Biophysical journal最新文献

The polymerization of cytoskeletal filaments is regulated by both biochemical pathways, as well as physical factors such as crowding. The effect of crowding in vivo emerges from the density of intracellular components. Due to the complexity of the intracellular environment, most studies are based on either in vitro reconstitution or theory. Crowding agent (crowdants) size has been shown to influence polymerization of both actin and microtubules (MTs). Previously, the elongation rates of MT dynamics observed at single filament scale were reported to decrease with increasing concentrations of small but not large crowdants, and this correlated with in vivo viscosity increases. However, the exact nature of the connection between viscosity, crowdant size, nucleation and MT elongation has remained unclear. Here, we use in vitro reconstitution of bulk MT polymerization kinetics and microscopy to examine the collective effect of crowdant molecular weight, volume occupancy and viscosity on elongation and spontaneous polymerization. We find MT elongation rates obtained from bulk polymerization decrease in presence of multiple low molecular weight (LMW) crowdants, while increasing with high molecular weight (HMW) crowdants. Lattice Monte Carlo simulations of an effective model of collective polymerization demonstrate reduced polymerization rates arise due to decrease in monomer diffusion due to small sized crowdants. However, MT polymerization in the absence of nucleators, de novo, shows a crowdant size-independence of polymerization rate and critical concentration, depending solely on concentration of the crowdant. In microscopy, we find LMW crowdants result in short but many filaments, while HMW crowdants increase filament density, but have little effect on lengths. The effect of crowdant volume fraction ϕ_c and size in de novo polymerization match simulations, demonstrating crowdants affect elongation independent of nucleation. Thus, the effect of viscosity on collective MT dynamics, i.e. filament numbers and lengths, shows crowdant size dependence for elongation, but independence for de novo polymerization.

In the field of drug discovery, the generation of new molecules with desirable properties remains a critical challenge. Traditional methods often rely on SMILES (Simplified Molecular Input Line Entry System) representations for molecular input data, which can limit the diversity and novelty of generated molecules. To address this, we present the Transformer Graph Variational Autoencoder (TGVAE), an innovative AI model that employs molecular graphs as input data, thus captures the complex structural relationships within molecules more effectively than string models. To enhance molecular generation capabilities, TGVAE combines a Transformer, Graph Neural Network (GNN), and Variational Autoencoder (VAE). Additionally, we address common issues like over-smoothing in training GNNs and posterior collapse in VAE to ensure robust training and improve the generation of chemically valid and diverse molecular structures. Our results demonstrate that TGVAE outperforms existing approaches, generating a larger collection of diverse molecules and discovering structures that were previously unexplored. This advancement not only brings more possibilities for drug discovery but also sets a new level for the use of AI in molecular generation.

Synaptic morphology plays a critical role in modulating the dynamics of neurotransmitter diffusion and receptor activation in interneuron communication. Central physical aspects of synaptic geometry, such as the curvature of the synaptic cleft, the distance between the presynaptic and postsynaptic membranes, and the surface area-to-volume ratio of the cleft, crucially influence glutamate diffusion and N-Methyl-D-Aspartate receptor (NMDAR) opening probabilities. In this study, we developed a stochastic model for receptor activation using realistic synaptic geometries. Our simulations revealed substantial variability in NMDAR activation, showing the significant impact of synaptic structure on receptor activation. Next, we designed a theoretical study with idealized cleft geometries to understand the impact of different biophysical properties on receptor activation. Specifically, we found that increasing the curvature of the synaptic membranes could compensate for reduced NMDAR activation when the synaptic cleft width was large. Additionally, non-parallel membrane configurations, such as convex presynapses or concave postsynaptic densities (PSDs), maximize NMDAR activation by increasing the surface area-to-volume ratio, thereby increasing glutamate residence time and reducing glutamate escape. Furthermore, clustering NMDARs within the PSD significantly increased receptor activation across different geometric conditions and mitigated the effects of synaptic morphology on NMDAR opening probabilities. These findings highlight the complex interplay between synaptic geometry and receptor dynamics and provide important insights into how structural modifications can influence synaptic efficacy and plasticity. By considering the major physical factors that affect neurotransmitter diffusion and receptor activation, our work offers a comprehensive understanding of how variations in synaptic geometry regulate neurotransmission.

