Surface layer (S-layer) lattices, composed of proteins and glycoproteins, constitute one of the most abundant and conserved supramolecular structures in the prokaryotic world. These self-assembling, two-dimensional arrays represent a major evolutionary investment, often accounting for up to 10% of total cellular protein synthesis. Despite enormous sequence diversity and adaptation to widely different ecological niches, S-layers persist across phylogeny, suggesting a fundamental selective advantage. In this review, we synthesize historical ultrastructural observations with modern atomic-resolution structural data and biophysical principles to demonstrate that antifouling is a general and fundamental function of all bacterial and archaeal S-layers. We argue that antifouling arises from a sophisticated synergy of lattice dynamics, crystalline nanotopography, electrostatic mosaicity, fragmented hydrophobicity, structured hydration shells and frequently glycan-mediated steric repulsion. We specifically place S-layer antifouling into the physical framework of life at low Reynolds numbers, where even minimal surface fouling imposes severe energetic penalties on nutrient acquisition and motility. We also highlight the S-layer as a tunable interface that suppresses non-specific fouling while precisely gating specific molecular interactions and community formation. Finally, we discuss how this universal biophysical strategy provides a powerful blueprint for biomimetic surface engineering in (nano)biotechnology, synthetic biology, and materials science.
Lasing spectroscopy (LS) is emerging as a powerful extension of conventional fluorescence methods for highly sensitive bioanalytical detection. By exploiting stimulated emission and optical feedback mechanisms, LS generates narrow spectral linewidths, threshold-dependent emission, and highly directional radiation, enabling enhanced signal-to-noise ratios and improved sensitivity compared with traditional fluorescence spectroscopy. In bioanalytical systems, subtle molecular events such as biomolecular binding, conformational transitions, or local refractive-index changes can significantly modify lasing thresholds, emission intensity, or spectral position, providing sensitive optical readouts of biochemical processes. This review presents a comprehensive overview of LS methodologies and their emerging applications in biomedical research. The discussion is structured according to a graded framework of increasing optical and methodological complexity, beginning with mirrorless amplified spontaneous emission (ASE) and random lasing (RL) in solid-state biomolecular matrices, followed by engineered photonic architectures, including distributed-feedback gratings and nanoporous anodic alumina (NAA) structures. More advanced resonator-based configurations in liquids, such as Fabry–Pérot (FP) cavities, whispering-gallery-mode microresonators, and optofluidic droplet lasers, are also examined. Across these platforms, LS is shown to enable ultrasensitive bioanalytical detection and novel diagnostic strategies, including early detection of protein aggregation, monitoring nucleic-acid conformational states, tissue- and single-cell laser diagnostics, and label-free refractometric biosensing. Finally, the review highlights current technical challenges, including dye photostability, cavity engineering, and measurement standardization, and discusses future perspectives for translating lasing-based bioanalytics toward clinically relevant diagnostics in neurodegenerative diseases, oncology, metabolic disorders, and infectious diseases.
The activity of membrane-active peptides/proteins (MAPs) involves interactions with lipid bilayer regions of cell membranes. For example, antimicrobial peptides, lytic peptides, pore-forming toxins, lipidated peptides, and cell-penetrating peptides are all MAPs. Most MAPs induce damage in cell membranes/lipid bilayers, such as nanopore formation. Various methods have been employed to examine the interactions between MAPs and lipid bilayers, as well as MAP-induced membrane damage. Methods using giant unilamellar vesicles (GUVs) are particularly versatile techniques because they provide useful information regarding both MAP-lipid bilayer interactions and MAP activities such as membrane damage. GUV studies have revealed many aspects of elementary processes of MAP-induced membrane damage and their correlations, thus clarifying the mechanisms of MAPs-induced membrane damage. Here, we focus on GUV-based studies of MAP-induced nanopore formation in lipid bilayers. First, we review the binding of MAPs to the lipid bilayers. Second, we review the rate of MAP-induced nanopore formation and the rate of membrane permeation of fluorescent probes through the nanopores. Third, we review the relationships between several elementary processes involved in MAP-induced nanopore formation (i.e., binding of MAPs, nanopore formation, translocation of MAPs across lipid bilayers) and factors that induce membrane instability to facilitate nanopore formation. The pre-pore model of translocation of MAPs across lipid bilayers is also reviewed. Fourth, we review the effects of membrane tension, membrane potential, and lipid composition on MAP-induced formation of nanopores and their stability. Finally, we describe our perspectives on future GUV-based studies of MAP-induced nanopore formation.
