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The protein-ligand binding frequently occurs in living organisms and plays a crucial role in the execution of the functions of proteins and drugs. It is also an indispensable part of drug discovery and screening. While the methods for investigating protein-ligand binding are diverse, each has its own objectives, strengths, and limitations, which all influence the choice of method. Many studies concentrate on one or a few specific methods, suggesting that comprehensive summaries are lacking. Therefore in this review, these methods are comprehensively summarized and are discussed in detail: prediction and simulation methods, thermal and thermodynamic methods, spectroscopic methods, methods of determining three-dimensional structures of the complex, mass spectrometry-based methods and others. It is also important to integrate these methods based on the specific objectives of the research. With the aim of advancing pharmaceutical research, this review seeks to deepen the understanding of the protein-ligand binding process., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Feng Zhou reports financial support was provided by the National Key Research and Development Program for the 14th Five-Year Plan of China. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The prediction of protein 3D structure from amino acid sequence is a computational grand challenge in biophysics and plays a key role in robust protein structure prediction algorithms, from drug discovery to genome interpretation. The advent of AI models, such as AlphaFold, is revolutionizing applications that depend on robust protein structure prediction algorithms. To maximize the impact, and ease the usability, of these AI tools we introduce APACE, AlphaFold2 and advanced computing as a service, a computational framework that effectively handles this AI model and its TB-size database to conduct accelerated protein structure prediction analyses in modern supercomputing environments. We deployed APACE in the Delta and Polaris supercomputers and quantified its performance for accurate protein structure predictions using four exemplar proteins: 6AWO, 6OAN, 7MEZ, and 6D6U. Using up to 300 ensembles, distributed across 200 NVIDIA A100 GPUs, we found that APACE is up to two orders of magnitude faster than off-the-self AlphaFold2 implementations, reducing time-to-solution from weeks to minutes. This computational approach may be readily linked with robotics laboratories to automate and accelerate scientific discovery., Competing Interests: Competing interests statement:The authors declare no competing interest.

Protein-protein association and aggregation are fundamental processes that play critical roles in various biological phenomena, from cellular signaling to disease progression. Understanding the underlying biophysical principles governing these processes is crucial for elucidating their mechanisms and developing strategies for therapeutic intervention. In this review, we provide an overview of recent experimental studies focused on protein-protein association and aggregation. We explore the key biophysical factors that influence these processes, including protein structure, conformational dynamics, and intermolecular interactions. We discuss the effects of environmental conditions such as temperature, pH and related buffer-specific effects, and ionic strength and related ion-specific effects on protein aggregation. The effects of polymer crowders and sugars are also addressed. We list the techniques used to study aggregation. We analyze emerging trends and challenges in the field, including the development of computational models and the integration of multidisciplinary approaches for a comprehensive understanding of protein-protein association and aggregation.

Neurofilaments (NFs) are multisubunit, neuron-specific intermediate filaments consisting of a 10-nm diameter filament "core" surrounded by a layer of long intrinsically disordered protein (IDP) "tails." NFs are thought to regulate axonal caliber during development and then stabilize the mature axon, with NF subunit misregulation, mutation, and aggregation featuring prominently in multiple neurological diseases. The field's understanding of NF structure, mechanics, and function has been deeply informed by a rich variety of biochemical, cell biological, and mouse genetic studies spanning more than four decades. These studies have contributed much to our collective understanding of NF function in axonal physiology and disease. In recent years, however, there has been a resurgence of interest in NF subunit proteins in two new contexts: as potential blood- and cerebrospinal fluid-based biomarkers of neuronal damage, and as model IDPs with intriguing properties. Here, we review established principles and more recent discoveries in NF structure and function. Where possible, we place these findings in the context of biophysics of NF assembly, interaction, and contributions to axonal mechanics.

