Binding sites are key components of biomolecular structures, such as proteins and RNAs, serving as hubs for interactions with other molecules. Identification of the binding sites in macromolecules is essential for structure-based molecular and drug design. However, experimental methods for binding site identification are resource-intensive and time-consuming. In contrast, computational methods enable large-scale binding site identification, structure flexibility analysis, as well as assessment of intermolecular interactions within the binding sites. In this review, we describe recent advances in binding site identification using machine learning methods; we classify the approaches based on the encoding of the macromolecule information about its sequence, structure, template knowledge, geometry, and energetic characteristics. Importantly, we categorize the methods based on the type of the interacting molecule, namely, small molecules, peptides, and ions. Finally, we describe perspectives, limitations, and challenges of the state-of-the-art methods with an emphasis on deep learning-based approaches. These computational approaches aim to advance drug discovery by expanding the druggable genome through the identification of novel binding sites in pharmacological targets and facilitating structure-based hit identification and lead optimization.

Throughout all the domains of life, and even among the co-existing viruses, RNA molecules play key roles in regulating the rates, duration, and intensity of the expression of genetic information. RNA acts at many different levels in playing these roles. Trans-acting regulatory RNAs can modulate the lifetime and translational efficiency of transcripts with which they pair to achieve speedy and highly specific recognition using only a few components. Cis-acting recognition elements, covalent modifications, and changes to the termini of RNA molecules encode signals that impact transcript lifetime, translation efficiency, and other functional aspects. RNA can provide an allosteric function to signal state changes through the binding of small ligands or interactions with other macromolecules. In either cis or trans, RNA can act in conjunction with multi-enzyme assemblies that function in RNA turnover, processing and surveillance for faulty transcripts. These enzymatic machineries have likely evolved independently in diverse life forms but nonetheless share analogous functional roles, implicating the biological importance of cooperative assemblies to meet the exact demands of RNA metabolism. Underpinning all the RNA-mediated processes are two key aspects: specificity, which avoids misrecognition, and speedy action, which confers timely responses to signals. How these processes work and how aberrant RNA species are recognised and responded to by the degradative machines are intriguing puzzles. We review the biophysical basis for these processes. Kinetics of assembly and multivalency of interacting components provide windows of opportunity for recognition and action that are required for the key regulatory events. The thermodynamic irreversibility of RNA-mediated regulation is one emergent feature of biological systems that may help to account for the apparent specificity and optimal rates.

This review article describes the co-evolution of structural biology as a discipline and the Protein Data Bank (PDB), established in 1971 as the first open-access data resource in biology by like-minded structural scientists. As the PDB archive grew in size and scope to encompass macromolecular crystallography, NMR spectroscopy, and cryo-electron microscopy, new technologies were developed to ingest, validate, curate, store, and distribute the information. Community engagement ensured that the needs of structural biologists (data depositors) and data consumers were met. Today, the archive houses more than 230,000 experimentally determined structures of proteins, nucleic acids, and macromolecular machines and their complexes with one another and small-molecule ligands. Aggregate costs of PDB data preservation are ~1% of the cost of structure determination. The enormous impact of PDB data on basic and applied research and education across the natural and medical sciences is presented and highlighted with illustrative examples. Enablement of de novo protein structure prediction (AlphaFold2, RoseTTAfold, OpenFold, etc.) is the most widely appreciated benefit of having a corpus of rigorously validated, expertly curated 3D biostructure data.

All biochemical reactions directly involve structural changes that may occur over a very wide range of timescales from femtoseconds to seconds. Understanding the mechanism of action thus requires determination of both the static structures of the macromolecule involved and short-lived intermediates between reactant and product. This requires either freeze-trapping of intermediates, for example by cryo-electron microscopy, or direct determination of structures in active systems at near-physiological temperature by time-resolved X-ray crystallography. Storage ring X-ray sources effectively cover the time range down to around 100 ps that reveal tertiary and quaternary structural changes in proteins. The briefer pulses emitted by hard X-ray free electron laser sources extend that range to femtoseconds, which covers critical chemical reactions such as electron transfer, isomerization, breaking of covalent bonds, and ultrafast structural changes in light-sensitive protein chromophores and their protein environment. These reactions are exemplified by the time-resolved X-ray studies by two groups of the FAD-based DNA repair enzyme, DNA photolyase, over the time range from 1 ps to 100 μs.

The electron cryomicroscopy (cryo-EM) resolution revolution has shifted structural biology into a new era, enabling the routine structure determination of macromolecular complexes at an unprecedented rate. Building on this, electron cryotomography (cryo-ET) offers the potential to visualise the native three-dimensional organisation of biological specimens, from cells to tissues and even entire organisms. Despite this huge potential, the study of tissue-like multicellular specimens via cryo-ET still presents numerous challenges, wherein many steps in the workflow are being developed or in urgent need of improvement. In this review, we outline the latest techniques currently utilised for in situ imaging of multicellular specimens, while clearly enumerating their associated limitations. We consider every step in typical workflows employed by various laboratories, including sample preparation, data collection and image analysis, to highlight recent progress and showcase prominent success stories. By considering the entire structural biology workflow for multicellular specimens, we identify which future exciting developments in hardware and software could enable comprehensive in situ structural biology investigations, bringing forth a new age of discovery in molecular structural and cell biology.

