Developments, applications, and prospects of cryo-electron microscopy

Cryo-EM structures of pathogenic fibrils and their impact on neurodegenerative disease research

Neurodegenerative diseases are commonly associated with the formation of aberrant protein aggregates within the brain, and ultrastructural analyses have revealed that the proteins within these inclusions often assemble into amyloid filaments. Cryoelectron microscopy (cryo-EM) has emerged as an effective method for determining the near-atomic structure of these disease-associated filamentous proteins, and the resulting structures have revolutionized the way we think about aberrant protein aggregation and propagation during disease progression. These structures have also revealed that individual fibril conformations may dictate different disease conditions, and this newfound knowledge has improved disease modeling in the lab and advanced the ongoing pursuit of clinical tools capable of distinguishing and targeting different pathogenic entities within living patients. In this review, we summarize some of the recently developed cryo-EM structures of ex vivo α-synuclein, tau, β-amyloid (Aβ), TAR DNA-binding protein 43 (TDP-43), and transmembrane protein 106B (TMEM106B) fibrils and discuss how these structures are being leveraged toward mechanistic research and therapeutic development.

Exploring treatment options in cancer: Tumor treatment strategies

Traditional therapeutic approaches such as chemotherapy and radiation therapy have burdened cancer patients with onerous physical and psychological challenges. Encouragingly, the landscape of tumor treatment has undergone a comprehensive and remarkable transformation. Emerging as fervently pursued modalities are small molecule targeted agents, antibody-drug conjugates (ADCs), cell-based therapies, and gene therapy. These cutting-edge treatment modalities not only afford personalized and precise tumor targeting, but also provide patients with enhanced therapeutic comfort and the potential to impede disease progression. Nonetheless, it is acknowledged that these therapeutic strategies still harbour untapped potential for further advancement. Gaining a comprehensive understanding of the merits and limitations of these treatment modalities holds the promise of offering novel perspectives for clinical practice and foundational research endeavours. In this review, we discussed the different treatment modalities, including small molecule targeted drugs, peptide drugs, antibody drugs, cell therapy, and gene therapy. It will provide a detailed explanation of each method, addressing their status of development, clinical challenges, and potential solutions. The aim is to assist clinicians and researchers in gaining a deeper understanding of these diverse treatment options, enabling them to carry out effective treatment and advance their research more efficiently.

Reconstruction of the real 3D shape of the SARS-CoV-2 virus

The photographs of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus taken by electron transmission microscopy and cryoelectron microscopy provide only a 2D silhouette. The viruses appear to look like distorted circles. The present paper questions the real shape of the SARS-CoV-2 virus and makes an attempt to give an answer. Is this a general ellipsoid, a spheroid with rotational symmetry, a sphere, or something else? The answer requires the application of tools from three different disciplines: structural mechanics, microbiology, and statistics. A total of 590 virus photographs taken from 22 recently published papers were examined. From this experimental data pool, the histogram of diameter ratios was built from the 283 measurements where the virus images could be approximated as ellipses. The curve peaks at the diameter ratio of 1.22. The transformation equation for the spatial shape to the planar shade was derived for a fixed light source of the microscope. This equation involves an unknown orientation of the viruses with respect to the microscope. Two sets of models were developed, one with a uniform distribution of the virus orientation and the other with the orientation defined by the normalized beta distribution. In both sets of models, the unknown diameter ratio of the spheroidal virus was regarded as a random realization from translated gamma distributions. The parameters of the distribution of the kernel functions were determined by minimizing the mean square difference between the predicted and measured 2D histograms. The information included in the measured histograms was found to be insufficient to find an unknown distribution of the virus's orientation. Simply too many unknown parameters render the solution physically unrealistic. The minimization procedure with a uniform probability of virus orientation predicted the peak of the aspect ratio of the 3D spheroid at 1.32. Based on this result, models of the virus will be developed in the continuation of this research for a full dynamic analysis.

Emerging Topics in Protein Crystallography

Protein crystallography is the discipline concerned with the determination of the three-dimensional structure of biological macromolecules in a crystalline state [...].

Tailoring Biomaterials Ameliorate Inflammatory Bone Loss

Inflammatory diseases, such as rheumatoid arthritis, periodontitis, chronic obstructive pulmonary disease, and celiac disease, disrupt the delicate balance between bone resorption and formation, leading to inflammatory bone loss. Conventional approaches to tackle this issue encompass pharmaceutical interventions and surgical procedures. Nevertheless, pharmaceutical interventions exhibit limited efficacy, while surgical treatments impose trauma and significant financial burden upon patients. Biomaterials show outstanding spatiotemporal controllability, possess a remarkable specific surface area, and demonstrate exceptional reactivity. In the present era, the advancement of emerging biomaterials has bestowed upon more efficacious solutions for combatting the detrimental consequences of inflammatory bone loss. In this review, the advances of biomaterials for ameliorating inflammatory bone loss are listed. Additionally, the advantages and disadvantages of various biomaterials-mediated strategies are summarized. Finally, the challenges and perspectives of biomaterials are analyzed. This review aims to provide new possibilities for developing more advanced biomaterials toward inflammatory bone loss.

An optimised protocol for the expression and purification of adenovirus core protein VII

Adenovirus protein VII (pVII) is a highly basic core protein, bearing resemblance to mammalian histones. Despite its diverse functions, a comprehensive understanding of its structural intricacies and the mechanisms underlying its functions remain elusive, primarily due to the complexity of producing a good amount of soluble pVII. This study aimed to optimise the expression and purification of recombinant pVII from four different adenoviruses with a simple vector construct. This study successfully determined the optimal conditions for efficiently purifying pVII across four adenovirus species, revealing the differential preference for bacterial expression systems. The One Shot BL21 Star (DE3) proved favourable over Rosetta 2 (DE3) pLysS with consistent levels of expression between IPTG-induced and auto-induction. We demonstrated that combining chemical and mechanical cell lysis is possible and highly effective. Other noteworthy benefits were observed in using RNase during sample processing. The addition of RNase has significantly improved the quality and quantity of the purified protein as confirmed by chromatographic and western blot analyses. These findings established a solid groundwork for pVII purification methodologies and carry the significant potential to assist in unveiling the core structure of pVII, its arrangement within the core, DNA condensation intricacies, and potential pathways for nuclear transport.