We present a model to describe the concentration-dependent growth of protein filaments. Our model contains two states, a low entropy/high affinity ordered state and a high entropy/low affinity disordered state. Consistent with experiments, our model shows a diffusion-limited linear growth regime at low concentration, followed by a concentration-independent plateau at intermediate concentrations, and rapid disordered precipitation at the highest concentrations. We show that growth in the linear and plateau regions is the result of two processes that compete amid the rapid binding and unbinding of non-specific states. The first process is the addition of ordered molecules during periods in which the end of the filament is free of incorrectly bound molecules. The second process is the capture of defects, which occurs when consecutive ordered additions occur on top of incorrectly bound molecules. We show that a key molecular property is the probability that a diffusive collision results in a correctly bound state. Small values of this probability suppress the defect capture growth mode, resulting in a plateau in the growth rate when incorrectly bound molecules become common enough to poison ordered growth. We show that conditions that non-specifically suppress or enhance intermolecular interactions, such as the addition of depletants or osmolytes, have opposite effects on the growth rate in the linear and plateau regimes. In the linear regime, stronger interactions promote growth by reducing dissolution events, but in the plateau regime stronger interactions inhibit growth by stabilizing incorrectly bound molecules.

Membrane fusion is central to fundamental cellular processes such as exocytosis, when an intracellular machinery fuses membrane-enclosed vesicles to the plasma membrane for contents release. The core machinery components are the SNARE proteins. SNARE complexation pulls the membranes together, but the fusion mechanism remains unclear. A common view is that the complexation energy drives fusion, but how this energy is harvested for fusion is unexplained. Moreover, SNAREs likely fully assemble before fusion. Computer simulation is challenging, since even fast neurotransmitter release at neuronal synapses involves fusion on ms timescales, beyond the scope of atomistic or mildly coarse-grained approaches. Here we used highly coarse-grained representations, allowing simulation of the ms timescales of physiological SNARE-driven fusion under physiological conditions. Due to constant collisions, the rodlike SNARE complexes spontaneously generated entropic forces ∼ 8 pN per SNARE that cleared the fusion site and squeezed the membranes with forces ∼ 19 pN per SNARE, catalyzing a hemifused stalk connection. Regrouping, five or more SNARE complexes exerted entropic tensions 3 pN/nm or greater, expanding the stalk into a hemifusion diaphragm (HD) followed by HD rupture and fusion. The entropic forces generated tensions ∼ 17-21 pN in the SNARE linker domains (LDs). Previous optical tweezer measurements suggest, on the ms timescales of fusion, these LD tensions are sufficient to unzipper the LDs while leaving the C-terminal domain (CTD) marginally intact, both required for fusion. Consistent with a recent magnetic tweezers study, we propose the CTD may be further stabilized by complexin for robust fusion. Our results explain how SNARE-generated forces fuse membranes, and predict that more SNARE complexes exert higher net force so fusion is faster, consistent with experimental electrophysiological studies at neuronal synapses. Thus, entropic forces evolve SNARE complexes into a fusogenic partially unzippered state, squeeze membranes for hemifusion, and expand hemifusion connections for fusion.

The Hsp100 family of protein disaggregases play important roles in maintaining protein homeostasis in cells. E. coli ClpB is an Hsp100 protein that solubilizes protein aggregates. ClpB is proposed to couple the energy from ATP binding and hydrolysis to processively unfold and translocate protein substrates through its axial channel in the hexameric ring structure. However, many of the details of this reaction remain obscure. We have recently developed a transient state kinetics approach to study ClpB catalyzed protein unfolding and translocation. In the work reported here we have used the approach to examine how ATP is coupled to the protein unfolding reaction. Here we show that at saturating [ATP], ClpB induces the cooperative unfolding of a complete TitinI27 domain of 98 amino acids, which is represented by our measured kinetic step-size m ∼100 amino acids. This unfolding event is followed by rapid and undetected translocation up to the next folded domain. At sub-saturating [ATP], ClpB induces cooperative unfolding of a complete TitinI27 domain but translocation becomes partially rate-limiting, which leads to an apparent reduced kinetic step-size as small as ∼ 50 amino acids. Further, we show that ClpB exhibits an unfolding processivity of P = (0.74 ± 0.06) independent of [ATP]. These findings advance our understanding of the ATP coupling to enzyme catalyzed protein unfolding by E. coli ClpB and present a strategy that is broadly applicable to a variety of Hsp100 family members and AAA+ superfamily members.

