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Allostery is a phenomenon that couples effector ligand binding at an allosteric site to a structural and/or dynamic change at a distant regulated site. To study an allosteric transition, we vary the size of the allosteric site and its interactions to construct a series of energy landscapes with pronounced minima corresponding to both the effector bound and unbound crystal structures. We use molecular dynamics to sample these landscapes. The degree of perturbation by the effector, modeled by the size of the allosteric site, provides an order parameter for allostery that allows us to determine how microscopic motions give rise to commonly discussed macroscopic mechanisms: (i) induced fit, (ii) population shift, and (iii) entropy driven. These mechanisms involve decreasing structural differences between the effector bound and unbound populations. A metric (ligand-induced cooperativity) can measure how cooperatively a given regulated site responds to effector binding and therefore what kind of allosteric mechanism is involved. We apply the model to three proteins with experimentally characterized transitions: (i) calmodulin-GFP Ca2+ sensor protein, (ii) maltose binding protein, and (iii) CSL transcription factor. Remarkably, the model is able to reproduce allosteric motion and predict coupling in a manner consistent with experiment.

Integrative approaches using data from a wide variety of methods are yielding model structures of complex biological assemblies. Biological assemblies and machines often elude structural characterization, hampering our understanding of how they function, how they evolved, and how they can be modulated. A number of macromolecular assemblies have been reconstructed over the years by piecemeal efforts, such as fitting high-resolution crystal structures of individual components into lower-resolution electron microscopy (EM) reconstructions of the entire complex ( 1 ). Although notable successes have been achieved in this way, ambiguous or conflicting models can still arise ( 2 – 4 ). Thus, structural and computational biologists have been looking for new ways to put all of the pieces back together. Sophisticated integrative approaches are being developed ( 5 , 6 ) that combine information from different types of experiments, physical theories, and statistical analyses to compute structural models of multicomponent assemblies and complex biological systems.

A set of software tools for building and distributing models of macromolecular assemblies uses an integrative structure modeling approach, which casts the building of models as a computational optimization problem where information is encoded into a scoring function used to evaluate candidate models.

Nuclear pore complexes play central roles as gatekeepers of RNA and protein transport between the cytoplasm and nucleoplasm. However, their large size and dynamic nature have impeded a full structural and functional elucidation. Here we determined the structure of the entire 552-protein nuclear pore complex of the yeast Saccharomyces cerevisiae at sub-nanometre precision by satisfying a wide range of data relating to the molecular arrangement of its constituents. The nuclear pore complex incorporates sturdy diagonal columns and connector cables attached to these columns, imbuing the structure with strength and flexibility. These cables also tie together all other elements of the nuclear pore complex, including membrane-interacting regions, outer rings and RNA-processing platforms. Inwardly directed anchors create a high density of transport factor-docking Phe-Gly repeats in the central channel, organized into distinct functional units. This integrative structure enables us to rationalize the architecture, transport mechanism and evolutionary origins of the nuclear pore complex. The structure of the yeast nuclear pore complex, determined at sub-nanometre precision using an integrative approach that combines a wide range of data, reveals details of its architecture, transport mechanism and evolutionary origins. Structure of yeast nuclear pore complex Nuclear pore complexes (NPCs) are the gateways for the transport of RNA and proteins into and out of the nucleus. Although previous work has provided structural insights into parts of NPCs, getting a full picture of these complexes has proved difficult owing to their large size and dynamic nature. A multidisciplinary team of researchers now report the structure of the entire 552-protein NPC of the yeast at a sub-nanometre level using an integrative approach including mass spectrometry, cryo-electron tomography and chemical crosslinking. The structure provides a detailed view of the functional elements of the NPC and clarifies its architecture, mechanism of action and evolutionary origins.

Understanding how the nuclear pore complex (NPC) is assembled is of fundamental importance to grasp the mechanisms behind its essential function and understand its role during the evolution of eukaryotes 1 – 4 . There are at least two NPC assembly pathways—one during the exit from mitosis and one during nuclear growth in interphase—but we currently lack a quantitative map of these events. Here we use fluorescence correlation spectroscopy calibrated live imaging of endogenously fluorescently tagged nucleoporins to map the changes in the composition and stoichiometry of seven major modules of the human NPC during its assembly in single dividing cells. This systematic quantitative map reveals that the two assembly pathways have distinct molecular mechanisms, in which the order of addition of two large structural components, the central ring complex and nuclear filaments are inverted. The dynamic stoichiometry data was integrated to create a spatiotemporal model of the NPC assembly pathway and predict the structures of postmitotic NPC assembly intermediates. Single-molecule calibrated live microscopy and computational modelling have revealed that human nuclear pore complex assembly takes different pathways during the exit from mitosis and during nuclear growth in interphase.