In an editorial for a Special Issue, Nussinov and Wolynes explored the energy landscapes of biomolecular function, questioning whether they constituted a second molecular biology revolution. With more than a decade having passed and science having progressed significantly, we revisit this question. Statistical energy landscapes not only visualize folding funnels but also quantify the likelihoods of different states, embodying the foundational physical-chemical principles of protein actions. Building upon the theory of energy landscapes, the conformational selection and population shift paradigm posited that since all functional conformations already pre-exist in a dynamic equilibrium, a ligand 'selects' and stabilizes a state from this pre-existing pool, resulting in re-equilibration, or shift, of the population. The principle that it established - that function harnesses transitions between pre-existing conformations - revolutionized the understanding of allostery and, broadly, regulation. This paradigm challenged and superseded the decades-old, albeit persisting, belief of only one (or two; 'open' and 'closed') protein conformations. It also indicates that for engineered proteins to exert effective function, we must account for the timescales of flipping between energy landscape states, for example, by tuning the barrier heights. Returning to the question of whether landscapes constituted a second biomolecular biology revolution, we consider their bedrock contributions, which are far beyond the original protein folding funnels. They established the principle of multiple dynamic conformational states 'jumping' over barriers during population shifts. By leveraging core concepts like conformational ensembles, modern molecular biology has achieved breakthroughs such as next-generation allosteric drugs, indeed leading to a transformative era in molecular science.
L-α-amino acids are the fundamental building blocks of proteins and play a pivotal role in the biochemistry of living organisms. The behavior of these molecules in an aqueous solution – the primary medium for biological reactions – is contingent on their physicochemical properties, including molecular structure and dissociation constants (Ka). The objective of this article is to provide a comprehensive description of the chemical significance of amino acids in an aqueous environment. This encompasses their ionization states at varying pH, interactions with water molecules, environmental effects (e.g., ionic strength, temperature, the presence of other ions, and pressure), and the implications of these factors for the stability and biological function of the example peptides and proteins. The article also presents a discussion of contemporary experimental and computational methodologies employed in the study of the physicochemical properties of amino acids in an aqueous solution. It is imperative that these relationships are comprehended if advancements in the fields of drug design, protein engineering, and biotechnology are to be facilitated.
Octahedral transition metal complexes are increasingly recognised as useful tools for the development of complex cations that recognise and interact with specific DNA sequences and higher-order DNA topologies. The versatility and diversity of these complexes is particularly due to their rich photophysical and electrochemical properties at the octahedral metal centre, which can be modulated by changing the surrounding ligands. While X-ray crystallography provides uniquely direct structural information on metal-DNA binding, it is one of several essential approaches; solution-state methods such as NMR and complementary biophysical studies are critical for defining predominant binding modes in solution and in biologically relevant environments. Here, we present an overview of the different binding modes of some of these octahedral transition metal complexes with DNA, emphasising the structural and biophysical studies employed to understand metal complex-DNA interactions.
