Annual Review of Biophysics - Volume 36, 2007

Synthetic circuits offer great promise for generating insights into nature's underlying design principles or forward engineering novel biotechnology applications. However, construction of these circuits is not straightforward. Synthetic circuits generally consist of components optimized to function in their natural context, not in the context of the synthetic circuit. Combining mathematical modeling with directed evolution offers one promising means for addressing this problem. Modeling identifies mutational targets and limits the evolutionary search space for directed evolution, which alters circuit performance without the need for detailed biophysical information. This review examines strategies for integrating modeling and directed evolution and discusses the utility and limitations of available methods.

Accurate methods of computing the affinity of a small molecule with a protein are needed to speed the discovery of new medications and biological probes. This paper reviews physics-based models of binding, beginning with a summary of the changes in potential energy, solvation energy, and configurational entropy that influence affinity, and a theoretical overview to frame the discussion of specific computational approaches. Important advances are reported in modeling protein-ligand energetics, such as the incorporation of electronic polarization and the use of quantum mechanical methods. Recent calculations suggest that changes in configurational entropy strongly oppose binding and must be included if accurate affinities are to be obtained. The linear interaction energy (LIE) and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) methods are analyzed, as are free energy pathway methods, which show promise and may be ready for more extensive testing. Ultimately, major improvements in modeling accuracy will likely require advances on multiple fronts, as well as continued validation against experiment.

It is becoming increasingly clear that many macromolecules are intrinsically flexible and exist in multiple conformations in solution. Single-particle reconstruction of vitrified samples (cryo-electron microscopy, or cryo-EM) is uniquely positioned to visualize this conformational flexibility in its native state. Although heterogeneity remains a significant challenge in cryo-EM single-particle analysis, recent efforts in the field point to a future where it will be possible to tap into this rich source of biological information on a routine basis. In this article, we review the basic principles behind a few relatively new and generally applicable methods that show particular promise as tools to analyze macromolecular flexibility. We also discuss some of their recent applications to problems of biological interest.

Bilayer mixtures of lipids are used by many researchers as chemically simple models for biological membranes. In particular, observations on three-component bilayer mixtures containing cholesterol show rich phase behavior, including several regions of two-phase coexistence and one region of three-phase coexistence. Yet, the relationship between these simple model mixtures and biological membranes, which contain hundreds of different proteins and lipids, is not clear. Many of the model mixtures have been chosen for study because they exhibit readily observed phase separations, not because they are good mimics of cell membrane components. If the many components of cell membranes could be grouped in some way, then understanding the phase behaviors of biological membranes might be enhanced. Furthermore, if the underlying interaction energies between lipids and proteins can be determined, then it might be possible to model the distributions of lipids and proteins in a bilayer membrane, even in complex mixtures.

The physicochemical concepts that underlie our present ideas on the structure and assembly of the “macromolecular machines of gene expression” are developed, starting with the structure and folding of the individual protein and DNA components, the thermodynamics and kinetics of their conformational rearrangements during complex assembly, and the molecular basis of the sequence specificity and recognition interactions of the final assemblies that include the DNA genome. The role of diffusion in reduced dimensions in the kinetics of the assembly of macromolecular machines from their components is also considered, and diffusion-driven reactions are compared with those fueled by ATP binding and hydrolysis, as well as by the specific covalent chemical modifications involved in rearranging chromatin and modifying signal transduction networks in higher organisms.

The lipid bilayer component of biological membranes is important for the distribution, organization, and function of bilayer-spanning proteins. This regulation is due to both specific lipid-protein interactions and general bilayer-protein interactions, which modulate the energetics and kinetics of protein conformational transitions, as well as the protein distribution between different membrane compartments. The bilayer regulation of membrane protein function arises from the hydrophobic coupling between the protein's hydrophobic domains and the bilayer hydrophobic core, which causes protein conformational changes that involve the protein/bilayer boundary to perturb the adjacent bilayer. Such bilayer perturbations, or deformations, incur an energetic cost, which for a given conformational change varies as a function of the bilayer material properties (bilayer thickness, intrinsic lipid curvature, and the elastic compression and bending moduli). Protein function therefore is regulated by changes in bilayer material properties, which determine the free-energy changes caused by the protein-induced bilayer deformation. The lipid bilayer thus becomes an allosteric regulator of membrane function.