Simulations of Functional Motions of Super Large Biomolecules with a Mixed-Resolution Model

Many large protein machines function through an interplay between large-scale movements and intricate conformational changes. Understanding functional motions of these proteins through simulations becomes challenging for both all-atom and coarse-grained (CG) modeling techniques because neither approach alone can readily capture the full details of these motions. In this study, we develop a multiscale model by employing the popular MARTINI CG model to represent a heterogeneous environment and structurally stable proteins and using the united-atom (UA) model PACE to describe proteins undergoing subtle conformational changes. PACE was previously developed to be compatible with the MARTINI solvent and membrane. Here, we couple the protein descriptions of the two models by directly mixing UA and CG interaction parameters to greatly simplify parameter determination. Through extensive validations with diverse protein systems in solution or membrane, we demonstrate that only additional parameter rescaling is needed to enable the resulting model to recover the stability of native structures of proteins under mixed representation. Moreover, we identify the optimal scaling factors that can be applied to various protein systems, rendering the model potentially transferable. To further demonstrate its applicability for realistic systems, we apply the model to a mechanosensitive ion channel Piezo1 that has peripheral arms for sensing membrane tension and a central pore for ion conductance. The model can reproduce the coupling between Piezo1's large-scale arm movement and subtle pore opening in response to membrane stress while consuming much less computational costs than all-atom models. Therefore, our model shows promise for studying functional motions of large protein machines.

Cryo-electron microscopy-based drug design

Structure-based drug design (SBDD) has gained popularity owing to its ability to develop more potent drugs compared to conventional drug-discovery methods. The success of SBDD relies heavily on obtaining the three-dimensional structures of drug targets. X-ray crystallography is the primary method used for solving structures and aiding the SBDD workflow; however, it is not suitable for all targets. With the resolution revolution, enabling routine high-resolution reconstruction of structures, cryogenic electron microscopy (cryo-EM) has emerged as a promising alternative and has attracted increasing attention in SBDD. Cryo-EM offers various advantages over X-ray crystallography and can potentially replace X-ray crystallography in SBDD. To fully utilize cryo-EM in drug discovery, understanding the strengths and weaknesses of this technique and noting the key advancements in the field are crucial. This review provides an overview of the general workflow of cryo-EM in SBDD and highlights technical innovations that enable its application in drug design. Furthermore, the most recent achievements in the cryo-EM methodology for drug discovery are discussed, demonstrating the potential of this technique for advancing drug development. By understanding the capabilities and advancements of cryo-EM, researchers can leverage the benefits of designing more effective drugs. This review concludes with a discussion of the future perspectives of cryo-EM-based SBDD, emphasizing the role of this technique in driving innovations in drug discovery and development. The integration of cryo-EM into the drug design process holds great promise for accelerating the discovery of new and improved therapeutic agents to combat various diseases.

Chemical Reactions in Living Systems

The term "in vivo ("in the living") chemistry" refers to chemical reactions that take place in a complex living system such as cells, tissue, body liquids, or even in an entire organism. In contrast, reactions that occur generally outside living organisms in an artificial environment (e.g., in a test tube) are referred to as in vitro. Over the past decades, significant contributions have been made in this rapidly growing field of in vivo chemistry, but it is still not fully understood, which transformations proceed efficiently without the formation of by-products or how product formation in such complex environments can be characterized. Potential applications can be imagined that synthesize drug molecules directly within the cell or confer new cellular functions through controlled chemical transformations that will improve the understanding of living systems and develop new therapeutic strategies. The guiding principles of this contribution are twofold: 1) Which chemical reactions can be translated from the laboratory to the living system? 2) Which characterization methods are suitable for studying reactions and structure formation in complex living environments?

Structure-Based Evaluation of Hybrid Lipid-Polymer Nanoparticles: The Role of the Polymeric Guest

The combination of phospholipids and block-copolymers yields advanced hybrid nanoparticles through the self-assembly process in an aqueous environment. The physicochemical features of the lipid/polymer components, like the lipid-polymer molar ratio, the macromolecular architecture of the block copolymer, the main transition temperature of the phospholipid, as well as the formulation and preparation protocol parameters, are some of the most crucial parameters for the formation of hybrid lipid/polymer vesicles and for the differentiation of their morphology. The morphology, along with other physicochemical nanoparticle characteristics are strictly correlated with the nanoparticle's later biological behavior after being administered, affecting interactions with cells, biodistribution, uptake, toxicity, drug release, etc. In the present study, a structural evaluation of hybrid lipid-polymer nanoparticles based on cryo-TEM studies was undertaken. Different kinds of hybrid lipid-polymer nanoparticles were designed and developed using phospholipids and block copolymers with different preparation protocols. The structures obtained ranged from spherical vesicles to rod-shaped structures, worm-like micelles, and irregular morphologies. The obtained morphologies were correlated with the formulation and preparation parameters and especially the type of lipid, the polymeric guest, and their ratio.

Recent Advances and Challenges in Protein Structure Prediction

Artificial intelligence has made significant advances in the field of protein structure prediction in recent years. In particular, DeepMind's end-to-end model, AlphaFold2, has demonstrated the capability to predict three-dimensional structures of numerous unknown proteins with accuracy levels comparable to those of experimental methods. This breakthrough has opened up new possibilities for understanding protein structure and function as well as accelerating drug discovery and other applications in the field of biology and medicine. Despite the remarkable achievements of artificial intelligence in the field, there are still some challenges and limitations. In this Review, we discuss the recent progress and some of the challenges in protein structure prediction. These challenges include predicting multidomain protein structures, protein complex structures, multiple conformational states of proteins, and protein folding pathways. Furthermore, we highlight directions in which further improvements can be conducted.

One bead per residue can describe all-atom protein structures

Atomistic resolution is the standard for high-resolution biomolecular structures, but experimental structural data are often at lower resolution. Coarse-grained models are also used extensively in computational studies to reach biologically relevant spatial and temporal scales. This study explores the use of advanced machine learning networks for reconstructing atomistic models from reduced representations. The main finding is that a single bead per amino acid residue allows construction of accurate and stereochemically realistic all-atom structures with minimal loss of information. This suggests that lower resolution representations of proteins may be sufficient for many applications when combined with a machine learning framework that encodes knowledge from known structures. Practical applications include the rapid addition of atomistic detail to low-resolution structures from experiment or computational coarse-grained models. The application of rapid, deterministic all-atom reconstruction within multi-scale frameworks is further demonstrated with a rapid protocol for the generation of accurate models from cryo-EM densities close to experimental structures.

