A core-weighted fitting method for docking atomic structures into low-resolution maps: application to cryo-electron microscopy

Likelihood-based signal and noise analysis for docking of models into cryo-EM maps

Fast, reliable docking of models into cryo-EM maps requires understanding of the errors in the maps and the models. Likelihood-based approaches to errors have proven to be powerful and adaptable in experimental structural biology, finding applications in both crystallography and cryo-EM. Indeed, previous crystallographic work on the errors in structural models is directly applicable to likelihood targets in cryo-EM. Likelihood targets in Fourier space are derived here to characterize, based on the comparison of half-maps, the direction- and resolution-dependent variation in the strength of both signal and noise in the data. Because the signal depends on local features, the signal and noise are analysed in local regions of the cryo-EM reconstruction. The likelihood analysis extends to prediction of the signal that will be achieved in any docking calculation for a model of specified quality and completeness. A related calculation generalizes a previous measure of the information gained by making the cryo-EM reconstruction.

Design and Development of Novel Glitazones for Activation of PGC-1α Signaling Via PPAR-γ Agonism: A Promising Therapeutic Approach against Parkinson's Disease

Herein, we rationally designed and developed two novel glitazones (G1 and G2) to target peroxisome proliferator-activated receptor-gamma coactivator 1-alpha (PGC-1α) signaling through peroxisome proliferator-activated receptors (PPAR)-γ agonism as a therapeutic for Parkinson's disease (PD). The synthesized molecules were analyzed by mass spectrometry and NMR spectroscopy. The neuroprotective functionality of the synthesized molecules was assessed by a cell viability assay in lipopolysaccharide-intoxicated SHSY5Y neuroblastoma cell lines. The ability of these new glitazones to scavenge free radicals was further ascertained via a lipid peroxide assay, and pharmacokinetic properties were verified using in silico absorption, distribution, metabolism, excretion, and toxicity analyses. The molecular docking reports recognized the mode of interaction of the glitazones with PPAR-γ. The G1 and G2 exhibited a noticeable neuroprotective effect in lipopolysaccharide-intoxicated SHSY5Y neuroblastoma cells with the half-maximal inhibitory concentration value of 2.247 and 4.509 μM, respectively. Both test compounds prevented 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine-induced motor impairment in mice, as demonstrated by the beam walk test. Further, treating the diseased mice with G1 and G2 resulted in significant restoration of antioxidant enzymes glutathione and superoxide and reduced the intensity of lipid peroxidation inside the brain tissues. Histopathological analysis of the glitazones-treated mice brain revealed a reduced apoptotic region and a rise in the number of viable pyramidal neurons and oligodendrocytes. The study concluded that G1 and G2 showed promising results in treating PD by activating PGC-1α signaling in brain via PPAR-γ agonism. However, more extensive research is necessary for a better understanding of functional targets and signaling pathways.

MarkovFit: Structure Fitting for Protein Complexes in Electron Microscopy Maps Using Markov Random Field

An increasing number of protein complex structures are determined by cryo-electron microscopy (cryo-EM). When individual protein structures have been determined and are available, an important task in structure modeling is to fit the individual structures into the density map. Here, we designed a method that fits the atomic structures of proteins in cryo-EM maps of medium to low resolutions using Markov random fields, which allows probabilistic evaluation of fitted models. The accuracy of our method, MarkovFit, performed better than existing methods on datasets of 31 simulated cryo-EM maps of resolution 10 Å , nine experimentally determined cryo-EM maps of resolution less than 4 Å , and 28 experimentally determined cryo-EM maps of resolution 6 to 20 Å .

Simulation and Machine Learning Methods for Ion-Channel Structure Determination, Mechanistic Studies and Drug Design

Ion channels are expressed in almost all living cells, controlling the in-and-out communications, making them ideal drug targets, especially for central nervous system diseases. However, owing to their dynamic nature and the presence of a membrane environment, ion channels remain difficult targets for the past decades. Recent advancement in cryo-electron microscopy and computational methods has shed light on this issue. An explosion in high-resolution ion channel structures paved way for structure-based rational drug design and the state-of-the-art simulation and machine learning techniques dramatically improved the efficiency and effectiveness of computer-aided drug design. Here we present an overview of how simulation and machine learning-based methods fundamentally changed the ion channel-related drug design at different levels, as well as the emerging trends in the field.

Hybrid methods for combined experimental and computational determination of protein structure

Knowledge of protein structure is paramount to the understanding of biological function, developing new therapeutics, and making detailed mechanistic hypotheses. Therefore, methods to accurately elucidate three-dimensional structures of proteins are in high demand. While there are a few experimental techniques that can routinely provide high-resolution structures, such as x-ray crystallography, nuclear magnetic resonance (NMR), and cryo-EM, which have been developed to determine the structures of proteins, these techniques each have shortcomings and thus cannot be used in all cases. However, additionally, a large number of experimental techniques that provide some structural information, but not enough to assign atomic positions with high certainty have been developed. These methods offer sparse experimental data, which can also be noisy and inaccurate in some instances. In cases where it is not possible to determine the structure of a protein experimentally, computational structure prediction methods can be used as an alternative. Although computational methods can be performed without any experimental data in a large number of studies, inclusion of sparse experimental data into these prediction methods has yielded significant improvement. In this Perspective, we cover many of the successes of integrative modeling, computational modeling with experimental data, specifically for protein folding, protein-protein docking, and molecular dynamics simulations. We describe methods that incorporate sparse data from cryo-EM, NMR, mass spectrometry, electron paramagnetic resonance, small-angle x-ray scattering, Förster resonance energy transfer, and genetic sequence covariation. Finally, we highlight some of the major challenges in the field as well as possible future directions.

