an "areal pressure" generated by callose and/or other polysaccharides. Regular cell plate development in the model is possible, with suitable bending modulus, for a two-dimensional late stage spreading force parameter of between 2-6pN/nm, an osmotic pressure difference of 2-10kPa, and spontaneous curvature between 0-0.04nm-1. With these conditions, stable membrane conformation sizes and morphologies emerge in concordance with stages of cell plate development. With no spreading force, the cell plate fails to mature properly, corroborating experimental observations of cytokinesis arrest in the absence of callose. To reach a nearly mature cell plate, our model requires the late stage onset that the spreading force coupled with a concurrent loss of spontaneous curvature. A simple model based upon production of callose as a quasi-two-dimensional self-avoiding polymer produces the correct phenomenological form of the spreading force, which will be further refined, since matching to our numbers requires an exceptionally high callose synthesis rate. Significance StatementPlant cell division features the development of a unique membrane network called the cell plate that matures to a cell wall which separates the two daughter cells. During cell plate development, callose, a {beta}-1-3 glucan polymer, is transiently synthesized at the cell plate only to be replaced by cellulose in mature stages. The role for this transient callose accumulation at the cell plate is unknown. It has been suggested that callose provides mechanical stability, as well as a spreading force that widens and expands tubular and fenestrated cell plate structures to aid the maturation of the cell plate. Chemical inhibition of callose deposition results in the failure of cell plate development supporting this hypothesis. This publication establishes the need for a spreading force in cell plate development using a biophysical model that predicts cell plate development in the presence and the absence of this force. Such models can potentially be used to decipher for the transition/maturation of membrane networks upon the deposition of polysaccharide polymers.

biophysics↗

bioRxiv2020

Biophysical characterization of the inactivation of E. coli transketolase by aqueous co-solvents

Transketolase (TK) has been previously engineered, using semi-rational directed evolution and substrate walking, to accept increasingly aliphatic, cyclic and then aromatic substrates. This has ultimately led to the poor water solubility of new substrates, as a potential bottleneck to further exploitation of this enzyme in biocatalysis. Here we used a range of biophysical studies to characterise the response of both E. coli apo- and holo-TK activity and structure to a range of commonly used polar organic co-solvents: acetonitrile (MeCN), n- butanol (nBuOH), ethyl acetate (EToAc), isopropanol (iPrOH), and tetrahydrofuran (THF). The mechanism of enzyme deactivation was found to be predominantly via solvent-induced local unfolding. Holo-TK is thermodynamically more stable than apo-TK and yet for four of the five co-solvents it retained less activity than apo-TK after exposure to organic solvents, indicating that solvent tolerance was not correlated to global conformational stability. The co-solvent concentrations required for complete enzyme inactivation was inversely proportional to co-solvent log(P), while the unfolding rate was directly proportional, indicating that the solvents interact with and partially unfold the enzyme through hydrophobic contacts. Aggregation was not found to be the driving mechanism of enzyme inactivation, but was in some cases an additional impact of solvent-induced local or global unfolding. TK was found to be tolerant to 15% (v/v) iPrOH, 10% (v/v) MeCN, or 6% (v/v) nBuOH over 3 hours. This work indicates that future attempts to engineer the enzyme to better tolerate co-solvents should focus on increasing the stability of the protein to local unfolding, particularly in and around the cofactor-binding loops.

biophysics↗

bioRxiv2020

Integrating deep learning with microfluidics for biophysical classification of sickle red blood cells