Intrinsically disordered proteins (IDPs) and disordered regions of folded proteins (IDRs) perform a plethora of cellular functions involving interactions with a variety of proteins, DNA, and RNA. Their flexibility enables them to interact with different cellular components. They can adopt molten globule as well as extended statistical coil structures depending on their amino acid residue sequence. They are generally more enriched in polar and charged residues, which generally facilitate solvation. This review article asks to what extent water as a solvent affects local (on a residue level) and global properties (size, Flory exponents) of IDPs. It introduces various aspects of protein hydration in the folded state as a benchmark and reference. The results of experimental and computational studies on short model peptides reveal how local structural propensities of residues are determined by water-backbone and water-side chain interactions. Ramachandran plots of individual amino acid residues are side-chain and neighbor-dependent. For unfolded oligo-peptides and IDPs (IDRs) the article discusses the intricated relationship between IDP hydration and global parameters (i.e., radius of gyration), which involves multiple parameters such as net charge, charge distribution, hydrophobicity, and the ionic strength of the aqueous solution. A review of experimental work that explored the strength of water-protein interactions and their influence on water dynamics reveals significant differences between water binding to folded and disordered proteins. Finally, The role of water in liquid-liquid mixing of short peptides and IDPs is delineated, which can lead to gelation and the formation of membrane-less droplets.
In 2019, in this journal, I discussed approaches for controlling the movement of molecules, in particular macromolecules, with an emphasis on how this enabled advances in the field of drug delivery - a field that has impacted billions of people worldwide. Since 2019, there have been advances in our work and this field including a striking demonstration in which drug delivery nanoparticles were crucial to the success of mRNA therapies and the Covid-19 vaccine. In this paper, I provide updates in such areas as i) developing new methods for oral drug delivery systems, ii) delivery of molecules to specific sites of the body, iii) new types of delivery systems, and iv) examples of machine learning/artificial intelligence in these areas. I also discuss advances in mRNA technology as it relates to drug delivery and the development of nanoparticles to protect and deliver vaccines, which saved and improved the lives of hundreds of millions of people throughout the world.
Allosteric communication is established by networks through which strain energy generated at the allosteric site by an allosteric event, such as ligand binding, can propagate to the functional site. Exerted on multiple molecules in the cell, it can wield a biased function. Here, we discuss allosteric networks and allosteric signaling bias. Networks are graphs specified by nodes (residues) and edges (their connections). Allosteric bias is a property of a population. It is described by allosteric effector-specific dynamic distributions of conformational ensembles, as classically exemplified by G protein-coupled receptors (GPCRs). An ensemble describes the likelihood of a specific (strong/weak) allosteric signal propagating to a specific functional site. A network description provides the propagation route in a specific conformation, pinpointing key residues whose mutations could promote drug resistance. Efficiency is influenced by path length, relative stabilities and allosteric transitions. Through specific contacts, specific ligands can bias signaling in proteins, for example, in receptor tyrosine kinases (RTKs) toward specific phosphorylation sites and cell signaling activation. Thus, rather than the two - active and inactive - states, and a single pathway, we consider multiple states and favored pathways. This allows us to consider biased allosteric switches among minor, invisible states and observable outcomes. Within this framework, we further consider signaling strength and duration as key determinants of cell fate: If weak and sustained, it may induce differentiation; If bursts of strong and short, proliferation.
Time-resolved (TR) intrinsic fluorescence of tryptophan (Trp) provides a wealth of information on the structure and localization of proteins and peptides and their interactions with one another, with drugs, lipid membranes, lipid- and surfactant-based drug delivery systems, et cetera. Intrinsic Trp eliminates the need for labeling and avoids the perturbation of the system by the label; introduced Trp is a rather conservative and small label compared to others. Whereas custom-tailored fluorophores are often optimized for a special technique, Trp can be employed to monitor a wide variety of effects. We address interactions of Trp with surrounding molecules, dynamic quenchers and Förster resonance energy transfer (FRET) acceptors that affect the fluorescence decay. Speed and range of angular motion of Trp are characterized by TR anisotropy. Electrostatic interactions of Trp with charged and polar molecules, including water, are monitored by decay-associated spectra (DAS) or TR emission spectra (TRES) and quantified in terms of TR shifts of the spectral center of gravity. This versatility is a great advantage and, at the same time, comes with a complexity of the behavior that can render it a challenge to interpret the data in detail properly. This review provides an overview of applications of TR fluorescence of Trp bulk samples in biomolecular, biophysical, and pharmaceutical studies. The aim is not only to point out the diversity of the read-out of these techniques, but also critically examine their current use. Therefore, we identify most common technical pitfalls and evaluate the degree of reliability of the interpretational approaches. This should aid a more extensive and meaningful use of TR fluorescence of Trp.