Proteomics provides insights into the theranostic potential of extracellular vesicles

Extracellular vesicles (EVs) encompass a diverse range of membranous structures derived from cells, including exosomes and microvesicles. These vesicles are present in biological fluids and play vital roles in various physiological and pathological processes. They facilitate intercellular communication by enabling the exchange of proteins, lipids, and genetic material between cells. Understanding the cellular processes that govern EV biology is essential for unraveling their physiological and pathological functions and their potential clinical applications. Despite significant advancements in EV research in recent years, there is still much to learn about these vesicles. The advent of improved mass spectrometry (MS)-based techniques has allowed for a deeper characterization of EV protein composition, providing valuable insights into their roles in different physiological and pathological conditions. In this chapter, we provide an overview of proteomics studies conducted to identify the protein contents of EVs, which contribute to their therapeutic and pathological features. We also provided evidence on the potential of EV proteome contents as biomarkers for early disease diagnosis, progression, and treatment response, as well as factors that influence their composition. Additionally, we discuss the available databases containing information on EV proteome contents, and finally, we highlight the need for further research to pave the way toward their utilization in clinical settings.

Aptamer-Protein Interactions: From Regulation to Biomolecular Detection

Serving as the basis of cell life, interactions between nucleic acids and proteins play essential roles in fundamental cellular processes. Aptamers are unique single-stranded oligonucleotides generated by in vitro evolution methods, possessing the ability to interact with proteins specifically. Altering the structure of aptamers will largely modulate their interactions with proteins and further affect related cellular behaviors. Recently, with the in-depth research of aptamer-protein interactions, the analytical assays based on their interactions have been widely developed and become a powerful tool for biomolecular detection. There are some insightful reviews on aptamers applied in protein detection, while few systematic discussions are from the perspective of regulating aptamer-protein interactions. Herein, we comprehensively introduce the methods for regulating aptamer-protein interactions and elaborate on the detection techniques for analyzing aptamer-protein interactions. Additionally, this review provides a broad summary of analytical assays based on the regulation of aptamer-protein interactions for detecting biomolecules. Finally, we present our perspectives regarding the opportunities and challenges of analytical assays for biological analysis, aiming to provide guidance for disease mechanism research and drug discovery.

Novel approaches to target fibroblast mechanotransduction in fibroproliferative diseases

The ability of cells to sense and respond to changes in mechanical environment is vital in conditions of organ injury when the architecture of normal tissues is disturbed or lost. Among the various cellular players that respond to injury, fibroblasts take center stage in re-establishing tissue integrity by secreting and organizing extracellular matrix into stabilizing scar tissue. Activation, activity, survival, and death of scar-forming fibroblasts are tightly controlled by mechanical environment and proper mechanotransduction ensures that fibroblast activities cease after completion of the tissue repair process. Conversely, dysregulated mechanotransduction often results in fibroblast over-activation or persistence beyond the state of normal repair. The resulting pathological accumulation of extracellular matrix is called fibrosis, a condition that has been associated with over 40% of all deaths in the industrialized countries. Consequently, elements in fibroblast mechanotransduction are scrutinized for their suitability as anti-fibrotic therapeutic targets. We review the current knowledge on mechanically relevant factors in the fibroblast extracellular environment, cell-matrix and cell-cell adhesion structures, stretch-activated membrane channels, stress-regulated cytoskeletal structures, and co-transcription factors. We critically discuss the targetability of these elements in therapeutic approaches and their progress in pre-clinical and/or clinical trials to treat organ fibrosis.

Preparing Arabidopsis thaliana root protoplasts for cryo electron tomography

The use of protoplasts in plant biology has become a convenient tool for the application of transient gene expression. This model system has allowed the study of plant responses to biotic and abiotic stresses, protein location and trafficking, cell wall dynamics, and single-cell transcriptomics, among others. Although well-established protocols for isolating protoplasts from different plant tissues are available, they have never been used for studying plant cells using cryo electron microscopy (cryo-EM) and cryo electron tomography (cryo-ET). Here we describe a workflow to prepare root protoplasts from Arabidopsis thaliana plants for cryo-ET. The process includes protoplast isolation and vitrification on EM grids, and cryo-focused ion beam milling (cryo-FIB), with the aim of tilt series acquisition. The whole workflow, from growing the plants to the acquisition of the tilt series, may take a few months. Our protocol provides a novel application to use plant protoplasts as a tool for cryo-ET.

In the Age of Machine Learning Cryo-EM Research is Still Necessary: A Path toward Precision Medicine

Machine learning has proven useful in analyzing complex biological data and has greatly influenced the course of research in structural biology and precision medicine. Deep neural network models oftentimes fail to predict the structure of complex proteins and are heavily dependent on experimentally determined structures for their training and validation. Single-particle cryogenic electron microscopy (cryoEM) is also advancing the understanding of biology and will be needed to complement these models by continuously supplying high-quality experimentally validated structures for improvements in prediction quality. In this perspective, the significance of structure prediction methods is highlighted, but the authors also ask, what if these programs cannot accurately predict a protein structure important for preventing disease? The role of cryoEM is discussed to help fill the gaps left by artificial intelligence predictive models in resolving targetable proteins and protein complexes that will pave the way for personalized therapeutics.

Toward the analysis of functional proteoforms using mass spectrometry-based stability proteomics

Functional proteomics aims to elucidate biological functions, mechanisms, and pathways of proteins and proteoforms at the molecular level to examine complex cellular systems and disease states. A series of stability proteomics methods have been developed to examine protein functionality by measuring the resistance of a protein to chemical or thermal denaturation or proteolysis. These methods can be applied to measure the thermal stability of thousands of proteins in complex biological samples such as cell lysate, intact cells, tissues, and other biological fluids to measure proteome stability. Stability proteomics methods have been popularly applied to observe stability shifts upon ligand binding for drug target identification. More recently, these methods have been applied to characterize the effect of structural changes in proteins such as those caused by post-translational modifications (PTMs) and mutations, which can affect protein structures or interactions and diversify protein functions. Here, we discussed the current application of a suite of stability proteomics methods, including thermal proteome profiling (TPP), stability of proteomics from rates of oxidation (SPROX), and limited proteolysis (LiP) methods, to observe PTM-induced structural changes on protein stability. We also discuss future perspectives highlighting the integration of top-down mass spectrometry and stability proteomics methods to characterize intact proteoform stability and understand the function of variable protein modifications.