Covalent attachment of ubiquitin-like proteins (Ubls) is a predominant mechanism for regulating protein function in eukaryotes. Several structurally related Ubls, such as ubiquitin, SUMO, NEDD8, and ISG15, modify a vast number of proteins, altering their functions in a variety of ways. Ubl modifications can affect the target's half-life, subcellular localization, enzymatic activity, or ability to interact with protein or DNA partners. Generally, these diverse Ubls are covalently attached via their C termini to their targets by parallel, but specific, cascades involving three classes of enzymes known as E1, E2, and E3. Structures are now available for many protein complexes in E1-E2-E3 cascades, revealing a series of modular building blocks and providing mechanistic insights into their functions.

Fluorescence correlation spectroscopy (FCS) is one of the major biophysical techniques used for unraveling molecular interactions in vitro and in vivo. It allows minimally invasive study of dynamic processes in biological specimens with extremely high temporal and spatial resolution. By recording and correlating the fluorescence fluctuations of single labeled molecules through the exciting laser beam, FCS gives information on molecular mobility and photophysical and photochemical reactions. By using dual-color fluorescence cross-correlation, highly specific binding studies can be performed. These have been extended to four reaction partners accessible by multicolor applications. Alternative detection schemes shift accessible time frames to slower processes (e.g., scanning FCS) or higher concentrations (e.g., TIR–FCS). Despite its long tradition, FCS is by no means dated. Rather, it has proven to be a highly versatile technique that can easily be adapted to solve specific biological questions, and it continues to find exciting applications in biology and medicine.

Many biologically important macromolecules undergo motions that are essential to their function. Biophysical techniques can now resolve the motions of single molecules down to the nanometer scale or even below, providing new insights into the mechanisms that drive molecular movements. This review outlines the principal approaches that have been used for high-resolution measurements of single-molecule motion, including centroid tracking, fluorescence resonance energy transfer, magnetic tweezers, atomic force microscopy, and optical traps. For each technique, the principles of operation are outlined, the capabilities and typical applications are examined, and various practical issues for implementation are considered. Extensions to these methods are also discussed, with an eye toward future application to outstanding biological problems.

Controlling the differential expression of many thousands of genes is the most fundamental task of a developing organism. It requires an enormous computational device that has the capacity to process in parallel a vast number of regulatory inputs in the various cells of the embryo and come out with regulatory outputs that are tissue specific. The regulatory genome constitutes this computational device, comprising many thousands of processing units in the form of cis-regulatory modules. The interconnected cis-regulatory modules that control regulatory gene expression create a network that is the underlying mechanism of specification. In this review we use the gene regulatory network that governs endomesoderm specification in the sea urchin embryo to demonstrate the salient features of developmental gene regulatory networks and illustrate the information processing that is done by the regulatory sequences.

Microfluidic large-scale integration (mLSI) refers to the development of microfluidic chips with thousands of integrated micromechanical valves and control components. This technology is utilized in many areas of biology and chemistry and is a candidate to replace today's conventional automation paradigm, which consists of fluid-handling robots. We review the basic development of mLSI and then discuss design principles of mLSI to assess the capabilities and limitations of the current state of the art and to facilitate the application of mLSI to areas of biology. Many design and practical issues, including economies of scale, parallelization strategies, multiplexing, and multistep biochemical processing, are discussed. Several microfluidic components used as building blocks to create effective, complex, and highly integrated microfluidic networks are also highlighted.

Molecular interactions are the basic language of biological processes. They establish the forces interacting between the building blocks of proteins and other macromolecules, thus determining their functional roles. Because molecular interactions trigger virtually every biological process, approaches to decipher their language are needed. Single-molecule force spectroscopy (SMFS) has been used to detect and characterize different types of molecular interactions that occur between and within native membrane proteins. The first experiments detected and localized molecular interactions that stabilized membrane proteins, including how these interactions were established during folding of α-helical secondary structure elements into the native protein and how they changed with oligomerization, temperature, and mutations. SMFS also enables investigators to detect and locate molecular interactions established during ligand and inhibitor binding. These exciting applications provide opportunities for studying the molecular forces of life. Further developments will elucidate the origins of molecular interactions encoded in their lifetimes, interaction ranges, interplay, and dynamics characteristic of biological systems.

Globular proteins are a key component of the network of life. Over many decades much experimental data on proteins have been gathered, yet theoretical progress has been somewhat limited. We show that the results accumulated over the years inexorably lead to a unified framework for understanding proteins. The framework predicts the existence of a fixed menu of folds determined by geometry, clarifies the role of the amino acid sequence in selecting the native-state structure from this menu, and explains the propensity for amyloid formation. The experimental data and the new approach reveal an astonishing simplicity underlying the protein problem.