The question of whether PCR is reliable sounds strange at first. However, looking at the scientific literature from the 1950s and 60s, one will find many publications on the physicochemistry of DNA that have been forgotten meanwhile. Quite a few of these studies have shown that DNA is thermolabile, which consequently raises the question of whether this thermolability is relevant in the context of PCR, namely in the denaturation phase. However, it can be shown that this is not the case: losses due to thermal hydrolysis are irrelevant for the performance of contemporary PCR protocols and their specificity as well as for the significance of their results. There is now a huge amount of scientifically verified and published data on technical and molecular aspects of PCR, a small selection of which we quote here. In addition, we present some primary data that also clearly demonstrate the reliability of PCR.
Neurotransmitter release via synaptic vesicle fusion with the plasma membrane is driven by SNARE proteins (Synaptobrevin, Syntaxin, and SNAP-25) and accessory proteins (Synaptotagmin, Complexin, Munc13, and Munc18). While extensively studied experimentally, the precise mechanisms and dynamics remain elusive due to spatiotemporal limitations. Molecular dynamics (MD) simulations-both all-atom (AA) and coarse-grained (CG)-bridge these gaps by capturing fusion dynamics beyond experimental resolution. This review explores the use of these simulations in understanding SNARE-mediated membrane fusion and its regulation by Synaptotagmin and Complexin. We first examine two competing hypotheses regarding the driving force of fusion: (1) SNARE zippering transducing energy through rigid juxtamembrane domains (JMDs) and (2) SNAREs generating entropic forces via flexible JMDs. Despite different origins of forces, the conserved fusion pathway - from membrane adhesion to stalk and fusion pore (FP) formation - emerges across models. We also highlight the critical role of SNARE transmembrane domains (TMDs) and their regulation by post-translational modifications like palmitoylation in fast fusion. Further, we review Ca²⁺-dependent interactions of Synaptotagmin's C2 domains with lipids and SNAREs at the primary and tripartite interfaces, and how these interactions regulate fusion timing. Complexin's role in clamping spontaneous fusion while facilitating evoked release via its central and accessory helices is also discussed. We present a case study leveraging AA and CG simulations to investigate ion selectivity in FPs, balancing timescale and accuracy. We conclude with the limitations in current simulations and using AI tools to construct complete fusion machinery and explore isoform-specific functions in fusion machinery.
Riboswitches are RNA elements with a defined structure found in noncoding sections of genes that allow the direct control of gene expression by the binding of small molecules functionally related to the gene product. In most cases, this is a metabolite in the same (typically biosynthetic) pathway as an enzyme (or transporter) encoded by the gene that is controlled. The structures of many riboswitches have been determined and this provides a large database of RNA structure and ligand binding. In this review, we extract general principles of RNA structure and the manner or ligand binding from this resource.
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.
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.
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.
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.
Allostery describes the ability of biological macromolecules to transmit signals spatially through the molecule from an allosteric site – a site that is distinct from orthosteric binding sites of primary, endogenous ligands – to the functional or active site. This review starts with a historical overview and a description of the classical example of allostery – hemoglobin – and other well-known examples (aspartate transcarbamoylase, Lac repressor, kinases, G-protein-coupled receptors, adenosine triphosphate synthase, and chaperonin). We then discuss fringe examples of allostery, including intrinsically disordered proteins and inter-enzyme allostery, and the influence of dynamics, entropy, and conformational ensembles and landscapes on allosteric mechanisms, to capture the essence of the field. Thereafter, we give an overview over central methods for investigating molecular mechanisms, covering experimental techniques as well as simulations and artificial intelligence (AI)-based methods. We conclude with a review of allostery-based drug discovery, with its challenges and opportunities: with the recent advent of AI-based methods, allosteric compounds are set to revolutionize drug discovery and medical treatments.
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.