In vivo Protein Footprinting Reveals the Dynamic Conformational Changes of Proteome of Multiple Tissues in Progressing Alzheimer's Disease

Numerous studies have investigated changes in protein expression at the system level using proteomic mass spectrometry, but only recently have studies explored the structure of proteins at the proteome level. We developed covalent protein painting (CPP), a protein footprinting method that quantitatively labels exposed lysine, and have now extended the method to whole intact animals to measure surface accessibility as a surrogate of in vivo protein conformations. We investigated how protein structure and protein expression change as Alzheimer's disease (AD) progresses by conducting in vivo whole animal labeling of AD mice. This allowed us to analyze broadly protein accessibility in various organs over the course of AD. We observed that structural changes of proteins related to 'energy generation,' 'carbon metabolism,' and 'metal ion homeostasis' preceded expression changes in the brain. We found that proteins in certain pathways undergoing structural changes were significantly co-regulated in the brain, kidney, muscle, and spleen.

Past, Present, and Future Perspectives on Computer-Aided Drug Design Methodologies

The application of computational approaches in drug discovery has been consolidated in the last decades. These families of techniques are usually grouped under the common name of "computer-aided drug design" (CADD), and they now constitute one of the pillars in the pharmaceutical discovery pipelines in many academic and industrial environments. Their implementation has been demonstrated to tremendously improve the speed of the early discovery steps, allowing for the proficient and rational choice of proper compounds for a desired therapeutic need among the extreme vastness of the drug-like chemical space. Moreover, the application of CADD approaches allows the rationalization of biochemical and interactive processes of pharmaceutical interest at the molecular level. Because of this, computational tools are now extensively used also in the field of rational 3D design and optimization of chemical entities starting from the structural information of the targets, which can be experimentally resolved or can also be obtained with other computer-based techniques. In this work, we revised the state-of-the-art computer-aided drug design methods, focusing on their application in different scenarios of pharmaceutical and biological interest, not only highlighting their great potential and their benefits, but also discussing their actual limitations and eventual weaknesses. This work can be considered a brief overview of computational methods for drug discovery.

Structural studies of protein-nucleic acid complexes: A brief overview of the selected techniques

Protein-nucleic acid complexes are involved in all vital processes, including replication, transcription, translation, regulation of gene expression and cell metabolism. Knowledge of the biological functions and molecular mechanisms beyond the activity of the macromolecular complexes can be determined from their tertiary structures. Undoubtably, performing structural studies of protein-nucleic acid complexes is challenging, mainly because these types of complexes are often unstable. In addition, their individual components may display extremely different surface charges, causing the complexes to precipitate at higher concentrations used in many structural studies. Due to the variety of protein-nucleic acid complexes and their different biophysical properties, no simple and universal guideline exists that helps scientists chose a method to successfully determine the structure of a specific protein-nucleic acid complex. In this review, we provide a summary of the following experimental methods, which can be applied to study the structures of protein-nucleic acid complexes: X-ray and neutron crystallography, nuclear magnetic resonance (NMR) spectroscopy, cryogenic electron microscopy (cryo-EM), atomic force microscopy (AFM), small angle scattering (SAS) methods, circular dichroism (CD) and infrared (IR) spectroscopy. Each method is discussed regarding its historical context, advancements over the past decades and recent years, and weaknesses and strengths. When a single method does not provide satisfactory data on the selected protein-nucleic acid complex, a combination of several methods should be considered as a hybrid approach; thus, specific structural problems can be solved when studying protein-nucleic acid complexes.

Potassium Ion Channels in Glioma: From Basic Knowledge into Therapeutic Applications

Ion channels, specifically those controlling the flux of potassium across cell membranes, have recently been shown to exhibit an important role in the pathophysiology of glioma, the most common primary central nervous system tumor with a poor prognosis. Potassium channels are grouped into four subfamilies differing by their domain structure, gating mechanisms, and functions. Pertinent literature indicates the vital functions of potassium channels in many aspects of glioma carcinogenesis, including proliferation, migration, and apoptosis. The dysfunction of potassium channels can result in pro-proliferative signals that are highly related to calcium signaling as well. Moreover, this dysfunction can feed into migration and metastasis, most likely by increasing the osmotic pressure of cells allowing the cells to initiate the "escape" and "invasion" of capillaries. Reducing the expression or channel blockage has shown efficacy in reducing the proliferation and infiltration of glioma cells as well as inducing apoptosis, priming several approaches to target potassium channels in gliomas pharmacologically. This review summarizes the current knowledge on potassium channels, their contribution to oncogenic transformations in glioma, and the existing perspectives on utilizing them as potential targets for therapy.

In situ single particle characterization of the themoresponsive and co-nonsolvent behavior of PNIPAM microgels and silica@PNIPAM core-shell colloids

Poly(N-isopropylacrylamide) (PNIPAM) microgels and PNIPAM colloidal shells attract continuous strong interest due to their thermoresponsive behavior, as their size and properties can be tuned by temperature. The direct single particle observation and characterization of pure, unlabeled PNIPAM microgels in their native aqueous environment relies on imaging techniques that operate either at interfaces or in cryogenic conditions, thus limiting the observation of their dynamic nature. Liquid Cell (Scanning) Transmission Electron Microscopy (LC-(S) TEM) imaging allows the characterization of materials and dynamic processes such as nanoparticle growth, etching, and diffusion, at nanometric resolution in liquids. Here we show that via a facile post-synthetic in situ polymer labelling step with high-contrast marker core-shell Au@SiO₂ nanoparticles (NPs) it is possible to determine the full volume of PNIPAM microgels in water. The labelling allowed for the successful characterization of the thermoresponsive behavior of PNIPAM microgels and core shell silica@PNIPAM hybrid microgels, as well as the co-nonsolvency of PNIPAM in aqueous alcoholic solutions. The interplay between electron beam irradiation and PNIPAM systems in water resulted in irreversible shrinkage due to beam induced water radiolysis products, which in turn also affected the thermoresponsive behavior of PNIPAM. The addition of 2-propanol as radical scavenger improved PNIPAM stability in water under electron beam irradiation.

