Annual review of biophysics and biomolecular structure最新文献

The transport of electrically charged macromolecules such as DNA through narrow pores is a fundamental process in life. When polymer molecules are forced to navigate through pores, their transport is controlled by entropic barriers that accompany their conformational changes. During the past decade, exciting results have emerged from single-molecule electrophysiology experiments. Specifically, the passage of single-stranded DNA/RNA through alpha-hemolysin pores and double-stranded DNA through solid-state nanopores has been investigated. By a combination of these results with the entropic barrier theory of polymer transport and macromolecular simulations, an understanding of the mechanism of DNA transport through pores has emerged.

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.

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.

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.

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.

This review summarizes what is known about the biochemical and biophysical mechanisms that initiate the assembly of actin filaments in cells. Assembly and disassembly of these filaments contribute to many types of cellular movements. Numerous proteins regulate actin assembly, but Arp2/3 complex and formins are the focus of this review because more is known about them than other proteins that stimulate the formation of new filaments. Arp2/3 complex is active at the leading edge of motile cells, where it produces branches on the sides of existing filaments. Growth of these filaments produces force to protrude the membrane. Crystal structures, reconstructions from electron micrographs, and biophysical experiments have started to map out the steps through which proteins called nucleation-promoting factors stimulate the formation of branches. Formins nucleate and support the elongation of unbranched actin filaments for cytokinesis and various types of actin filament bundles. Formins associate processively with the fast-growing ends of filaments and protect them from capping.

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.

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 alpha-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.

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.

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.