Annual Review of Biophysics - Volume 42, 2013

A macromolecular structure, as measured data or as a list of coordinates or even on-screen as a full atomic model, is an extremely complex and confusing object. The underlying rules of how it folds, moves, and interacts as a biological entity are even less evident or intuitive to the human mind. To do science on such molecules, or to relate them usefully to higher levels of biology, we need to start with a natural history that names their features in meaningful ways and with multiple representations (visual or algebraic) that show some aspect of their organizing principles. The two of us have jointly enjoyed a highly varied and engrossing career in biophysical research over nearly 50 years. Our frequent changes of emphasis are tied together by two threads: first, by finding the right names, visualizations, and methods to help both ourselves and others to better understand the 3D structures of protein and RNA molecules, and second, by redefining the boundary between signal and noise for complex data, in both directions—sometimes identifying and promoting real signal up out of what seemed just noise, and sometimes demoting apparent signal into noise or systematic error. Here we relate parts of our scientific and personal lives, including ups and downs, influences, anecdotes, and guiding principles such as the title theme.

The proteasome refers to a collection of complexes centered on the 20S proteasome core particle (20S CP), a complex of 28 subunits that houses proteolytic sites in its hollow interior. Proteasomes are found in eukaryotes, archaea, and some eubacteria, and their activity is critical for many cellular pathways. Important recent advances include inhibitor binding studies and the structure of the immunoproteasome, whose specificity is altered by the incorporation of inducible catalytic subunits. The inherent repression of the 20S CP is relieved by the ATP-independent activators 11S and Blm10/PA200, whose structures reveal principles of proteasome mechanism. The structure of the ATP-dependent 19S regulatory particle, which mediates degradation of polyubiquitylated proteins, is being revealed by a combination of crystal or NMR structures of individual subunits and electron microscopy reconstruction of the intact complex. Other recent structural advances inform us about mechanisms of assembly and the role of conformational changes in the functional cycle.

Secondary active transporters exploit the electrochemical potential of solutes to shuttle specific substrate molecules across biological membranes, usually against their concentration gradient. Transporters of different functional families with little sequence similarity have repeatedly been found to exhibit similar folds, exemplified by the MFS, LeuT, and NhaA folds. Observations of multiple conformational states of the same transporter, represented by the LeuT superfamily members Mhp1, AdiC, vSGLT, and LeuT, led to proposals that structural changes are associated with substrate binding and transport. Despite recent biochemical and structural advances, our understanding of substrate recognition and energy coupling is rather preliminary. This review focuses on the common folds and shared transport mechanisms of secondary active transporters. Available structural information generally supports the alternating access model for substrate transport, with variations and extensions made by emerging structural, biochemical, and computational evidence.

Connecting the molecular world to biology requires understanding how molecular-scale dynamics propagate upward in scale to define the function of biological structures. To address this challenge, multiscale approaches, including coarse-graining methods, become necessary. We discuss here the theoretical underpinnings and history of coarse-graining and summarize the state of the field, organizing key methodologies based on an emerging paradigm for multiscale theory and modeling of biomolecular systems. This framework involves an integrated, iterative approach to couple information from different scales. The primary steps, which coincide with key areas of method development, include developing first-pass coarse-grained models guided by experimental results, performing numerous large-scale coarse-grained simulations, identifying important interactions that drive emergent behaviors, and finally reconnecting to the molecular scale by performing all-atom molecular dynamics simulations guided by the coarse-grained results. The coarse-grained modeling can then be extended and refined, with the entire loop repeated iteratively if necessary.

Active transport in biological membranes has been traditionally studied using a variety of biochemical and biophysical techniques, including electrophysiology. This review focuses on aspects of electrophysiological methods that make them particularly suited for the investigation of transporter function. Two major approaches to electrical recording of transporter activity are discussed: (a) artificial planar lipid membranes, such as the black lipid membrane and solid supported membrane, which are useful for studies on bacterial transporters and transporters of intracellular compartments, and (b) patch clamp and voltage clamp techniques, which investigate transporters in native cellular membranes. The analytical power of these methods is highlighted by several examples of mechanistic studies of specific membrane proteins, including cytochrome c oxidase, NhaA Na⁺/H⁺ exchanger, ClC-7 H⁺/Cl⁻ exchanger, glutamate transporters, and neutral amino acid transporters. These examples reveal the wealth of mechanistic information that can be obtained when electrophysiological methods are used in combination with rapid perturbation approaches.