Sickle cell disease (SCD), a group of inherited blood disorders with significant morbidity and early mortality, affects a sizeable global demographic largely of African and Indian descent. It is manifested in a mutated form of hemoglobin that distorts the red blood cells into a characteristic sickle shape with altered biophysical properties. Sickle red blood cells (sRBCs) show heightened adhesive interactions with inflamed endothelium, triggering obstruction of blood vessels and painful vaso-occlusive crisis events. Numerous studies have reported microfluidic-assay-based disease monitoring tools which rely on quantifying adhesion characteristics of adhered sRBCs from high resolution channel images. The current workflow for analyzing images from these assays relies on manual cell counting and detailed morphological characterization by a specially trained worker, which is time and labor intensive. Moreover manual counts by different individuals are prone to artifacts due to user bias. We present here a standardized and reproducible image analysis workflow designed to tackle these issues, using a two part deep neural network architecture that works in tandem for automatic, fast and reliable segmentation and classification into subtypes of adhered cell images. Our training utilized an exhaustive data set of images generated by the SCD BioChip, a microfluidic assay which injects clinical whole blood samples into protein-functionalized microchannels, mimicking physiological conditions in the microvasculature. The automated image analysis performs robustly in comparison to human classification: accuracies were similar to or better than those of the trained personnel, while the overall analysis time was improved by two orders of magnitude.Competing Interest StatementThe authors have declared no competing interest.View Full Text

biophysics↗

bioRxiv2020

Biophysical and dynamic characterization of a fine-tuned binding of the human Respiratory Syncytial Virus M2-1 core domain to long RNAs

The human Respiratory Syncytial Virus (hRSV) M2-1 protein functions as a processivity and antitermination factor of the viral polymerase complex. Here it is presented the first evidence that hRSV M2-1 core domain (cdM2-1) alone has an unfolding activity for long RNAs, as well as a biophysical and dynamic characterization of the cdM2-1/RNA complex. The main contact region of cdM2-1 with RNA was the 1-2-5-6 helix bundle, which suffered local conformational changes and promoted the RNA unfolding activity. This activity may be triggered by base-pairing recognition. RNA molecules wrap around the whole cdM2-1, protruding their terminals over the domain. The 2-3 and 3-4 loops of cdM2-1 were marked by an increase in picosecond internal motions upon RNA binding even though they are not directly involved in the interaction. The results revealed that the cdM2-1/RNA complex originates from a fine-tuned binding, contributing to unraveling interaction aspects necessary to M2-1 activity. IMPORTANCEThe main outcome is the molecular description of a fine-tuned binding of the cdM2-1/RNA complex and the evidence that the domain alone has an unfolding activity for long RNAs. This binding mode is essential in the understanding of the function in the full-length protein. Orthopneumovirus, as the human Respiratory Syncytial Virus (hRSV), stands out for the unique role of M2-1 as a transcriptional antitermination factor able to increase the RNA polymerase processivity.

biophysics↗

bioRxiv2020

Biophysical characterization of two commercially available preparations of the drug containing Escherichia coli L-Asparaginase 2

The hydrolysis of asparagine and glutamine by L-asparaginase has been used to treat acute lymphoblastic leukemia for over four decades. Each L-asparaginase monomer has a long loop that closes over the active site upon substrate binding, acting as a lid. Here we present a comparative study two commercially available preparations of the drug containing Escherichia coli L-Asparaginase 2, performed by a comprehensive array of biophysical and biochemical approaches. We report the oligomeric landscape and conformational and dynamic plasticity of E. coli type 2 L-asparaginase (EcA2) present in two different formulations, and its relationship with L-aspartic acid, which is present in Aginasa, but not in Leuginase. EcA2 shows a composition of monomers and oligomers up to tetramers, which is mostly not altered in the presence of L-Asp. The N-terminal loop of Leuginase, which is part of the active site is flexibly disordered, but gets ordered as in Aginasa in the presence os L-Asp, while L-Glu only does so to a limited extent. Ion-mobility spectrometry-mass spectrometry reveals two conformers for the monomeric EcA2, one of which can selectively bind to L-Asp and L-Glu. Aginasa has higher resistance to in vitro proteolysis than Leuginase, and this is directly related to the presence of L-Asp.