With an estimate of hundred thousands of protein molecules per cell and the number of metabolites several orders of magnitude higher, protein-metabolite interactions are omnipresent. In vitro analyses are one of the main pillars on the way to establish a solid understanding of how these interactions contribute to maintaining cellular homeostasis. A repertoire of biophysical techniques is available by which protein-metabolite interactions can be quantitatively characterized in terms of affinity, specificity, and kinetics in a broad variety of solution environments. Several of those provide information on local or global conformational changes of the protein partner in response to ligand binding. This review chapter gives an overview of the state-of-the-art biophysical toolbox for the study of protein-metabolite interactions. It briefly introduces basic principles, highlights recent examples from the literature, and pinpoints promising future directions., (© 2023. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Cell monolayers are a central model system in the study of tissue biophysics. In vivo, epithelial tissues are curved on the scale of microns, and the curvature's role in the onset of spontaneous tissue flows is still not well understood. Here, we present a hydrodynamic theory for an apical-basal asymmetric active nematic gel on a curved strip. We show that surface curvature qualitatively changes monolayer motion compared with flat space: the resulting flows can be thresholdless, and the transition to motion may change from continuous to discontinuous. Surface curvature, friction, and active tractions are all shown to control the flow pattern selected, from simple shear to vortex chains.

Bone mechanobiology is the study of the physical, biological and mechanical processes that continuously affect the multiscale multicellular system of the bone from the organ to the molecular scale. Current knowledge derives from experimental studies, which are often limited to gathering qualitative data in a cross-sectional manner, up to a restricted number of time points. Moreover, the simultaneous collection of information about 3D bone microarchitecture, cell activity as well as protein distribution and level is still a challenge. In silico models can expand qualitative information with hypothetical quantitative systems, which allow quantification, testing and comparison to existing quantifiable experimental data. An overview of multiscale, multiphysics, agent-based and hybrid techniques and their applications to bone mechanobiology is provided in the present review. The study analysed how mechanical signals, cells and proteins can be modelled in silico to represent bone remodelling and adaptation. Hybrid modelling of bone mechanobiology could combine the methods used in multiscale, multiphysics and agent-based models into a single model, leading to a unified and comprehensive understanding of bone mechanobiology. Numerical simulations of in vivo multicellular systems aided in hypothesis testing of such in silico models. Recently, in silico trials have been used to illustrate the mechanobiology of cells and signalling pathways in clinical biopsies and animal bones, including the effects of drugs on single cells and signalling pathways up to the organ level. This improved understanding may lead to the identification of novel therapies for degenerative diseases such as osteoporosis.

Highly deuterated protein samples expand the biophysics and biological tool kit by providing, among other qualities, contrast matching in neutron diffraction experiments and reduction of dipolar spin interactions from normally protonated proteins in magnetic resonance studies, impacting both electron paramagnetic resonance and NMR spectroscopy. In NMR applications, deuteration is often combined with other isotopic labeling patterns to expand the range of conventional NMR spectroscopy research in both solution and solid-state conditions. However, preparation of deuterated proteins is challenging. We present here a simple, effective, and user-friendly protocol to produce highly deuterated proteins in Escherichia coli cells. The protocol utilizes the common shaker flask growth method and the well-known pET system (which provides expression control via the T7 promotor) for large-scale recombinant protein expression. One liter expression typically yields 5 to 50 mg of highly deuterated protein. Our data demonstrate that the optimized procedure produces a comparable quantity of protein in deuterium ( 2 H 2 O) oxide M9 medium compared with that in 1 H 2 O M9 medium. The protocol will enable a broader utilization of deuterated proteins in a number of biophysical techniques., Competing Interests: Conflict of interest The authors declare that they have no conflicts of interest with the contents of this article., (Published by Elsevier Inc.)

Using Brownian Dynamics simulations, we study effective interactions mediated between two identical and impermeable disks (inclusions) immersed in a bath of identical, active (self-propelled), Brownian rods in two spatial dimensions, by assuming that the self-propulsion axis of the rods may generally deviate from their longitudinal axis. When the self-propulsion is transverse (perpendicular to the rod axis), the accumulation of active rods around the inclusions is significantly enhanced, causing a more expansive steric layering (ring formation) of the rods around the inclusions, as compared with the reference case of longitudinally self-propelling rods. As a result, the transversally self-propelling rods also mediate a significantly longer ranged effective interaction between the inclusions. The bath-mediated interaction arises due to the overlaps between the active-rod rings formed around the inclusions, as they are brought into small separations. When the self-propulsion axis is tilted relative to the rod axis, we find an asymmetric imbalance of active-rod accumulation around the inclusion dimer. This leads to a noncentral interaction, featuring an anti-parallel pair of transverse force components and, hence, a bath-mediated torque on the dimer., (© 2021. The Author(s).)

