Solving the mechanism of a chemical reaction requires determining the structures of all the ground states on the pathway and the elusive transition states linking them. 2024 is the centenary of Brønsted’s landmark paper that introduced the β-value and structure-activity studies as the only experimental means to infer the structures of transition states. It involves making systematic small changes in the covalent structure of the reactants and analysing changes in activation and equilibrium-free energies. Protein engineering was introduced for an analogous procedure, Φ-value analysis, to analyse the noncovalent interactions in proteins central to biological chemistry. The methodology was developed first by analysing noncovalent interactions in transition states in enzyme catalysis. The mature procedure was then applied to study transition states in the pathway of protein folding – ‘part (b) of the protein folding problem’. This review describes the development of Φ-value analysis of transition states and compares and contrasts the interpretation of β- and Φ-values and their limitations. Φ-analysis afforded the first description of transition states in protein folding at the level of individual residues. It revealed the nucleation-condensation folding mechanism of protein domains with the transition state as an expanded, distorted native structure, containing little fully formed secondary structure but many weak tertiary interactions. A spectrum of transition states with various degrees of structural polarisation was then uncovered that spanned from nucleation-condensation to the framework mechanism of fully formed secondary structure. Φ-analysis revealed how movement of the expanded transition state on an energy landscape accommodates the transition from framework to nucleation-condensation mechanisms with a malleability of structure as a unifying feature of folding mechanisms. Such movement follows the rubric of analysis of classical covalent chemical mechanisms that began with Brønsted. Φ-values are used to benchmark computer simulation, and Φ and simulation combine to describe folding pathways at atomic resolution.

Optogenetics, the use of microbial rhodopsins to make the electrical activity of targeted neurons controllable by light, has swept through neuroscience, enabling thousands of scientists to study how specific neuron types contribute to behaviors and pathologies, and how they might serve as novel therapeutic targets. By activating a set of neurons, one can probe what functions they can initiate or sustain, and by silencing a set of neurons, one can probe the functions they are necessary for. We here review the biophysics of these molecules, asking why they became so useful in neuroscience for the study of brain circuitry. We review the history of the field, including early thinking, early experiments, applications of optogenetics, pre-optogenetics targeted neural control tools, and the history of discovering and characterizing microbial rhodopsins. We then review the biophysical attributes of rhodopsins that make them so useful to neuroscience – their classes and structure, their photocycles, their photocurrent magnitudes and kinetics, their action spectra, and their ion selectivity. Our hope is to convey to the reader how specific biophysical properties of these molecules made them especially useful to neuroscientists for a difficult problem – the control of high-speed electrical activity, with great precision and ease, in the brain.

DNA dynamics can only be understood by taking into account its complex mechanical behavior at different length scales. At the micrometer level, the mechanical properties of single DNA molecules have been well-characterized by polymer models and are commonly quantified by a persistence length of 50 nm (~150 bp). However, at the base pair level (~3.4 Å), the dynamics of DNA involves complex molecular mechanisms that are still being deciphered. Here, we review recent single-molecule experiments and molecular dynamics simulations that are providing novel insights into DNA mechanics from such a molecular perspective. We first discuss recent findings on sequence-dependent DNA mechanical properties, including sequences that resist mechanical stress and sequences that can accommodate strong deformations. We then comment on the intricate effects of cytosine methylation and DNA mismatches on DNA mechanics. Finally, we review recently reported differences in the mechanical properties of DNA and double-stranded RNA, the other double-helical carrier of genetic information. A thorough examination of the recent single-molecule literature permits establishing a set of general ‘rules’ that reasonably explain the mechanics of nucleic acids at the base pair level. These simple rules offer an improved description of certain biological systems and might serve as valuable guidelines for future design of DNA and RNA nanostructures.