biophysics↗

bioRxiv2020

Biochemical and Biophysical Characterization of the dsDNA packaging motor from the Lactococcus lactis bacteriophage asccphi28

Double-stranded DNA viruses package their genomes into pre-assembled protein procapsids. This process is driven by macromolecular motors that transiently assemble at a unique vertex of the procapsid and utilize homomeric ring ATPases to couple genome encapsidation to ATP hydrolysis. Here we describe biochemical and biophysical characterization of the packaging ATPase from Lactococcus lactis phage ascc{varphi}28. Size-exclusion chromatography, analytical ultracentrifugation, small angle x-ray scattering, and negative stain TEM indicate that the ~45 kDa protein formed a 443 kDa cylindrical assembly with a maximum dimension of ~155 [A] and radius of gyration of ~54 [A]. Together with the dimensions of the crystallographic asymmetric unit from preliminary X-ray diffraction experiments, these results indicate that gp11 forms a decameric D5-symmetric complex consisting of two pentameric rings related by 2-fold symmetry. Additional kinetic analysis shows that recombinantly expressed gp11 has ATPase activity comparable to that of functional ATPase rings assembled on procapsids in other genome packaging systems. Hence, gp11 forms rings in solution that likely reflect the fully assembled ATPases in active virus-bound motor complexes. Whereas ATPase functionality in other dsDNA phage packaging systems requires assembly on viral capsids, the ability to form functional rings in solution imparts gp11 with significant advantages for high resolution structural studies and rigorous biophysical/biochemical analysis.

biophysics↗

bioRxiv2020

The effect of acidic pH on the interaction and lytic activity of MP1 and its H-MP1 analog in anionic lipid membrane: a biophysical study by Molecular Dynamics and Spectroscopy

Antimicrobial peptides (AMPs) are part of the innate immune system of many species and are compounds with potential application against the development of resistant bacterial strains promoted by conventional antibiotics. The AMPs are rich in cationic and hydrophobic residues and act directly on the lipidic phase of the cell membranes. The MP1 has a broad-spectrum bactericide activity in both Gram-negative and positive bacteria, not being hemolytic or cytotoxic. H-MP1 is a synthetic analog of MP1 with lysines replaced by histidines so that its net charge could be responsive to changes in solution pH. In the present work, we investigated the effect of the solution pH on the structural properties, in the adsorption and insertion, and on the lytic activity of these peptides in lipid bilayers mimicking the cell membrane of Gram-negative bacteria, using experimental and computational biophysical techniques. The results indicate that the lytic activity of H-MP1 is sensitive to pH, increasing to an acidic environment, matching that of MP1, which is not influenced by solution pH. Molecular Dynamic simulations indicated that the adsorption process of both peptides started by the interaction of the N-terminus with the bilayer, followed by the complete adsorption of the peptide laying parallel to the bilayer plane, inducing an increase in the peptides helical content enhancing peptides contact with the bilayer hydrophobic phase.

biophysics↗

bioRxiv2020

Structural and biophysical characterization of the tandem substrate-binding domains of the ABC importer GlnPQ