Using mass spectrometry imaging to visualize age-related subcellular disruption

Metabolic homeostasis balances the production and consumption of energetic molecules to maintain active, healthy cells. Cellular stress, which disrupts metabolism and leads to the loss of cellular homeostasis, is important in age-related diseases. We focus here on the role of organelle dysfunction in age-related diseases, including the roles of energy deficiencies, mitochondrial dysfunction, endoplasmic reticulum (ER) stress, changes in metabolic flux in aging (e.g., Ca2+ and nicotinamide adenine dinucleotide), and alterations in the endoplasmic reticulum-mitochondria contact sites that regulate the trafficking of metabolites. Tools for single-cell resolution of metabolite pools and metabolic flux in animal models of aging and age-related diseases are urgently needed. High-resolution mass spectrometry imaging (MSI) provides a revolutionary approach for capturing the metabolic states of individual cells and cellular interactions without the dissociation of tissues. mass spectrometry imaging can be a powerful tool to elucidate the role of stress-induced cellular dysfunction in aging.

Analysis of Single Biomacromolecules and Viruses: Is It a Myth or Reality?

The beginning of the twenty-first century witnessed novel breakthrough research directions in the life sciences, such as genomics, transcriptomics, translatomics, proteomics, metabolomics, and bioinformatics. A newly developed single-molecule approach addresses the physical and chemical properties and the functional activity of single (individual) biomacromolecules and viral particles. Within the alternative approach, the combination of "single-molecule approaches" is opposed to "omics approaches". This new approach is fundamentally unique in terms of its research object (a single biomacromolecule). Most studies are currently performed using postgenomic technologies that allow the properties of several hundreds of millions or even billions of biomacromolecules to be analyzed. This paper discusses the relevance and theoretical, methodological, and practical issues related to the development potential of a single-molecule approach using methods based on molecular detectors.

Illuminating Intrinsically Disordered Proteins with Integrative Structural Biology

Intense study of intrinsically disordered proteins (IDPs) did not begin in earnest until the late 1990s when a few groups, working independently, convinced the community that these 'weird' proteins could have important functions. Over the past two decades, it has become clear that IDPs play critical roles in a multitude of biological phenomena with prominent examples including coordination in signaling hubs, enabling gene regulation, and regulating ion channels, just to name a few. One contributing factor that delayed appreciation of IDP functional significance is the experimental difficulty in characterizing their dynamic conformations. The combined application of multiple methods, termed integrative structural biology, has emerged as an essential approach to understanding IDP phenomena. Here, we review some of the recent applications of the integrative structural biology philosophy to study IDPs.

Comprehensive Survey of Consensus Docking for High-Throughput Virtual Screening

The rapid advances of 3D techniques for the structural determination of proteins and the development of numerous computational methods and strategies have led to identifying highly active compounds in computer drug design. Molecular docking is a method widely used in high-throughput virtual screening campaigns to filter potential ligands targeted to proteins. A great variety of docking programs are currently available, which differ in the algorithms and approaches used to predict the binding mode and the affinity of the ligand. All programs heavily rely on scoring functions to accurately predict ligand binding affinity, and despite differences in performance, none of these docking programs is preferable to the others. To overcome this problem, consensus scoring methods improve the outcome of virtual screening by averaging the rank or score of individual molecules obtained from different docking programs. The successful application of consensus docking in high-throughput virtual screening highlights the need to optimize the predictive power of molecular docking methods.

The premetazoan ancestry of the synaptic toolkit and appearance of first neurons

Neurons, especially when coupled with muscles, allow animals to interact with and navigate through their environment in ways unique to life on earth. Found in all major animal lineages except sponges and placozoans, nervous systems range widely in organization and complexity, with neurons possibly representing the most diverse cell-type. This diversity has led to much debate over the evolutionary origin of neurons as well as synapses, which allow for the directed transmission of information. The broad phylogenetic distribution of neurons and presence of many of the defining components outside of animals suggests an early origin of this cell type, potentially in the time between the first animal and the last common ancestor of extant animals. Here, we highlight the occurrence and function of key aspects of neurons outside of animals as well as recent findings from non-bilaterian animals in order to make predictions about when and how the first neuron(s) arose during animal evolution and their relationship to those found in extant lineages. With advancing technologies in single cell transcriptomics and proteomics as well as expanding functional techniques in non-bilaterian animals and the close relatives of animals, it is an exciting time to begin unraveling the complex evolutionary history of this fascinating animal cell type.

Virus-like Particles: Fundamentals and Biomedical Applications

Nanotechnology is a fast-evolving field focused on fabricating nanoscale objects for industrial, cosmetic, and therapeutic applications. Virus-like particles (VLPs) are self-assembled nanoparticles whose intrinsic properties, such as heterogeneity, and highly ordered structural organization are exploited to prepare vaccines; imaging agents; construct nanobioreactors; cancer treatment approaches; or deliver drugs, genes, and enzymes. However, depending upon the intrinsic features of the native virus from which they are produced, the therapeutic performance of VLPs can vary. This review compiles the recent scientific literature about the fundamentals of VLPs with biomedical applications. We consulted different databases to present a general scenario about viruses and how VLPs are produced in eukaryotic and prokaryotic cell lines to entrap therapeutic cargo. Moreover, the structural classification, morphology, and methods to functionalize the surface of VLPs are discussed. Finally, different characterization techniques required to examine the size, charge, aggregation, and composition of VLPs are described.

Deciphering the role of plant plasma membrane lipids in response to invasion patterns: how could biology and biophysics help?

Plants have to constantly face pathogen attacks. To cope with diseases, they have to detect the invading pathogen as early as possible via the sensing of conserved motifs called invasion patterns. The first step of perception occurs at the plasma membrane. While many invasion patterns are perceived by specific proteinaceous immune receptors, several studies have highlighted the influence of the lipid composition and dynamics of the plasma membrane in the sensing of invasion patterns. In this review, we summarize current knowledge on how some microbial invasion patterns could interact with the lipids of the plasma membrane, leading to a plant immune response. Depending on the invasion pattern, different mechanisms are involved. This review outlines the potential of combining biological with biophysical approaches to decipher how plasma membrane lipids are involved in the perception of microbial invasion patterns.

Heterogeneous cryo-EM projection image classification using a two-stage spectral clustering based on novel distance measures

Single-particle cryo-electron microscopy (cryo-EM) has become one of the mainstream technologies in the field of structural biology to determine the three-dimensional (3D) structures of biological macromolecules. Heterogeneous cryo-EM projection image classification is an effective way to discover conformational heterogeneity of biological macromolecules in different functional states. However, due to the low signal-to-noise ratio of the projection images, the classification of heterogeneous cryo-EM projection images is a very challenging task. In this paper, two novel distance measures between projection images integrating the reliability of common lines, pixel intensity and class averages are designed, and then a two-stage spectral clustering algorithm based on the two distance measures is proposed for heterogeneous cryo-EM projection image classification. In the first stage, the novel distance measure integrating common lines and pixel intensities of projection images is used to obtain preliminary classification results through spectral clustering. In the second stage, another novel distance measure integrating the first novel distance measure and class averages generated from each group of projection images is used to obtain the final classification results through spectral clustering. The proposed two-stage spectral clustering algorithm is applied on a simulated and a real cryo-EM dataset for heterogeneous reconstruction. Results show that the two novel distance measures can be used to improve the classification performance of spectral clustering, and using the proposed two-stage spectral clustering algorithm can achieve higher classification and reconstruction accuracy than using RELION and XMIPP.