Chemically modified nucleic acids function as model systems for native DNA and RNA; as chemical probes in diagnostics or the analysis of protein–nucleic acid interactions and in high-throughput genomics and drug target validation; as potential antigene-, antisense-, or RNAi-based drugs; and as tools for structure determination (i.e., crystallographic phasing), just to name a few. Biophysical and structural investigations of chemically modified DNAs and RNAs, particularly of nucleic acid analogs with more significant alterations to the well-known base-sugar-phosphate framework (i.e., peptide or hexopyranose nucleic acids), can also provide insights into the properties of the natural nucleic acids that are beyond the reach of studies focusing on DNA or RNA alone. In this review we summarize results from crystallographic analyses of chemically modified DNAs and RNAs that are primarily of interest in the context of the discovery and development of oligonucleotide-based therapeutics. In addition, we re-examine recent structural data on nucleic acid analogs that are investigated as part of a systematic effort to rationalize nature's choice of pentose in the genetic system.

Small-angle X-ray scattering (SAXS) is increasingly used to characterize the structure and interactions of biological macromolecules and their complexes in solution. Although still a low-resolution technique, the advent of high-flux synchrotron sources and the development of algorithms for the reconstruction of 3-D electron density maps from 1-D scattering profiles have made possible the generation of useful low-resolution molecular models from SAXS data. Furthermore, SAXS is well suited for the study of unfolded or partially folded conformational ensembles as a function of time or solution conditions. Here, we review recently developed algorithms for 3-D structure modeling and applications to protein complexes. Furthermore, we discuss the emerging use of SAXS as a tool to study membrane protein-detergent complexes. SAXS is proving useful to study the folding of functional RNA molecules, and finally we discuss uses of SAXS to study ensembles of denatured proteins.

Various algorithms are available for predicting mRNA expression and modeling gene regulatory processes. They differ in whether they rely on the existence of modules of coregulated genes or build a model that applies to all genes, whether they represent regulatory activities as hidden variables or as mRNA levels, and whether they implicitly or explicitly model the complex cis-regulatory logic of multiple interacting transcription factors binding the same DNA. The fact that functional genomics data of different types reflect the same molecular processes provides a natural strategy for integrative computational analysis. One promising avenue toward an accurate and comprehensive model of gene regulation combines biophysical modeling of the interactions among proteins, DNA, and RNA with the use of large-scale functional genomics data to estimate regulatory network connectivity and activity parameters. As the ability of these models to represent complex cis-regulatory logic increases, the need for approaches based on cross-species conservation may diminish.

Single-molecule biophysics has been serving biology for more than two decades. Fluorescence microscopy is one of the most commonly used tools to identify molecules of interest and to visualize biological events. Here we describe some of the most commonly used fluorescence imaging tools to measure nanoscale movements and the rotational dynamics of biomolecules.

Recent progress in proteomics suggests that the cell can be conceived as a large network of highly refined, nanomachine-like protein complexes. This working hypothesis calls for new methods capable of analyzing individual protein complexes in living cells and tissues at high speed. Here, we examine whether single-molecule fluorescence (SMF) analysis can satisfy that demand. First, recent technical progress in the visualization, localization, tracking, conformational analysis, and true resolution of individual protein complexes is highlighted. Second, results obtained by the SMF analysis of protein complexes are reviewed, focusing on the nuclear pore complex as an instructive example. We conclude that SMF methods provide powerful, indispensable tools for the structural and functional characterization of protein complexes. However, the transition from in vitro systems to living cells is in the initial stages. We discuss how current limitations in the nanoscopic analysis of living cells and tissues can be overcome to create a new paradigm, nanoscopic biomedicine.

Recent experimental developments are changing the ways we interpret experimental data in protein folding, leading to a closer connection with theory and an improved understanding of some long-standing questions in the field. We now have a basic roadmap of the types of polypeptide motions and timescales that are relevant to the various folding stages. The folding barriers estimated with a variety of independent methods are consistently small, indicating that several fast-folding proteins are near or within the downhill folding regime. Finally, the structural and statistical analysis of global downhill folding is promising to open a new avenue of research in which folding mechanisms and the networks of noncovalent interactions that stabilize native structures are directly resolved in equilibrium experiments of nonmutated proteins.

Within a population of genetically identical cells there can be significant variation, or noise, in gene expression. Yet even with this inherent variability, cells function reliably. This review focuses on our understanding of noise at the level of both single genes and genetic regulatory networks, emphasizing comparisons between theoretical models and experimental results whenever possible. To highlight the importance of noise, we particularly emphasize examples in which a stochastic description of gene expression leads to a qualitatively different outcome than a deterministic one.