Quarterly Reviews of Biophysics最新文献

Single-particle electron cryomicroscopy (cryo-EM) has enabled rapid advances in our understanding of membrane protein structure and function. The primary goal during the development of cryo-EM was to perform experiments equivalent to X-ray crystallography, but without needing to crystallize the protein of interest first. However, exciting recent progress in single-particle cryo-EM has come from relaxing assumptions and constraints related to the homogeneity of samples. These assumptions and constraints, which were necessary for crystallization, include that all molecules imaged have the same composition and are in the same conformation, that the specimen consists of only one species, and that the specimen is derived from a solution of isolated protein particles. Here, I discuss the study of membrane protein complexes within lipid bilayers by single-particle cryo-EM. I point out the value and recently achieved capability of studying membrane proteins in lipid vesicles, and in particular endogenous membrane proteins in vesicles prepared from their native lipid bilayer.

While the structure of proteins can now be predicted from sequence with high certainty, the prediction of protein functional dynamics remains to be achieved. Progress towards this goal will require a much larger experimental database of the relationships among sequence, dynamics, and function than currently available. Dynamic transitions that are key to protein function and turnover remain difficult to access and characterize because they have significantly higher free energy than the folded states of proteins and hence are not populated. To access these higher free energy states, proteins must be perturbed. High temperatures often lead to aggregation, while chemical denaturants, because they interact with the entire protein backbone, tend to smooth protein conformational landscapes. In contrast, high hydrostatic pressure represents a continuous and reversible variable that can perturb protein structure locally around internal cavities, leading to partial structural disruption, populating these higher energy states sufficiently for their characterization.

Theoretical analysis of an energy barrier model for the electrical properties of a biological membrane yields new results. Discontinuities at the membrane-solution interfaces are crucial and receive careful attention, as does the polarization charge density due to electroneutral but polarized ion distributions. The topics explored include the equilibrium and time-dependent Nernst potential, the resting potential, the capacitance-resistance equation for membrane voltage, and large electrical effects on osmosis (bulk volume flow). The generalization of Nernst-Hartley salt diffusion to the diffusion of mixed salts as a necessary tool is accomplished. The electric field inside the membrane is especially strong at the membrane-solution interfaces. The analysis of the resting potential differs from the Goldman-Hodgkin-Katz formulation but predicts realistic numerical values for animal cells and also captures the effect of switching sodium and potassium ion permeabilities. An analysis of the physical basis of bulk water flow in the presence of impermeant and permeant ions, that is, Donnan osmosis, reveals large ion charge effects that have not previously been considered. The equation derived here for Donnan osmotic flow helps to explain why the action of the sodium pump is essential for the prevention of excessive osmotic stress on cellular membranes.

In 2019, in this journal, I discussed approaches for controlling the movement of molecules, in particular macromolecules, with an emphasis on how this enabled advances in the field of drug delivery - a field that has impacted billions of people worldwide. Since 2019, there have been advances in our work and this field including a striking demonstration in which drug delivery nanoparticles were crucial to the success of mRNA therapies and the Covid-19 vaccine. In this paper, I provide updates in such areas as i) developing new methods for oral drug delivery systems, ii) delivery of molecules to specific sites of the body, iii) new types of delivery systems, and iv) examples of machine learning/artificial intelligence in these areas. I also discuss advances in mRNA technology as it relates to drug delivery and the development of nanoparticles to protect and deliver vaccines, which saved and improved the lives of hundreds of millions of people throughout the world.

Allosteric communication is established by networks through which strain energy generated at the allosteric site by an allosteric event, such as ligand binding, can propagate to the functional site. Exerted on multiple molecules in the cell, it can wield a biased function. Here, we discuss allosteric networks and allosteric signaling bias. Networks are graphs specified by nodes (residues) and edges (their connections). Allosteric bias is a property of a population. It is described by allosteric effector-specific dynamic distributions of conformational ensembles, as classically exemplified by G protein-coupled receptors (GPCRs). An ensemble describes the likelihood of a specific (strong/weak) allosteric signal propagating to a specific functional site. A network description provides the propagation route in a specific conformation, pinpointing key residues whose mutations could promote drug resistance. Efficiency is influenced by path length, relative stabilities and allosteric transitions. Through specific contacts, specific ligands can bias signaling in proteins, for example, in receptor tyrosine kinases (RTKs) toward specific phosphorylation sites and cell signaling activation. Thus, rather than the two - active and inactive - states, and a single pathway, we consider multiple states and favored pathways. This allows us to consider biased allosteric switches among minor, invisible states and observable outcomes. Within this framework, we further consider signaling strength and duration as key determinants of cell fate: If weak and sustained, it may induce differentiation; If bursts of strong and short, proliferation.