Computational strategies to identify new drug candidates against neuroinflammation

The even more increasing application of computational approaches in these last decades has deeply modified the process of discovery and commercialization of new therapeutic entities. This is especially true in the field of neuroinflammation, in which both the peculiar anatomical localization and the presence of the blood-brain barrier makeit mandatory to finely tune the candidates' physicochemical properties from the early stages of the discovery pipeline. The aim of this review is therefore to provide a general overview to the readers about the topic of neuroinflammation, together with the most common computational strategies that can be exploited to discover and design small molecules controlling neuroinflammation, especially those based on the knowledge of the three-dimensional structure of the biological targets of therapeutic interest. The techniques used to describe the molecular recognition mechanisms, such as molecular docking and molecular dynamics, will therefore be eviscerated, highlighting their advantages and their limitations. Finally, we report several case studies in which computational methods have been applied in drug discovery on neuroinflammation, focusing on the last decade's research.

Functions and Regulation of Translation Elongation Factors

Translation elongation is a key step of protein synthesis, during which the nascent polypeptide chain extends by one amino acid residue during one elongation cycle. More and more data revealed that the elongation is a key regulatory node for translational control in health and disease. During elongation, elongation factor Tu (EF-Tu, eEF1A in eukaryotes) is used to deliver aminoacyl-tRNA (aa-tRNA) to the A-site of the ribosome, and elongation factor G (EF-G, EF2 in eukaryotes and archaea) is used to facilitate the translocation of the tRNA₂-mRNA complex on the ribosome. Other elongation factors, such as EF-Ts/eEF1B, EF-P/eIF5A, EF4, eEF3, SelB/EFsec, TetO/Tet(M), RelA and BipA, have been found to affect the overall rate of elongation. Here, we made a systematic review on the canonical and non-canonical functions and regulation of these elongation factors. In particular, we discussed the close link between translational factors and human diseases, and clarified how post-translational modifications control the activity of translational factors in tumors.

Protein of a thousand faces: The tumor-suppressive and oncogenic responses of p53

The p53 protein is a pleiotropic regulator working as a tumor suppressor and as an oncogene. Depending on the cellular insult and the mutational status, p53 may trigger opposing activities such as cell death or survival, senescence and cell cycle arrest or proliferative signals, antioxidant or prooxidant activation, glycolysis, or oxidative phosphorylation, among others. By augmenting or repressing specific target genes or directly interacting with cellular partners, p53 accomplishes a particular set of activities. The mechanism in which p53 is activated depends on increased stability through post-translational modifications (PTMs) and the formation of higher-order structures (HOS). The intricate cell death and metabolic p53 response are reviewed in light of gaining stability via PTM and HOS formation in health and disease.

Using cryo-EM to uncover mechanisms of bacterial transcriptional regulation

Transcription is the principal control point for bacterial gene expression, and it enables a global cellular response to an intracellular or environmental trigger. Transcriptional regulation is orchestrated by transcription factors, which activate or repress transcription of target genes by modulating the activity of RNA polymerase. Dissecting the nature and precise choreography of these interactions is essential for developing a molecular understanding of transcriptional regulation. While the contribution of X-ray crystallography has been invaluable, the 'resolution revolution' of cryo-electron microscopy has transformed our structural investigations, enabling large, dynamic and often transient transcription complexes to be resolved that in many cases had resisted crystallisation. In this review, we highlight the impact cryo-electron microscopy has had in gaining a deeper understanding of transcriptional regulation in bacteria. We also provide readers working within the field with an overview of the recent innovations available for cryo-electron microscopy sample preparation and image reconstruction of transcription complexes.

Generation of a Soluble Form of Human Endoglin Fused to Green Fluorescent Protein

Endoglin (Eng, CD105) is a type I membrane glycoprotein that functions in endothelial cells as an auxiliary receptor for transforming growth factor β (TGF-β)/bone morphogenetic protein (BMP) family members and as an integrin ligand, modulating the vascular pathophysiology. Besides the membrane-bound endoglin, there is a soluble form of endoglin (sEng) that can be generated by the action of the matrix metalloproteinase (MMP)-14 or -12 on the juxtamembrane region of its ectodomain. High levels of sEng have been reported in patients with preeclampsia, hypercholesterolemia, atherosclerosis and cancer. In addition, sEng is a marker of cardiovascular damage in patients with hypertension and diabetes, plays a pathogenic role in preeclampsia, and inhibits angiogenesis and tumor proliferation, migration, and invasion in cancer. However, the mechanisms of action of sEng have not yet been elucidated, and new tools and experimental approaches are necessary to advance in this field. To this end, we aimed to obtain a fluorescent form of sEng as a new tool for biological imaging. Thus, we cloned the extracellular domain of endoglin in the pEGFP-N1 plasmid to generate a fusion protein with green fluorescent protein (GFP), giving rise to pEGFP-N1/Eng.EC. The recombinant fusion protein was characterized by transient and stable transfections in CHO-K1 cells using fluorescence microscopy, SDS-PAGE, immunodetection, and ELISA techniques. Upon transfection with pEGFP-N1/Eng.EC, fluorescence was readily detected in cells, indicating that the GFP contained in the recombinant protein was properly folded into the cytosol. Furthermore, as evidenced by Western blot analysis, the secreted fusion protein yielded the expected molecular mass and displayed a specific fluorescent signal. The fusion protein was also able to bind to BMP9 and BMP10 in vitro. Therefore, the construct described here could be used as a tool for functional in vitro studies of the extracellular domain of endoglin.