Recent calorimetric studies of interactions between small molecules and biomolecular targets have generated renewed interest in the phenomenon of entropy-enthalpy compensation. In these studies, entropic and enthalpic contributions to binding are observed to vary substantially and in an opposing manner as the ligand or protein is modified, whereas the binding free energy varies little. In severe examples, engineered enthalpic gains can lead to completely compensating entropic penalties, frustrating ligand design. Here, we examine the evidence for compensation, as well as its potential origins, prevalence, severity, and ramifications for ligand engineering. We find the evidence for severe compensation to be weak in light of the large magnitude of and correlation between errors in experimental measurements of entropic and enthalpic contributions to binding, though a limited form of compensation may be common. Given the difficulty of predicting or measuring entropic and enthalpic changes to useful precision, or using this information in design, we recommend ligand engineering efforts instead focus on computational and experimental methodologies to directly assess changes in binding free energy.

Volatile anesthetics serve as useful probes of a conserved biological process that is essential to the proper functioning of the central nervous system. A kinetic and thermodynamic analysis of their unusual pharmacological and physiological characteristics has led to a general, predictive theory in which small molecules that adsorb to membranes modulate ion channel function by altering physical properties of membrane bilayers. A kinetic model that is both parsimonious and falsifiable has been developed to test this mechanism. This theory leads to predictions about the structure, function, origin, and evolution of synapses, the etiology of several diseases and disease symptoms affecting the brain, and the mechanism of action of several drugs that are used therapeutically. Neuronal membranes may offer an appealing drug target, given the large number of compounds that adsorb to interfaces and hence membranes.

Allosteric propagation results in communication between distinct sites in the protein structure; it also encodes specific effects on cellular pathways, and in this way it shapes cellular response. One example of long-range effects is binding of morphogens to cell surface receptors, which initiates a cascade of protein interactions that leads to genome activation and specific cellular action. Allosteric propagation results from combinations of multiple factors, takes place through dynamic shifts of conformational ensembles, and affects the equilibria of macromolecular interactions. Here, we (a) emphasize the well-known yet still underappreciated role of allostery in conveying explicit signals across large multimolecular assemblies and distances to specify cellular action; (b) stress the need for quantitation of the allosteric effects; and finally, (c) propose that each specific combination of allosteric effectors along the pathway spells a distinct function. The challenges are colossal; the inspiring reward will be predicting function, misfunction, and outcomes of drug regimes.

The adaptive immune system, which is based on highly diverse antigen receptors that are generated by somatic recombination, arose approximately 500 Mya at the dawn of vertebrate evolution. In jawed vertebrates, adaptive immunity is mediated by antibodies and T cell receptors (TCRs), which are composed of immunoglobulin (Ig) domains containing hypervariable loops that bind antigen. In striking contrast, the adaptive immune receptors of jawless vertebrates, termed variable lymphocyte receptors (VLRs), are constructed from leucine-rich repeat (LRR) modules. Structural studies of VLRs have shown that these LRR-based receptors bind antigens though their concave surface, in addition to a unique hypervariable loop in the C-terminal LRR capping module. These studies have revealed a remarkable example of convergent evolution in which jawless vertebrates adopted the LRR scaffold to recognize as broad a spectrum of antigens as the Ig-based antibodies and TCRs of jawed vertebrates, with altogether comparable affinity and specificity.

Small RNA molecules regulate eukaryotic gene expression during development and in response to stresses including viral infection. Specialized ribonucleases and RNA-binding proteins govern the production and action of small regulatory RNAs. After initial processing in the nucleus by Drosha, precursor microRNAs (pre-miRNAs) are transported to the cytoplasm, where Dicer cleavage generates mature microRNAs (miRNAs) and short interfering RNAs (siRNAs). These double-stranded products assemble with Argonaute proteins such that one strand is preferentially selected and used to guide sequence-specific silencing of complementary target mRNAs by endonucleolytic cleavage or translational repression. Molecular structures of Dicer and Argonaute proteins, and of RNA-bound complexes, have offered exciting insights into the mechanisms operating at the heart of RNA-silencing pathways.

All aspects of DNA metabolism—including transcription, replication, and repair—involve motor enzymes that move along genomic DNA. These processes must all take place on chromosomes that are occupied by a large number of other proteins. However, very little is known regarding how nucleic acid motor proteins move along the crowded DNA substrates that are likely to exist in physiological settings. This review summarizes recent progress in understanding how DNA-binding motor proteins respond to the presence of other proteins that lie in their paths. We highlight recent single-molecule biophysical experiments aimed at addressing this question, with an emphasis placed on analyzing the single-molecule, ensemble biochemical, and in vivo data from a mechanistic perspective.