Time-resolved (TR) intrinsic fluorescence of tryptophan (Trp) provides a wealth of information on the structure and localization of proteins and peptides and their interactions with one another, with drugs, lipid membranes, lipid- and surfactant-based drug delivery systems, et cetera. Intrinsic Trp eliminates the need for labeling and avoids the perturbation of the system by the label; introduced Trp is a rather conservative and small label compared to others. Whereas custom-tailored fluorophores are often optimized for a special technique, Trp can be employed to monitor a wide variety of effects. We address interactions of Trp with surrounding molecules, dynamic quenchers and Förster resonance energy transfer (FRET) acceptors that affect the fluorescence decay. Speed and range of angular motion of Trp are characterized by TR anisotropy. Electrostatic interactions of Trp with charged and polar molecules, including water, are monitored by decay-associated spectra (DAS) or TR emission spectra (TRES) and quantified in terms of TR shifts of the spectral center of gravity. This versatility is a great advantage and, at the same time, comes with a complexity of the behavior that can render it a challenge to interpret the data in detail properly. This review provides an overview of applications of TR fluorescence of Trp bulk samples in biomolecular, biophysical, and pharmaceutical studies. The aim is not only to point out the diversity of the read-out of these techniques, but also critically examine their current use. Therefore, we identify most common technical pitfalls and evaluate the degree of reliability of the interpretational approaches. This should aid a more extensive and meaningful use of TR fluorescence of Trp.

The question of whether PCR is reliable sounds strange at first. However, looking at the scientific literature from the 1950s and 60s, one will find many publications on the physicochemistry of DNA that have been forgotten meanwhile. Quite a few of these studies have shown that DNA is thermolabile, which consequently raises the question of whether this thermolability is relevant in the context of PCR, namely in the denaturation phase. However, it can be shown that this is not the case: losses due to thermal hydrolysis are irrelevant for the performance of contemporary PCR protocols and their specificity as well as for the significance of their results. There is now a huge amount of scientifically verified and published data on technical and molecular aspects of PCR, a small selection of which we quote here. In addition, we present some primary data that also clearly demonstrate the reliability of PCR.

Neurotransmitter release via synaptic vesicle fusion with the plasma membrane is driven by SNARE proteins (Synaptobrevin, Syntaxin, and SNAP-25) and accessory proteins (Synaptotagmin, Complexin, Munc13, and Munc18). While extensively studied experimentally, the precise mechanisms and dynamics remain elusive due to spatiotemporal limitations. Molecular dynamics (MD) simulations-both all-atom (AA) and coarse-grained (CG)-bridge these gaps by capturing fusion dynamics beyond experimental resolution. This review explores the use of these simulations in understanding SNARE-mediated membrane fusion and its regulation by Synaptotagmin and Complexin. We first examine two competing hypotheses regarding the driving force of fusion: (1) SNARE zippering transducing energy through rigid juxtamembrane domains (JMDs) and (2) SNAREs generating entropic forces via flexible JMDs. Despite different origins of forces, the conserved fusion pathway - from membrane adhesion to stalk and fusion pore (FP) formation - emerges across models. We also highlight the critical role of SNARE transmembrane domains (TMDs) and their regulation by post-translational modifications like palmitoylation in fast fusion. Further, we review Ca²⁺-dependent interactions of Synaptotagmin's C2 domains with lipids and SNAREs at the primary and tripartite interfaces, and how these interactions regulate fusion timing. Complexin's role in clamping spontaneous fusion while facilitating evoked release via its central and accessory helices is also discussed. We present a case study leveraging AA and CG simulations to investigate ion selectivity in FPs, balancing timescale and accuracy. We conclude with the limitations in current simulations and using AI tools to construct complete fusion machinery and explore isoform-specific functions in fusion machinery.