Simulation-Based Methods for Model Building and Refinement in Cryoelectron Microscopy

Advances in cryoelectron microscopy (cryo-EM) have revolutionized the structural investigation of large macromolecular assemblies. In this review, we first provide a broad overview of modeling methods used for flexible fitting of molecular models into cryo-EM density maps. We give special attention to approaches rooted in molecular simulations-atomistic molecular dynamics and Monte Carlo. Concise descriptions of the methods are given along with discussion of their advantages, limitations, and most popular alternatives. We also describe recent extensions of the widely used molecular dynamics flexible fitting (MDFF) method and discuss how different model-building techniques could be incorporated into new hybrid modeling schemes and simulation workflows. Finally, we provide two illustrative examples of model-building and refinement strategies employing MDFF, cascade MDFF, and RosettaCM. These examples come from recent cryo-EM studies that elucidated transcription preinitiation complexes and shed light on the functional roles of these assemblies in gene expression and gene regulation.

Advances in Structure Modeling Methods for Cryo-Electron Microscopy Maps

Cryo-electron microscopy (cryo-EM) has now become a widely used technique for structure determination of macromolecular complexes. For modeling molecular structures from density maps of different resolutions, many algorithms have been developed. These algorithms can be categorized into rigid fitting, flexible fitting, and de novo modeling methods. It is also observed that machine learning (ML) techniques have been increasingly applied following the rapid progress of the ML field. Here, we review these different categories of macromolecule structure modeling methods and discuss their advances over time.

Enhanced Sampling of Interdomain Motion Using Map-Restrained Langevin Dynamics and NMR: Application to Pin1

Many signaling proteins consist of globular domains connected by flexible linkers that allow for substantial domain motion. Because these domains often serve as complementary functional modules, the possibility of functionally important domain motions arises. To explore this possibility, we require knowledge of the ensemble of protein conformations sampled by interdomain motion. Measurements of NMR residual dipolar couplings (RDCs) of backbone HN bonds offer a per-residue characterization of interdomain dynamics, as the couplings are sensitive to domain orientation. A challenge in reaching this potential is the need to interpret the RDCs as averages over dynamic ensembles of domain conformations. Here, we address this challenge by introducing an efficient protocol for generating conformational ensembles appropriate for flexible, multi-domain proteins. The protocol uses map-restrained self-guided Langevin dynamics simulations to promote collective, interdomain motion while restraining the internal domain motion to near rigidity. Critically, the simulations retain an all-atom description for facile inclusion of site-specific NMR RDC restraints. The result is the rapid generation of conformational ensembles consistent with the RDC data. We illustrate this protocol on human Pin1, a two-domain peptidyl-prolyl isomerase relevant for cancer and Alzheimer's disease. The results include the ensemble of domain orientations sampled by Pin1, as well as those of a dysfunctional variant, I28A-Pin1. The differences between the ensembles corroborate our previous spin relaxation results that showed weakened interdomain contact in the I28A variant relative to wild type. Our protocol extends our abilities to explore the functional significance of protein domain motions.

Tools for the cryo-EM gold rush: going from the cryo-EM map to the atomistic model

As cryo-electron microscopy (cryo-EM) enters mainstream structural biology, the demand for fitting methods is high. Here, we review existing flexible fitting methods for cryo-EM. We discuss their importance, potential concerns and assessment strategies. We aim to give readers concrete descriptions of cryo-EM flexible fitting methods with corresponding examples.

A novel fast Fourier transform accelerated off-grid exhaustive search method for cryo-electron microscopy fitting

This paper presents a novel fast Fourier transform (FFT)-based exhaustive search method extended to off-grid translational and rotational degrees of freedom. The method combines the advantages of the FFT-based exhaustive search, which samples all the conformations of a system under study on a grid, with a local optimization technique that guarantees to find the nearest optimal off-grid conformation. The method is demonstrated on a fitting problem and can be readily applied to a docking problem. The algorithm first samples a scoring function on a six-dimensional grid of sizeN6using the FFT. This operation has an asymptotic complexity ofO(N6logN). Then, the method performs the off-grid search using a local quadratic approximation of the cost function and the trust-region optimization algorithm. The computation of the quadratic approximation is also accelerated by FFT at the same additional asymptotic cost ofO(N6logN). The method is demonstrated by fitting atomic protein models into several simulated and experimental maps from cryo-electron microscopy. The method is available at https://team.inria.fr/nano-d/software/offgridfit.