Advances in our understanding of macromolecular structure come from experimental methods, such as X-ray crystallography, and also computational analysis of the growing number of atomic models obtained from such experiments. The later analyses have made it possible to develop powerful tools for structure prediction and optimization in the absence of experimental data. In recent years, a synergy between these computational methods for crystallographic structure determination and structure prediction and optimization has begun to be exploited. We review some of the advances in the algorithms used for crystallographic structure determination in the Phenix and Crystallography & NMR System software packages and describe how methods from ab initio structure prediction and refinement in Rosetta have been applied to challenging crystallographic problems. The prospects for future improvement of these methods are discussed.

Posttranslational modification is an evolutionarily conserved mechanism for regulating protein activity, binding affinity, and stability. Compared with established posttranslational modifications such as phosphorylation or ubiquitination, posttranslational modification by protons within physiological pH ranges is a less recognized mechanism for regulating protein function. By changing the charge of amino acid side chains, posttranslational modification by protons can drive dynamic changes in protein conformation and function. Addition and removal of a proton is rapid and reversible and, in contrast to most other posttranslational modifications, does not require an enzyme. Signaling specificity is achieved by only a minority of sites in proteins titrating within the physiological pH range. Here, we examine the structural mechanisms and functional consequences of proton posttranslational modification of pH-sensing proteins regulating different cellular processes.

In the past decade, a concerted effort to successfully capture specific tertiary packing interactions produced specific three-dimensional structures for many de novo designed proteins that are validated by nuclear magnetic resonance and/or X-ray crystallographic techniques. However, the success rate of computational design remains low. In this review, we provide an overview of experimentally validated, de novo designed proteins and compare four available programs, RosettaDesign, EGAD, Liang-Grishin, and RosettaDesign-SR, by assessing designed sequences computationally. Computational assessment includes the recovery of native sequences, the calculation of sizes of hydrophobic patches and total solvent-accessible surface area, and the prediction of structural properties such as intrinsic disorder, secondary structures, and three-dimensional structures. This computational assessment, together with a recent community-wide experiment in assessing scoring functions for interface design, suggests that the next-generation protein-design scoring function will come from the right balance of complementary interaction terms. Such balance may be found when more negative experimental data become available as part of a training set.

We review the recent developments in understanding the bacterial chemotaxis signaling pathway by using quantitative modeling methods. The models developed are based on structural information of the signaling complex and the dynamics of the underlying biochemical network. We focus on two important functions of the bacterial chemotaxis signaling pathway: signal amplification and adaptation. We describe in detail the structure and the dynamics of the mathematical models and how they compare with existing experiments, emphasizing the predictability of the models. Finally, we outline future directions for developing the modeling approach to better understand the bacterial chemosensory system.

The number of membrane protein structures in the Protein Data Bank is becoming significant and growing. Here, the transmembrane domain structures of the helical membrane proteins are evaluated to assess the influences of the membrane mimetic environments. Toward this goal, many of the biophysical properties of membranes are discussed and contrasted with those of the membrane mimetics commonly used for structure determination. Although the mimetic environments can perturb the protein structures to an extent that potentially gives rise to misinterpretation of functional mechanisms, there are also many structures that have a native-like appearance. From this assessment, an initial set of guidelines is proposed for distinguishing native-like from nonnative-like membrane protein structures. With experimental techniques for validation and computational methods for refinement and quality assessment and enhancement, there are good prospects for achieving native-like structures for these very important proteins.

Directly observing individual protein molecules in action at high spatiotemporal resolution has long been a holy grail for biological science. This is because we long have had to infer how proteins function from the static snapshots of their structures and dynamic behavior of optical makers attached to the molecules. This limitation has recently been removed to a large extent by the materialization of high-speed atomic force microscopy (HS-AFM). HS-AFM allows us to directly visualize the structure dynamics and dynamic processes of biological molecules in physiological solutions, at subsecond to sub-100-ms temporal resolution, without disturbing their function. In fact, dynamically acting molecules such as myosin V walking on an actin filament and bacteriorhodopsin in response to light are successfully visualized. In this review, we first describe theoretical considerations for the highest possible imaging rate of this new microscope, and then highlight recent imaging studies. Finally, the current limitation and future challenges to explore are described.