Prokaryotic microorganisms, comprising Bacteria and Archaea, exhibit a fascinating diversity of cell envelope structures reflecting their adaptations that contribute to their resilience and survival in diverse environments. Among these adaptations, surface layers (S-layers) composed of monomolecular protein or glycoprotein lattices are one of the most observed envelope components. They are the most abundant cellular proteins and represent the simplest biological membranes that have developed during evolution. S-layers provide organisms with a great variety of selective advantages, including acting as an antifouling layer, protective coating, molecular sieve, ion trap, structure involved in cell and molecular adhesion, surface recognition and virulence factor for pathogens. In Archaea that possess S-layers as the exclusive cell wall component, the (glyco)protein lattices function as a cell shape-determining/maintaining scaffold. The wealth of information available on the structure, chemistry, genetics and in vivo and in vitro morphogenesis has revealed a broad application potential for S-layers as patterning elements in a molecular construction kit for bio- and nanotechnology, synthetic biology, biomimetics, biomedicine and diagnostics. In this review, we try to describe the scientifically exciting early days of S-layer research with a special focus on the ‘Vienna-S-Layer-Group’. Our presentation is intended to illustrate how our curiosity and joy of discovery motivated us to explore this new structure and to make the scientific community aware of its relevance in the realm of prokaryotes, and moreover, how we developed concepts for exploiting this unique self-assembly structure. We hope that our presentation, with its many personal notes, is also of interest from the perspective of the history of S-layer research.

The GABA type A receptor (GABAAR) belongs to the family of pentameric ligand-gated ion channels and plays a key role in inhibition in adult mammalian brains. Dysfunction of this macromolecule may lead to epilepsy, anxiety disorders, autism, depression, and schizophrenia. GABAAR is also a target for multiple physiologically and clinically relevant modulators, such as benzodiazepines (BDZs), general anesthetics, and neurosteroids. The first GABAAR structure appeared in 2014, but the past years have brought a particularly abundant surge in structural data for these receptors with various ligands and modulators. Although the open conformation remains elusive, this novel information has pushed the structure–function studies to an unprecedented level. Electrophysiology, mutagenesis, photolabeling, and in silico simulations, guided by novel structural information, shed new light on the molecular mechanisms of receptor functioning. The main goal of this review is to present the current knowledge of GABAAR functional and structural properties. The review begins with an outline of the functional and structural studies of GABAAR, accompanied by some methodological considerations, especially biophysical methods, enabling the reader to follow how major breakthroughs in characterizing GABAAR features have been achieved. The main section provides a comprehensive analysis of the functional significance of specific structural elements in GABAARs. We additionally summarize the current knowledge on the binding sites for major GABAAR modulators, referring to the molecular underpinnings of their action. The final chapter of the review moves beyond examining GABAAR as an isolated macromolecule and describes the interactions of the receptor with other proteins in a broader context of inhibitory plasticity. In the final section, we propose a general conclusion that agonist binding to the orthosteric binding sites appears to rely on local interactions, whereas conformational transitions of bound macromolecule (gating) and allosteric modulation seem to reflect more global phenomena involving vast portions of the macromolecule.

Yeast frataxin (Yfh1) is a small natural protein from yeast that has the unusual property of undergoing cold denaturation at temperatures above the freezing point of water when under conditions of low ionic strength. This peculiarity, together with remarkable resilience, allows the determination, for the whole protein as well as for individual residues, of the stability curve, that is the temperature dependence of the free energy difference between the unfolded and folded forms. The ease of measuring stability curves without the need to add denaturants or introduce ad hoc destabilizing mutations makes this protein an ideal ‘tool’ for investigating the influence of many environmental factors on protein stability. The present review aims at recapitulating all the open questions that Yfh1 has helped to address, including understanding the differences and commonalities of the cold, heat and pressure unfolded states. This protein thus offers a unique tool for studying aspects of protein stability so far been considered difficult to assess and provides important guidelines that could allow the identification of other similar systems.

The ‘Viroporin’ family comprises a number of mostly small-sized, integral membrane proteins encoded by animal and plant viruses. Despite their sequence and structural diversity, viroporins share a common functional trend: their capacity to assemble transmembrane channels during the replication cycle of the virus. Their selectivity spectrum ranges from low-pH-activated, unidirectional proton transporters, to size-limited permeating pores allowing passive diffusion of metabolites. Through mechanisms not fully understood, expression of viroporins facilitates virion assembly/release from infected cells, and subverts the cell physiology, contributing to cytopathogenicity. Compounds that interact with viroporins and interfere with their membrane-permeabilizing activity in vitro, are known to inhibit virus production. Moreover, viroporin-defective viruses comprise a source of live attenuated vaccines that prevent infection by notorious human and livestock pathogens. This review dives into the origin and evolution of the viroporin concept, summarizes some of the methodologies used to characterize the structure–function relationships of these important virulence factors, and attempts to classify them on biophysical grounds attending to their mechanisms of ion/solute transport across membranes.