Graphene Oxide-Supported Microwell Grids for Preparing Cryo-EM Samples with Controlled Ice Thickness

Cryogenic-electron microscopy (cryo-EM) is the preferred method to determine 3D structures of proteins and to study diverse material systems that intrinsically have radiation or air sensitivity. Current cryo-EM sample preparation methods provide limited control over the sample quality, which limits the efficiency and high throughput of 3D structure analysis. This is partly because it is difficult to control the thickness of the vitreous ice that embeds specimens, in the range of nanoscale, depending on the size and type of materials of interest. Thus, there is a need for fine regulation of the thickness of vitreous ice to deliver consistent high signal-to-noise ratios for low-contrast biological specimens. Herein, an advanced silicon-chip-based device is developed which has a regular array of micropatterned holes with a graphene oxide (GO) window on freestanding silicon nitride (Six Ny ). Accurately regulated depths of micropatterned holes enable precise control of vitreous ice thickness. Furthermore, GO window with affinity for biomolecules can facilitate concentration of the sample molecules at a higher level. Incorporation of micropatterned chips with a GO window enhances cryo-EM imaging for various nanoscale biological samples including human immunodeficiency viral particles, groEL tetradecamers, apoferritin octahedral, aldolase homotetramer complexes, and tau filaments, as well as inorganic materials.

RNA polymerases from low G+C gram-positive bacteria

The low G + C Gram-positive bacteria represent some of the most medically and industrially important microorganisms. They are relied on for the production of food and dietary supplements, enzymes and antibiotics, as well as being responsible for the majority of nosocomial infections and serving as a reservoir for antibiotic resistance. Control of gene expression in this group is more highly studied than in any bacteria other than the Gram-negative model  Escherichia coli, yet until recently no structural information on RNA polymerase (RNAP) from this group was available. This review will summarize recent reports on the high-resolution structure of RNAP from the model low G + C representative  Bacillus subtilis, including the role of auxiliary subunits δ and ε, and outline approaches for the development of antimicrobials to target RNAP from this group.

Image Processing in Cryo-Electron Microscopy of Single Particles: The Power of Combining Methods

Cryo-electron microscopy has established as a mature structural biology technique to elucidate the three-dimensional structure of biological macromolecules. The Coulomb potential of the sample is imaged by an electron beam, and fast semi-conductor detectors produce movies of the sample under study. These movies have to be further processed by a whole pipeline of image-processing algorithms that produce the final structure of the macromolecule. In this chapter, we illustrate this whole processing pipeline putting in value the strength of "meta algorithms," which are the combination of several algorithms, each one with different mathematical rationale, in order to distinguish correctly from incorrectly estimated parameters. We show how this strategy leads to superior performance of the whole pipeline as well as more confident assessments about the reconstructed structures. The "meta algorithms" strategy is common to many fields and, in particular, it has provided excellent results in bioinformatics. We illustrate this combination using the workflow engine, Scipion.

Assessment of the CASP14 assembly predictions

In CASP14, 39 research groups submitted more than 2500 3D models on 22 protein complexes. In general, the community performed well in predicting the fold of the assemblies (for 80% of the targets), although it faced significant challenges in reproducing the native contacts. This is especially the case for the complexes without whole-assembly templates. The leading predictor, BAKER-experimental, used a methodology combining classical techniques (template-based modeling, protein docking) with deep learning-based contact predictions and a fold-and-dock approach. The Venclovas team achieved the runner-up position with template-based modeling and docking. By analyzing the target interfaces, we showed that the complexes with depleted charged contacts or dominating hydrophobic interactions were the most challenging ones to predict. We also demonstrated that if AlphaFold2 predictions were at hand, the interface prediction challenge could be alleviated for most of the targets. All in all, it is evident that new approaches are needed for the accurate prediction of assemblies, which undoubtedly will expand on the significant improvements in the tertiary structure prediction field.

The Cryo-EM Effect: Structural Biology of Neurodegenerative Disease Aggregates

Neurogenerative diseases are characterized by diverse protein aggregates with a variety of microscopic morphologic features. Although ultrastructural studies of human neurodegenerative disease tissues have been conducted since the 1960s, only recently have near-atomic resolution structures of neurodegenerative disease aggregates been described. Solid-state nuclear magnetic resonance spectroscopy and X-ray crystallography have provided near-atomic resolution information about in vitro aggregates but pose logistical challenges to resolving the structure of aggregates derived from human tissues. Recent advances in cryo-electron microscopy (cryo-EM) have provided the means for near-atomic resolution structures of tau, amyloid-β (Aβ), α-synuclein (α-syn), and transactive response element DNA-binding protein of 43 kDa (TDP-43) aggregates from a variety of diseases. Importantly, in vitro aggregate structures do not recapitulate ex vivo aggregate structures. Ex vivo tau aggregate structures indicate individual tauopathies have a consistent aggregate structure unique from other tauopathies. α-syn structures show that even within a disease, aggregate heterogeneity may correlate to disease course. Ex vivo structures have also provided insight into how posttranslational modifications may relate to aggregate structure. Though there is less cryo-EM data for human tissue-derived TDP-43 and Aβ, initial structural studies provide a basis for future endeavors. This review highlights structural variations across neurodegenerative diseases and reveals fundamental differences between experimental systems and human tissue derived protein inclusions.

Current directions in combining simulation-based macromolecular modeling approaches with deep learning

Introduction: Structure-guided drug discovery relies on accurate computational methods for modeling macromolecules. Simulations provide means of predicting macromolecular folds, of discovering function from structure, and of designing macromolecules to serve as drugs. Success rates are limited for any of these tasks, however. Recently, deep neural network-based methods have greatly enhanced the accuracy of predictions of protein structure from sequence, generating excitement about the potential impact of deep learning.Areas covered: This review introduces biologists to deep neural network architecture, surveys recent successes of deep learning in structure prediction, and discusses emerging deep learning-based approaches for structure-function analysis and design. Particular focus is given to the interplay between simulation-based and neural network-based approaches.Expert opinion: As deep learning grows integral to macromolecular modeling, simulation- and neural network-based approaches must grow more tightly interconnected. Modular software architecture must emerge allowing both types of tools to be combined with maximal versatility. Open sharing of code under permissive licenses will be essential. Although experiments will remain the gold standard for reliable information to guide drug discovery, we may soon see successful drug development projects based on high-accuracy predictions from algorithms that combine simulation with deep learning - the ultimate validation of this combination's power.