Small-angle X-ray scattering (SAXS) is a robust technique for the comprehensive structural characterizations of biological macromolecular complexes in solution. Here, we present a coherent synthesis of SAXS theory and experiment with a focus on analytical tools for accurate, objective, and high-throughput investigations. Perceived SAXS limitations are considered in light of its origins, and we present current methods that extend SAXS data analysis to the super-resolution regime. In particular, we discuss hybrid structural methods, illustrating the role of SAXS in structure refinement with NMR and ensemble refinement with single-molecule FRET. High-throughput genomics and proteomics are far outpacing macromolecular structure determinations, creating information gaps between the plethora of newly identified genes, known structures, and the structure-function relationship in the underlying biological networks. SAXS can bridge these information gaps by providing a reliable, high-throughput structural characterization of macromolecular complexes under physiological conditions.

NF-κB (nuclear factor kappa B) family transcription factors are master regulators of immune and inflammatory processes in response to both injury and infection. In the latent state, NF-κBs are sequestered in the cytosol by their inhibitor IκB (inhibitor of NF-κB) proteins. Upon stimulations of innate immune receptors such as Toll-like receptors and cytokine receptors such as those in the TNF (tumor necrosis factor) receptor superfamily, a series of membrane proximal events lead to the activation of the IKK (IκB kinase). Phosphorylation of IκBs results in their proteasomal degradation and the release of NF-κB for nuclear translocation and activation of gene transcription. Here, we review the plethora of structural studies in these NF-κB activation pathways, including the TRAF (TNF receptor–associated factor) proteins, IKK, NF-κB, ubiquitin ligases, and deubiquitinating enzymes. Although these structures only provide snapshots of isolated processes, an emerging picture is that these signaling cascades coalesce into large oligomeric signaling complexes, or signalosomes, for signal propagation.

The biochemical processes leading to the synthesis of new proteins are random, as they typically involve a small number of diffusing molecules. They lead to fluctuations in the number of proteins in a single cell as a function of time and to cell-to-cell variability of protein abundances. These in turn can lead to phenotypic heterogeneity in a population of genetically identical cells. Phenotypic heterogeneity may have important consequences for the development of multicellular organisms and the fitness of bacterial colonies, raising the question of how it is regulated. Here we review the experimental evidence that transcriptional regulation affects noise in gene expression, and discuss how the noise strength is encoded in the architecture of the promoter region. We discuss how models based on specific molecular mechanisms of gene regulation can make experimentally testable predictions for how changes to the promoter architecture are reflected in gene expression noise.

This review presents a broad survey of experimental microbial evolution, covering diverse topics including trade-offs, epistasis, fluctuating conditions, spatial dynamics, cooperation, aging, and stochastic switching. Emphasis is placed on examples that highlight key conceptual points or address theoretical predictions. Experimental evolution is discussed from two points of view. First, population trajectories are described as adaptive walks on a fitness landscape, whose genetic structure can be probed by experiments. Second, populations are viewed from a physiological perspective, and their nongenetic heterogeneity is examined. Bringing together these two viewpoints remains a major challenge for the future.

Protein structure determination methods using magic-angle spinning solid-state nuclear magnetic resonance (MAS SSNMR) have experienced a remarkable development in the past decade. Significant advances in instrumentation, sample preparation, spectroscopic techniques, and computational methods have made possible the determination of the first high-resolution structures of a peptide and a protein in 2002. Subsequent developments allowed the investigation of larger proteins, the initial application of automated analysis routines, and substantial improvements in structural resolution. The application of these methods has enabled the investigation of amyloid fibril structures, conformational dynamics, and their assembly pathways at an atomic level for the first time, as these are systems not accessible by other common techniques. Recent advances and future trends for protein structure determination using MAS SSNMR, as well as its application to the study of amyloid fibrils, are reviewed.

Ribonuclease P (RNase P) is one of the first ribozymes discovered and it is found in all phylogenetic groups. It is responsible for processing the 5′ end of pre-tRNAs as well as other RNA molecules. RNase P is formed by an RNA molecule responsible for catalysis and one or more proteins. Structural studies of the proteins from different organisms, the bacterial RNA component, and a bacterial RNase P holoenzyme/tRNA complex provide insights into the mechanism of this universal ribozyme. Together with the existing wealth of biochemical information, these studies provide atomic-level information on the mechanism of RNase P and continue to expand our understanding of the structure and architecture of large RNA molecules and ribonucleoprotein complexes, the nature of catalysis by ribozymes, the structural basis of recognition of RNA by RNA molecules, and the evolution of enzymes from the prebiotic, RNA-based world to the modern world.