CryoEM has become the method of choice for determining the structure of large macromolecular complexes in multiple conformations, at resolutions where unambiguous atomic models can be built. Two effects that have limited progress in single-particle cryoEM are (i) beam-induced movement during image acquisition and (ii) protein adsorption and denaturation at the air-water interface during specimen preparation. While beam-induced movement now appears to have been resolved by all-gold specimen support grids with very small holes, surface effects at the air-water interface are a persistent problem. Strategies to overcome these effects include the use of alternative support films and new techniques for specimen deposition. We examine the future potential of recording perfect images of biological samples for routine structure determination at atomic resolution.

Desoxyribosenucleic acid, DNA, and cellulose molecules self-assemble in aqueous systems. This aggregation is the basis of the important functions of these biological macromolecules. Both DNA and cellulose have significant polar and nonpolar parts and there is a delicate balance between hydrophilic and hydrophobic interactions. The hydrophilic interactions related to net charges have been thoroughly studied and are well understood. On the other hand, the detailed roles of hydrogen bonding and hydrophobic interactions have remained controversial. It is found that the contributions of hydrophobic interactions in driving important processes, like the double-helix formation of DNA and the aqueous dissolution of cellulose, are dominating whereas the net contribution from hydrogen bonding is small. In reviewing the roles of different interactions for DNA and cellulose it is useful to compare with the self-assembly features of surfactants, the simplest case of amphiphilic molecules. Pertinent information on the amphiphilic character of cellulose and DNA can be obtained from the association with surfactants, as well as on modifying the hydrophobic interactions by additives.

Cryo-electron microscopy (cryo-EM) has become the technique of choice for structural biology of macromolecular assemblies, after the ‘resolution revolution’ that has occurred in this field since 2012. With a suitable instrument, an appropriate electron detector and, last but not least, a cooperative sample it is now possible to collect images from which macromolecular structures can be determined to better than 2 Å resolution, where reliable atomic models can be built. By electron tomography and sub-tomogram averaging of cryo-samples, it is also possible to reconstruct subcellular structures to sub-nanometre resolution. This review describes the infrastructure that is needed to achieve this goal. Ideally, a cryo-EM lab will have a dedicated 300 kV electron microscope for data recording and a 200 kV instrument for screening cryo-samples, both with direct electron detectors, and at least one 120 kV EM for negative-stain screening at room temperature. Added to this should be ancillary equipment for specimen preparation, including a light microscope, carbon coater, plasma cleaner, glow discharge unit, a device for fast, robotic sample freezing, liquid nitrogen storage Dewars and a ready supply of clean liquid nitrogen. In practice, of course, the available budget will determine the number and types of microscopes and how elaborate the lab can be. The cryo-EM lab should be designed with adequate space for the electron microscopes and ancillary equipment, and should allow for sufficient storage space. Each electron microscope room should be connected to the image-processing computers by fibre-optic cables for the rapid transfer of large datasets. The cryo-EM lab should be overseen by a facility manager whose responsibilities include the day-to-day tasks to ensure that all microscopes are operating perfectly, organising service and repairs to minimise downtime, and controlling the budget. Large facilities will require additional support staff who help to oversee the operation of the facility and instruct new users.

DNA polymerases play a central role in biology by transferring genetic information from one generation to the next during cell division. Harnessing the power of these enzymes in the laboratory has fueled an increase in biomedical applications that involve the synthesis, amplification, and sequencing of DNA. However, the high substrate specificity exhibited by most naturally occurring DNA polymerases often precludes their use in practical applications that require modified substrates. Moving beyond natural genetic polymers requires sophisticated enzyme-engineering technologies that can be used to direct the evolution of engineered polymerases that function with tailor-made activities. Such efforts are expected to uniquely drive emerging applications in synthetic biology by enabling the synthesis, replication, and evolution of synthetic genetic polymers with new physicochemical properties.