A method motivated by the eye's aqueous veins is described for the imaging and strain calculation within soft biological tissues. A challenge to the investigation of the biomechanics of the aqueous vein-perilimbal sclera tissue complex is resolution of tissue deformations as a function of intraocular pressure and the subsequent calculation of strain (a normalized measure of deformation). The method involves perfusion of the eye with a contrast agent during conduction of non-invasive, optical resolution photoacoustic microscopy. This imaging technique permits three-dimensional displacement measurements of tracked points on the inner walls of the veins which are used in a finite element model to determine the corresponding strains. The methods are validated against two standard strain measurement methods. Representative porcine globe perfusion experiments are presented that demonstrate the power of the method to determine complex strain fields in the veins dependent on intraocular pressure as well as vein anatomy. In these cases, veins are observed to move radially outward during increases in intraocular pressure and to possess significant spatial strain variation, possibly influenced by their branching patterns. To the authors' knowledge, these are the only such quantitative, data driven, calculations of the aqueous vein strains available in the open literature., (© 2021. The Author(s).)

Calcineurin, also known as protein phosphatase 2B, is a heterodimeric serine threonine phosphatase involved in numerous signaling pathways. During the past 50 years, calcineurin has been the subject of extensive investigation. Many of its cellular and physiological functions have been described, and the underlying biophysical mechanisms are the subject of active investigation. With the abundance of techniques and experimental designs utilized to study calcineurin and its numerous substrates, it is difficult to reconcile the available information. There have been a plethora of reports describing the role of calcineurin in cardiac disease. However, a physiological role of calcineurin in healthy cardiomyocyte function requires clarification. Here, we review the seminal biophysical and structural details that are responsible for the molecular function and inhibition of calcineurin. We then focus on literature describing the roles of calcineurin in cardiomyocyte physiology and disease.

Deep learning using neural networks relies on a class of machine-learnable models constructed using 'differentiable programs'. These programs can combine mathematical equations specific to a particular domain of natural science with general-purpose, machine-learnable components trained on experimental data. Such programs are having a growing impact on molecular and cellular biology. In this Perspective, we describe an emerging 'differentiable biology' in which phenomena ranging from the small and specific (for example, one experimental assay) to the broad and complex (for example, protein folding) can be modeled effectively and efficiently, often by exploiting knowledge about basic natural phenomena to overcome the limitations of sparse, incomplete and noisy data. By distilling differentiable biology into a small set of conceptual primitives and illustrative vignettes, we show how it can help to address long-standing challenges in integrating multimodal data from diverse experiments across biological scales. This promises to benefit fields as diverse as biophysics and functional genomics., (© 2021. Springer Nature America, Inc.)

Mechanobiology has nowadays acquired the status of a topic of fundamental importance in a degree in Biological Sciences. It is inherently a multidisciplinary topic where biology, physics and engineering competences are required. A course in mechanobiology should include lab experiences where students can appreciate how mechanical stimuli from outside affect living cell behaviour. Here we describe all the steps to build a cell stretcher inside an on-stage cell incubator. This device allows exposing living cells to a periodic mechanical stimulus similar to what happens in physiological conditions such as, for example, in the vascular system or in the lungs. The reaction of the cells to the periodic mechanical stretching represents a prototype of a mechanobiological signal integrated by living cells. We also provide the theoretical and experimental aspects related to the calibration of the stretcher apparatus at a level accessible to researchers not used to dealing with topics like continuum mechanics and analysis of deformations. We tested our device by stretching cells of two different lines, U87-MG and Balb-3T3 cells, and we analysed and discussed the effect of the periodic stimulus on both cell reorientation and migration. We also discuss the basic aspects related to the quantitative analysis of the reorientation process and of cell migration. We think that the device we propose can be easily reproduced at low-cost within a project-oriented course in the fields of biology, biotechnology and medical engineering., (© 2021. Biomedical Engineering Society.)