Bacterial secondary metabolites are widely used as antibiotics, anticancer drugs, insecticides and food additives. Attempts to engineer their biosynthetic gene clusters (BGCs) to produce unnatural metabolites with improved properties are often frustrated by the unpredictability and complexity of the enzymes that synthesize these molecules, suggesting that genetic changes within BGCs are limited by specific constraints. Here, by performing a systematic computational analysis of BGC evolution, we derive evidence for three findings that shed light on the ways in which, despite these constraints, nature successfully invents new molecules: 1) BGCs for complex molecules often evolve through the successive merger of smaller sub-clusters, which function as independent evolutionary entities. 2) An important subset of polyketide synthases and nonribosomal peptide synthetases evolve by concerted evolution, which generates sets of sequence-homogenized domains that may hold promise for engineering efforts since they exhibit a high degree of functional interoperability, 3) Individual BGC families evolve in distinct ways, suggesting that design strategies should take into account family-specific functional constraints. These findings suggest novel strategies for using synthetic biology to rationally engineer biosynthetic pathways.

Genome sequencing projects are producing linear amino acid sequences, but full understanding of the biological role of these proteins will require knowledge of their structure and function. Although experimental structure determination methods are providing high-resolution structure information about a subset of the proteins, computational structure prediction methods will provide valuable information for the large fraction of sequences whose structures will not be determined experimentally. The first class of protein structure prediction methods, including threading and comparative modeling, rely on detectable similarity spanning most of the modeled sequence and at least one known structure. The second class of methods, de novo or ab initio methods, predict the structure from sequence alone, without relying on similarity at the fold level between the modeled sequence and any of the known structures. In this Viewpoint, we begin by describing the essential features of the methods, the accuracy of the models, and their application to the prediction and understanding of protein function, both for single proteins and on the scale of whole genomes. We then discuss the important role that protein structure prediction methods play in the growing worldwide effort in structural genomics.

The 20S proteasome (20S) facilitates turnover of most eukaryotic proteins. Substrate entry into the 20S first requires opening of gating loops through binding of HbYX motifs that are present at the C-termini of certain proteasome activators (PAs). The HbYX motif has been predominantly characterized in the archaeal 20S, whereas little is known about the sequence preferences of the human 20S ( h 20S). Here, we synthesize and screen ~120 HbYX-like peptides, revealing unexpected differences from the archaeal system and defining the h 20S recognition sequence as the Y-F/Y (YФ) motif. To gain further insight, we create a functional chimera of the optimized sequence, NLSYYT, fused to the model activator, PA26 E102A . A cryo-EM structure of PA26 E102A - h 20S is used to identify key interactions, including non-canonical contacts and gate-opening mechanisms. Finally, we demonstrate that the YФ sequence preferences are tuned by valency, allowing multivalent PAs to sample greater sequence space. These results expand the model for termini-mediated gating and provide a template for the design of h 20S activators. The proteasome complexes, composed of 20S core particles and one or two regulatory particles (proteasome activators), degrade most eukaryotic proteins. Here, the authors identify a sequence motif and resolve its interactions mediating the activation of the human 20S proteasome.

The 26S proteasome is at the executive end of the ubiquitin-proteasome pathway for the controlled degradation of intracellular proteins. While the structure of its 20S core particle (CP) has been determined by X-ray crystallography, the structure of the 19S regulatory particle (RP), which recruits substrates, unfolds them, and translocates them to the CP for degradation, has remained elusive. Here, we describe the molecular architecture of the 26S holocomplex determined by an integrative approach based on data from cryoelectron microscopy, X-ray crystallography, residue-specific chemical cross-linking, and several proteomics techniques. The \"lid\" of the RP (consisting of Rpn3/5/6/7/8/9/11/12) is organized in a modular fashion. Rpn3/5/6/7/9/12 form a horseshoe-shaped heterohexamer, which connects to the CP and roofs the AAA-ATPase module, positioning the Rpn8/Rpn11 heterodimer close to its mouth. Rpn2 is rigid, supporting the lid, while Rpn1 is conformationally variable, positioned at the periphery of the ATPase ring. The ubiquitin receptors Rpn10 and Rpn13 are located in the distal part of the RP, indicating that they were recruited to the complex late in its evolution. The modular structure of the 26S proteasome provides insights into the sequence of events prior to the degradation of ubiquitylated substrates.

The HIV-1 Nef protein suppresses multiple immune surveillance mechanisms to promote viral pathogenesis and is an attractive target for the development of novel therapeutics. A key function of Nef is to remove the CD4 receptor from the cell surface by hijacking clathrin- and adaptor protein complex 2 (AP2)-dependent endocytosis. However, exactly how Nef does this has been elusive. Here, we describe the underlying mechanism as revealed by a 3.0-Å crystal structure of a fusion protein comprising Nef and the cytoplasmic domain of CD4 bound to the tetrameric AP2 complex. An intricate combination of conformational changes occurs in both Nef and AP2 to enable CD4 binding and downregulation. A pocket on Nef previously identified as crucial for recruiting class I MHC is also responsible for recruiting CD4, revealing a potential approach to inhibit two of Nef’s activities and sensitize the virus to immune clearance.Crystallography and mutagenesis analyses examine how HIV-1 Nef interacts with AP2 to enable CD4 binding and downregulation and reveal the role of a Nef pocket that is also involved in downregulation of class I MHC.