The strong, long-range electrostatic forces described by Coulomb's law disappear for ions in water, and the behavior of these ions is instead controlled by their water affinity – a weak, short-range force which arises from their charge density. This was established experimentally in the mid-1980s by size-exclusion chromatography on carefully calibrated Sephadex® G-10 (which measures the effective volume and thus the water affinity of an ion) and by neutron diffraction with isotopic substitution (which measures the density and orientation of water molecules near the diffracting ion and thus its water affinity). These conclusions have been confirmed more recently by molecular dynamics simulations, which explicitly model each individual water molecule. This surprising change in force regime occurs because the oppositely charged ions in aqueous salt solutions exist functionally as ion pairs (separated by 0, 1 or 2 water molecules) as has now been shown by dielectric relaxation spectroscopy; this cancels out the strong long-range electrostatic forces and allows the weak, short-range water affinity effects to come to the fore. This microscopic structure of aqueous salt solutions is not captured by models utilizing a macroscopic dielectric constant. Additionally, the Law of Matching Water Affinity, first described in 1997 and 2004, establishes that contact ion pair formation is controlled by water affinity and is a major determinant of the solubility of charged species since only a net neutral species can change phases.

The development of clustered regularly interspaced short-palindromic repeat (CRISPR)-Cas systems for genome editing has transformed the way life science research is conducted and holds enormous potential for the treatment of disease as well as for many aspects of biotechnology. Here, I provide a personal perspective on the development of CRISPR-Cas9 for genome editing within the broader context of the field and discuss our work to discover novel Cas effectors and develop them into additional molecular tools. The initial demonstration of Cas9-mediated genome editing launched the development of many other technologies, enabled new lines of biological inquiry, and motivated a deeper examination of natural CRISPR-Cas systems, including the discovery of new types of CRISPR-Cas systems. These new discoveries in turn spurred further technological developments. I review these exciting discoveries and technologies as well as provide an overview of the broad array of applications of these technologies in basic research and in the improvement of human health. It is clear that we are only just beginning to unravel the potential within microbial diversity, and it is quite likely that we will continue to discover other exciting phenomena, some of which it may be possible to repurpose as molecular technologies. The transformation of mysterious natural phenomena to powerful tools, however, takes a collective effort to discover, characterize, and engineer them, and it has been a privilege to join the numerous researchers who have contributed to this transformation of CRISPR-Cas systems.

Thermally-induced protein unfolding is commonly described with the two-state model. This model assumes only two types of protein molecules in solution, the native (N) and the denatured, unfolded (U) protein. In reality, protein unfolding is a multistep process, even if intermediate states are only sparsely populated. As an alternative approach we explore the Zimm–Bragg theory, originally developed for the α-helix-to-random coil transition of synthetic polypeptides. The theory includes intermediate structures with concentrations determined by the cooperativity of the unfolding reaction. We illustrate the differences between the two-state model and the Zimm–Bragg theory with measurements of apolipoprotein A-1 and lysozyme by differential scanning calorimetry (DSC) and CD spectroscopy. Nine further protein examples are taken from the literature. The Zimm–Bragg theory provides a perfect fit of the calorimetric unfolding transitions for all proteins investigated. In contrast, the transition curves and enthalpies predicted by the two-state model differ considerably from the experimental results. Apolipoprotein A-1 is ~50% α-helical at ambient temperature and its unfolding follows the classical α-helix-to-random coil equilibrium. The unfolding of proteins with little α-helix content, such as lysozyme, can also be analyzed with the Zimm–Bragg theory by introducing the concept of ‘folded’ and ‘unfolded’ peptide units assuming an average unfolding enthalpy per peptide unit. DSC is the method of choice to measure the unfolding enthalpy, $\Delta H_{\rm exp} ^0 $, but CD spectroscopy in combination with the two-state model is often used to deduce the unfolding enthalpy. This can lead to erroneous result. Not only are different enthalpies required to describe the CD and DSC transition curves but these values deviate distinctly from the experimental result. In contrast, the Zimm–Bragg theory predicts the DSC and CD unfolding transitions with the same set of parameters.