The ATP-binding cassette transporter GlnPQ is an essential uptake system that transports glutamine, glutamic acid, and asparagine in Gram-positive bacteria. It features two extracytoplasmic substrate-binding domains (SBDs) that are linked in tandem to the transmembrane domain of the transporter. The two SBDs differ in their ligand specificities, binding affinities and their distance to the transmembrane domain. Here, we elucidate the effects of the tandem arrangement of the domains on the biochemical, biophysical and structural properties of the protein. For this, we determined the crystal structure of the ligand-free tandem SBD1-2 protein from L. lactis in the absence of the transporter and compared the tandem to the isolated SBDs. We also used isothermal titration calorimetry to determine the ligand-binding affinity of the SBDs and single-molecule Forster-resonance energy transfer (smFRET) to relate ligand binding to conformational changes in each of the domains of the tandem. We show that substrate binding and conformational changes are not notably affected by the presence of the adjoining domain in the wild-type protein, and changes only occur when the linker between the domains is shortened. In a proof-of-concept experiment, we combine smFRET with protein-induced fluorescence enhancement and show that a decrease in SBD linker length is observed as a linear increase in donor-brightness for SBD2 while we can still monitor the conformational states (open/closed) of SBD1. These results demonstrate the feasibility of PIFE-FRET to monitor protein-protein interactions and conformational states simultaneously. HIGHLIGHTSO_LIResolved crystal structure of tandem SBD1-2 of GlnPQ from Lactococcus lactis C_LIO_LIConformational states and ligand binding affinities of individual domains SBD1 and SBD2 are similar to tandem SBD1-2 C_LIO_LINo cooperative effects are seen for different ligands for SBDs in the tandem C_LIO_LIProof of concept experiments show that PIFE-FRET can monitor SBD conformations and protein-protein interaction simultaneously C_LI O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=142 SRC="FIGDIR/small/423572v1_ufig1.gif" ALT="Figure 1"> View larger version (87K): org.highwire.dtl.DTLVardef@1fa36f7org.highwire.dtl.DTLVardef@2e973forg.highwire.dtl.DTLVardef@cbae51org.highwire.dtl.DTLVardef@2185cc_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2021

Biophysical characterization of the SARS-CoV-2 E protein

SARS-CoV-2 contains four structural proteins in its genome. These proteins aid in the assembly and budding of new virions at the ER-Golgi intermediate compartment (ERGIC). Current fundamental research efforts largely focus on one of these proteins - the spike (S) protein. Since successful antiviral therapies are likely to target multiple viral components, there is considerable interest in understanding the biophysical role of its other structural proteins, in particular structural membrane proteins. Here, we have focused our efforts on the characterization of the full-length envelope (E) protein from SARS-CoV-2, combining experimental and computational approaches. Recombinant expression of the full-length E protein from SARS-CoV-2 reveals that this membrane protein is capable of independent multimerization, possibly as a tetrameric or smaller species. Fluorescence microscopy shows that the protein localizes intracellularly, and coarse-grained MD simulations indicate it causes bending of the surrounding lipid bilayer, corroborating a potential role for the E protein in viral budding. Although we did not find robust electrophysiological evidence of ion-channel activity, cells transfected with the E protein exhibited reduced intracellular Ca2+, which may further promote viral replication. However, our atomistic MD simulations revealed that previous NMR structures are relatively unstable, and result in models incapable of ion conduction. Our study highlights the importance of using high-resolution structural data obtained from a full-length protein to gain detailed molecular insights, and eventually permitting virtual drug screening.

biophysics↗

bioRxiv2021

Biophysical Models of PAR Cluster Transport by Cortical Flow in C. elegans Early Embryogenesis

The clustering of membrane-bound proteins facilitates their transport by cortical actin flow in early Caenorhabditis elegans embryo cell polarity. PAR-3 clustering is critical for this process, yet the bio-physical processes that couple protein clusters to cortical flow remain unknown. We develop a discrete, stochastic agent-based model of protein clustering and test four hypothetical models for how clusters may interact with the flow. Results show that the canonical way to assess transport characteristics from single particle tracking data used thus far in this area, the Peclet number, is insufficient to distinguish these hypotheses and that all models can account for transport characteristics quantified by this measure. However, using this model, we demonstrate that these different cluster-cortex interactions may be distinguished using a different metric, namely, the scalar projection of cluster displacement on to the flow displacement vector. Our results thus provide a testable way to use existing single particle tracking data to test how endogenous protein clusters may interact with the cortical flow to localize during polarity establishment. To facilitate this investigation, we also develop both improved simulation and semi-analytic methodologies to quantify motion summary statistics (e.g., Peclet number and scalar projection) for these stochastic models as a function of biophysical parameters.

biophysics↗