Translocation across barriers and through constrictions is a mechanism that is often used in vivo for transporting material between compartments. A specific example is apicomplexan parasites invading host cells through the tight junction that acts as a pore, and a similar barrier crossing is involved in drug delivery using lipid vesicles penetrating intact skin. Here, we use triangulated membranes and energy minimization to study the translocation of vesicles through pores with fixed radii. The vesicles bind to a lipid bilayer spanning the pore, the adhesion-energy gain drives the translocation, and the vesicle deformation induces an energy barrier. In addition, the deformation-energy cost for deforming the pore-spanning membrane hinders the translocation. Increasing the bending rigidity of the pore-spanning membrane and decreasing the pore size both increase the barrier height and shift the maximum to smaller translocation fractions. We compare the translocation of initially spherical vesicles with fixed membrane area and freely adjustable volume to that of initially prolate vesicles with fixed membrane area and volume. In the latter case, translocation can be entirely suppressed. Our predictions may help rationalize the invasion of apicomplexan parasites into host cells and design measures to combat the diseases they transmit.

The outer membrane is the defining structure of Gram-negative bacteria. We previously demonstrated that it is a major load-bearing component of the cell envelope and is therefore critical to the mechanical robustness of the bacterial cell. Here, to determine the key molecules and moieties within the outer membrane that underlie its contribution to cell envelope mechanics, we measured cell-envelope stiffness across several sets of mutants with altered outer-membrane sugar content, protein content, and electric charge. To decouple outer membrane stiffness from total cell envelope stiffness, we developed a novel microfluidics-based "osmotic force-extension" assay. In tandem, we developed a method to increase throughput of microfluidics experiments by performing them on color-coded pools of mutants. We found that truncating the core oligosaccharide, deleting the β-barrel protein OmpA, or deleting lipoprotein outer membrane-cell wall linkers all had the same modest, convergent effect on total cell-envelope stiffness in Escherichia coli. However, these mutations had large, variable effects on the ability of the cell wall to transfer tension to the outer membrane during large hyperosmotic shocks. Surprisingly, altering the electric charge of lipid A had little effect on the mechanical properties of the envelope. Finally, the presence or absence of OmpA determined whether truncating the core oligosaccharide decreased or increased envelope stiffness (respectively), revealing sign epistasis between these components. Based on these data we propose a putative structural model in which the spatial interactions between lipopolysaccharides, β-barrel proteins, and phospholipids coordinately determine cell envelope stiffness.

Photosynthetic organisms rely on a network of light-harvesting protein-pigment complexes to efficiently absorb sunlight and transfer excitation energy to reaction centre proteins where charge separation occurs. In photosynthetic purple bacteria, these complexes are embedded within the cell membrane, with lipid composition affecting complex clustering, thereby impacting inter-complex energy transfer. However, the impact of the lipid bilayer on intra-complex excitation dynamics is less understood. Recent experiments have addressed this question by comparing photo-excitation dynamics in detergent-isolated light-harvesting complex 2 (LH2) to LH2 complexes embedded in membrane discs mimicking the biological environment, revealing differences in spectra and energy transfer rates. In this paper, we use available quantum chemical and spectroscopy data to develop a complementary theoretical study on the excitonic structure and intra-complex energy transfer kinetics of the LH2 of photosynthetic purple bacteria Rhodoblastus (Rbl.) acidophilus (formerly Rhodopseudomonas acidophila) in two different conditions: the LH2 in a membrane environment and detergent-isolated LH2. We find that dark excitonic states, crucial for B800-B850 energy transfer within LH2, are more delocalised in the membrane model. Using non-perturbative and generalised Förster calculations, we show that such increased quantum delocalisation results in a 30% faster B800 to B850 transfer rate in the membrane model, in agreement with experimental results. We identify the dominant energy transfer pathways in each environment and demonstrate how differences in the B800 to B850 transfer rate arise from changes in LH2's electronic properties when embedded in the membrane. Furthermore, by accounting for the quasi-static variations of electronic excitation energies in the LH2, we show that the broadening of the distribution of the B800-B850 transfer rates is affected by the lipid composition. We argue that such variation in broadening could be a signature of a speed-accuracy trade-off, commonly seen in biological process.