PARP Power: A Structural Perspective on PARP1, PARP2, and PARP3 in DNA Damage Repair and Nucleosome Remodelling

Poly (ADP-ribose) polymerases (PARP) 1-3 are well-known multi-domain enzymes, catalysing the covalent modification of proteins, DNA, and themselves. They attach mono- or poly-ADP-ribose to targets using NAD⁺ as a substrate. Poly-ADP-ribosylation (PARylation) is central to the important functions of PARP enzymes in the DNA damage response and nucleosome remodelling. Activation of PARP happens through DNA binding via zinc fingers and/or the WGR domain. Modulation of their activity using PARP inhibitors occupying the NAD⁺ binding site has proven successful in cancer therapies. For decades, studies set out to elucidate their full-length molecular structure and activation mechanism. In the last five years, significant advances have progressed the structural and functional understanding of PARP1-3, such as understanding allosteric activation via inter-domain contacts, how PARP senses damaged DNA in the crowded nucleus, and the complementary role of histone PARylation factor 1 in modulating the active site of PARP. Here, we review these advances together with the versatility of PARP domains involved in DNA binding, the targets and shape of PARylation and the role of PARPs in nucleosome remodelling.

The Cryo-EM Effect: Structural Biology of Neurodegenerative Disease Proteostasis Factors

Neurodegenerative diseases are characterized by the accumulation of misfolded proteins. This protein aggregation suggests that abnormal proteostasis contributes to aging-related neurodegeneration. A better fundamental understanding of proteins that regulate proteostasis may provide insight into the pathophysiology of neurodegenerative disease and may perhaps reveal novel therapeutic opportunities. The 26S proteasome is the key effector of the ubiquitin-proteasome system responsible for degrading polyubiquitinated proteins. However, additional factors, such as valosin-containing protein (VCP/p97/Cdc48) and C9orf72, play a role in regulation and trafficking of substrates through the normal proteostasis systems of a cell. Nonhuman AAA+ ATPases, such as the disaggregase Hsp104, also provide insights into the biochemical processes that regulate protein aggregation. X-ray crystallography and cryo-electron microscopy (cryo-EM) structures not bound to substrate have provided meaningful information about the 26S proteasome, VCP, and Hsp104. However, recent cryo-EM structures bound to substrate have provided new information about the function and mechanism of these proteostasis factors. Cryo-EM and cryo-electron tomography data combined with biochemical data have also increased the understanding of C9orf72 and its role in maintaining proteostasis. These structural insights provide a foundation for understanding proteostasis mechanisms with near-atomic resolution upon which insights can be gleaned regarding the pathophysiology of neurodegenerative diseases.

Crosslinking mass spectrometry: A link between structural biology and systems biology

Protein structure underpins functional roles in all biological processes; therefore, improved understanding of protein structures is of fundamental importance in nearly all biological and biomedical research areas. Traditional techniques such as X-ray crystallography and more recently, cryo-EM, can reveal structural features on isolated proteins/protein complexes at atomic resolution level and have become indispensable tools for structural biology. Crosslinking mass spectrometry (XL-MS), on the other hand, is an emerging technique capable of capturing transient and dynamic information on protein interactions and assemblies in their native environment. The combination of XL-MS with traditional techniques holds potential for bridging the gap between structural biology and systems biology approaches. Such a combination will enable visualization of protein structures and interactions within the crowded macromolecular environment in living systems that can dramatically increase understanding of biological functions. In this review, we first discuss general strategies of XL-MS and then survey recent examples to show how qualitative and quantitative XL-MS studies can be integrated with available protein structural data to better understand biological function at systems level.

Beyond history and "on a roll": The list of the most well-studied human protein structures and overall trends in the protein data bank

Of the roughly 20,000 canonical human protein sequences, as of January 20, 2021, 7,077 proteins have had their full or partial, medium- to high-resolution structures determined by x-ray crystallography or other methods. Which of these proteins dominate the protein data bank (the PDB) and why? In this paper, we list the 273 top human protein structures based on the number of their PDB entries. This set of proteins accounts for more than 40% of all available human PDB entries and represent past trends as well as current status for protein structural biology. We briefly discuss the relationship which some of the prominent protein structures have with protein research as a whole and mention their relevance to human diseases. The top-10 soluble and membrane proteins are all well-known (most of their first structures being deposited more than 30 years ago). Overall, there is no dramatic change in recent trends in the PDB. Remarkably, the number of structure depositions has grown nearly exponentially over the last 10 or more years (with a doubling time of 7 years for proteins, obtained from any organism). Growth in human protein structures is slightly faster (at 5.9 years). The information in this paper may be informative to senior scientists but also inspire researchers who are new to protein science, providing the year 2021 snap-shot for the state of protein structural biology.

Volume electron microscopy: analyzing the lung

Since its entry into biomedical research in the first half of the twentieth century, electron microscopy has been a valuable tool for lung researchers to explore the lung's delicate ultrastructure. Among others, it proved the existence of a continuous alveolar epithelium and demonstrated the surfactant lining layer. With the establishment of serial sectioning transmission electron microscopy, as the first "volume electron microscopic" technique, electron microscopy entered the third dimension and investigations of the lung's three-dimensional ultrastructure became possible. Over the years, further techniques, ranging from electron tomography over serial block-face and focused ion beam scanning electron microscopy to array tomography became available. All techniques cover different volumes and resolutions, and, thus, different scientific questions. This review gives an overview of these techniques and their application in lung research, focusing on their fields of application and practical implementation. Furthermore, an introduction is given how the output raw data are processed and the final three-dimensional models can be generated.

Targeting thermoTRP ion channels: in silico preclinical approaches and opportunities

INTRODUCTION

A myriad of cellular pathophysiological responses are mediated by polymodal ion channels that respond to chemical and physical stimuli such as thermoTRP channels. Intriguingly, these channels are pivotal therapeutic targets with limited clinical pharmacology. In silico methods offer an unprecedented opportunity for discovering new lead compounds targeting thermoTRP channels with improved pharmacological activity and therapeutic index.

AREAS COVERED

This article reviews the progress on thermoTRP channel pharmacology because of (i) advances in solving their atomic structure using cryo-electron microscopy and, (ii) progress on computational techniques including homology modeling, molecular docking, virtual screening, molecular dynamics, ADME/Tox and artificial intelligence. Together, they have increased the number of lead compounds with clinical potential to treat a variety of pathologies. We used original and review articles from Pubmed (1997-2020), as well as the clinicaltrials.gov database, containing the terms thermoTRP, artificial intelligence, docking, and molecular dynamics.

EXPERT OPINION

The atomic structure of thermoTRP channels along with computational methods constitute a realistic first line strategy for designing drug candidates with improved pharmacology and clinical translation. In silico approaches can also help predict potential side-effects that can limit clinical development of drug candidates. Together, they should provide drug candidates with upgraded therapeutic properties.