It is well-established that dynamics are central to protein function; their importance is implicitly acknowledged in the principles of the Monod, Wyman and Changeux model of binding cooperativity, which was originally proposed in 1965. Nowadays the concept of protein dynamics is formulated in terms of the energy landscape theory, which can be used to understand protein folding and conformational changes in proteins. Because protein dynamics are so important, a key to understanding protein function at the molecular level is to design experiments that allow their quantitative analysis. Nuclear magnetic resonance (NMR) spectroscopy is uniquely suited for this purpose because major advances in theory, hardware, and experimental methods have made it possible to characterize protein dynamics at an unprecedented level of detail. Unique features of NMR include the ability to quantify dynamics (i) under equilibrium conditions without external perturbations, (ii) using many probes simultaneously, and (iii) over large time intervals. Here we review NMR techniques for quantifying protein dynamics on fast (ps-ns), slow (μs-ms), and very slow (s-min) time scales. These techniques are discussed with reference to some major discoveries in protein science that have been made possible by NMR spectroscopy.

Understanding protein–inorganic surface interactions is central to the rational design of new tools in biomaterial sciences, nanobiotechnology and nanomedicine. Although a significant amount of experimental research on protein adsorption onto solid substrates has been reported, many aspects of the recognition and interaction mechanisms of biomolecules and inorganic surfaces are still unclear. Theoretical modeling and simulations provide complementary approaches for experimental studies, and they have been applied for exploring protein–surface binding mechanisms, the determinants of binding specificity towards different surfaces, as well as the thermodynamics and kinetics of adsorption. Although the general computational approaches employed to study the dynamics of proteins and materials are similar, the models and force-fields (FFs) used for describing the physical properties and interactions of material surfaces and biological molecules differ. In particular, FF and water models designed for use in biomolecular simulations are often not directly transferable to surface simulations and vice versa. The adsorption events span a wide range of time- and length-scales that vary from nanoseconds to days, and from nanometers to micrometers, respectively, rendering the use of multi-scale approaches unavoidable. Further, changes in the atomic structure of material surfaces that can lead to surface reconstruction, and in the structure of proteins that can result in complete denaturation of the adsorbed molecules, can create many intermediate structural and energetic states that complicate sampling. In this review, we address the challenges posed to theoretical and computational methods in achieving accurate descriptions of the physical, chemical and mechanical properties of protein-surface systems. In this context, we discuss the applicability of different modeling and simulation techniques ranging from quantum mechanics through all-atom molecular mechanics to coarse-grained approaches. We examine uses of different sampling methods, as well as free energy calculations. Furthermore, we review computational studies of protein–surface interactions and discuss the successes and limitations of current approaches.

In recent decades, in silico absorption, distribution, metabolism, excretion (ADME), and toxicity (T) modelling as a tool for rational drug design has received considerable attention from pharmaceutical scientists, and various ADME/T-related prediction models have been reported. The high-throughput and low-cost nature of these models permits a more streamlined drug development process in which the identification of hits or their structural optimization can be guided based on a parallel investigation of bioavailability and safety, along with activity. However, the effectiveness of these tools is highly dependent on their capacity to cope with needs at different stages, e.g. their use in candidate selection has been limited due to their lack of the required predictability. For some events or endpoints involving more complex mechanisms, the current in silico approaches still need further improvement. In this review, we will briefly introduce the development of in silico models for some physicochemical parameters, ADME properties and toxicity evaluation, with an emphasis on the modelling approaches thereof, their application in drug discovery, and the potential merits or deficiencies of these models. Finally, the outlook for future ADME/T modelling based on big data analysis and systems sciences will be discussed.

In reviewing the structures of membrane proteins determined up to the end of 2009, we present in words and pictures the most informative examples from each family. We group the structures together according to their function and architecture to provide an overview of the major principles and variations on the most common themes. The first structures, determined 20 years ago, were those of naturally abundant proteins with limited conformational variability, and each membrane protein structure determined was a major landmark. With the advent of complete genome sequences and efficient expression systems, there has been an explosion in the rate of membrane protein structure determination, with many classes represented. New structures are published every month and more than 150 unique membrane protein structures have been determined. This review analyses the reasons for this success, discusses the challenges that still lie ahead, and presents a concise summary of the key achievements with illustrated examples selected from each class.