In the fifty years since the first atomic structure of a protein was revealed, tens of thousands of additional structures have been solved. Like all objects in biology, proteins structures show common patterns that seem to define family relationships. Classification of proteins structures, which started in the 1970s with about a dozen structures, has continued with increasing enthusiasm, leading to two main fold classifications, SCOP and CATH, as well as many additional databases. Classification is complicated by deciding what constitutes a domain, the fundamental unit of structure. Also difficult is deciding when two given structures are similar. Like all of biology, fold classification is beset by exceptions to all rules. Thus, the perspectives of protein fold space that the fold classifications offer differ from each other. In spite of these ambiguities, fold classifications are useful for prediction of structure and function. Studying the characteristics of fold space can shed light on protein evolution and the physical laws that govern protein behavior.

Methods for exerting and measuring forces on single molecules have revolutionized the study of the physics of biology. However, it is often the case that biological processes involve rotation or torque generation, and these parameters have been more difficult to access experimentally. Recent advances in the single-molecule field have led to the development of techniques that add the capability of torque measurement. By combining force, displacement, torque, and rotational data, a more comprehensive description of the mechanics of a biomolecule can be achieved. In this review, we highlight a number of biological processes for which torque plays a key mechanical role. We describe the various techniques that have been developed to directly probe the torque experienced by a single molecule, and detail a variety of measurements made to date using these new technologies. We conclude by discussing a number of open questions and propose systems of study that would be well suited for analysis with torsional measurement techniques.

Cell populations rarely exhibit gene-expression profiles that are homogeneous in time and space. In the temporal domain, dynamical behaviors such as oscillations and pulses of protein production pervade cell biology, underlying phenomena as diverse as circadian rhythmicity, cell cycle control, stress and damage responses, and stem-cell pluripotency. In multicellular populations, spatial heterogeneities are crucial for decision making and development, among many other functions. Cells need to exquisitely coordinate this temporal and spatial variation to survive. Although the spatiotemporal character of gene expression is challenging to quantify experimentally at the level of individual cells, it is beneficial from the modeling viewpoint, because it provides strong constraints that can be probed by theoretically analyzing mathematical models of candidate gene and protein circuits. Here, we review recent examples of temporal dynamics and spatial patterning in gene expression to show how modeling such phenomenology can help us unravel the molecular mechanisms of cellular function.

In eukaryotic cells, membrane compartments are split into two by membrane fission. This ensures discontinuity of membrane containers and thus proper compartmentalization. The first proteic machinery implicated in catalyzing membrane fission was dynamin. Dynamin forms helical collars at the neck of endocytic buds. This structural feature suggested that the helix of dynamin could constrict in order to promote fission of the enclosed membrane. However, verifying this hypothesis revealed itself to be a challenge, which inspired many in vitro and in vivo studies. The primary goal of this review is to discuss recent structural and physical data from biophysical studies that have refined our understanding of the dynamin mechanism. In addition to the constriction hypothesis, other models have been proposed to explain how dynamin induces membrane fission. We present experimental data supporting these various models and assess which model is the most probable.

This review examines size effects observed in the mechanical strength of biopolymers that are organized in microstructures such as fibrils, layered composites, or particle nanocomposites. We review the most important aspects that connect nanoconfinement of basic material constituents at critical length scales to the mechanical performance of the entire material system: elastic modulus, strength, extensibility, and robustness. We outline theoretical and computational analysis as well as experimentation by emphasizing two strategies found in abundant natural materials: confined fibrils as part of fibers and confined mineral platelets that transfer load through a biopolymer interface in nanocomposites. We also discuss the application of confinement as a mechanism to tailor specific material properties in biological systems.

Magic-angle spinning NMR, often in combination with photo-CIDNP, is applied to determine how photosynthetic antennae and reaction centers are activated in the ground state to perform their biological function upon excitation by light. Molecular modeling resolves molecular mechanisms by way of computational integration of NMR data with other structure-function analyses. By taking evolutionary historical contingency into account, a better biophysical understanding is achieved. Chlorophyll cofactors and proteins go through self-assembly trajectories that are engineered during evolution and lead to highly homogeneous protein complexes optimized for exciton or charge transfer. Histidine-cofactor interactions allow biological nanomachines to lower energy barriers for light harvesting and charge separation in photosynthetic energy conversion. In contrast, in primordial chlorophyll antenna aggregates, excessive heterogeneity is paired with much less specific characteristics, and both exciton and charge-transfer character are encoded in the ground state.