The DisVis and PowerFit Web Servers: Explorative and Integrative Modeling of Biomolecular Complexes

Structure determination of complex molecular machines requires a combination of an increasing number of experimental methods with highly specialized software geared toward each data source to properly handle the gathered data. Recently, we introduced the two software packages PowerFit and DisVis. These combine high-resolution structures of atomic subunits with density maps from cryo-electron microscopy or distance restraints, typically acquired by chemical cross-linking coupled with mass spectrometry, respectively. Here, we report on recent advances in both GPGPU-accelerated software packages: PowerFit is a tool for rigid body fitting of atomic structures in cryo-electron density maps and has been updated to also output reliability indicators for the success of fitting, through the use of the Fisher z-transformation and associated confidence intervals; DisVis aims at quantifying the information content of distance restraints and identifying false-positive restraints. We extended its analysis capabilities to include an analysis of putative interface residues and to output an average shape representing the putative location of the ligand. To facilitate their use by a broad community, they have been implemented as web portals harvesting both local CPU resources and GPGPU-accelerated EGI grid resources. They offer user-friendly interfaces, while minimizing computational requirements, and provide a first interactive view of the results. The portals can be accessed freely after registration via http://milou.science.uu.nl/services/DISVIS and http://milou.science.uu.nl/services/POWERFIT.

Allosteric communication between DNA-binding and light-responsive domains of diatom class I aureochromes

The modular architecture of aureochrome blue light receptors, found in several algal groups including diatoms, is unique by having the LOV-type photoreceptor domain fused to the C-terminus of its putative effector, an N-terminal DNA-binding bZIP module. The structural and functional understanding of aureochromes’ light-dependent signaling mechanism is limited, despite their promise as an optogenetic tool. We show that class I aureochromes 1a and 1c from the diatom Phaeodactylum tricornutum are regulated in a light-independent circadian rhythm. These aureochromes are capable to form functional homo- and heterodimers, which recognize the ACGT core sequence within the canonical ‘aureo box’, TGACGT, in a light-independent manner. The bZIP domain holds a more folded and less flexible but extended conformation in the duplex DNA-bound state. FT-IR spectroscopy in the absence and the presence of DNA shows light-dependent helix unfolding in the LOV domain, which leads to conformational changes in the bZIP region. The solution structure of DNA bound to aureochrome points to a tilted orientation that was further validated by molecular dynamics simulations. We propose that aureochrome signaling relies on an allosteric pathway from LOV to bZIP that results in conformational changes near the bZIP-DNA interface without major effects on the binding affinity.

Electron Microscopy and Image Processing: Essential Tools for Structural Analysis of Macromolecules

Macromolecular electron microscopy typically depicts the structures of macromolecular complexes ranging from ∼200 kDa to hundreds of MDa. The amount of specimen required, a few micrograms, is typically 100 to 1000 times less than needed for X-ray crystallography or nuclear magnetic resonance spectroscopy. Micrographs of frozen-hydrated (cryogenic) specimens portray native structures, but the original images are noisy. Computational averaging reduces noise, and three-dimensional reconstructions are calculated by combining different views of free-standing particles ("single-particle analysis"). Electron crystallography is used to characterize two-dimensional arrays of membrane proteins and very small three-dimensional crystals. Under favorable circumstances, near-atomic resolutions are achieved. For structures at somewhat lower resolution, pseudo-atomic models are obtained by fitting high-resolution components into the density. Time-resolved experiments describe dynamic processes. Electron tomography allows reconstruction of pleiomorphic complexes and subcellular structures and modeling of macromolecules in their cellular context. Significant information is also obtained from metal-coated and dehydrated specimens.

PF2fit: Polar Fast Fourier Matched Alignment of Atomistic Structures with 3D Electron Microscopy Maps

There continue to be increasing occurrences of both atomistic structure models in the PDB (possibly reconstructed from X-ray diffraction or NMR data), and 3D reconstructed cryo-electron microscopy (3D EM) maps (albeit at coarser resolution) of the same or homologous molecule or molecular assembly, deposited in the EMDB. To obtain the best possible structural model of the molecule at the best achievable resolution, and without any missing gaps, one typically aligns (match and fits) the atomistic structure model with the 3D EM map. We discuss a new algorithm and generalized framework, named PF(2) fit (Polar Fast Fourier Fitting) for the best possible structural alignment of atomistic structures with 3D EM. While PF(2) fit enables only a rigid, six dimensional (6D) alignment method, it augments prior work on 6D X-ray structure and 3D EM alignment in multiple ways: Scoring. PF(2) fit includes a new scoring scheme that, in addition to rewarding overlaps between the volumes occupied by the atomistic structure and 3D EM map, rewards overlaps between the volumes complementary to them. We quantitatively demonstrate how this new complementary scoring scheme improves upon existing approaches. PF(2) fit also includes two scoring functions, the non-uniform exterior penalty and the skeleton-secondary structure score, and implements the scattering potential score as an alternative to traditional Gaussian blurring. Search. PF(2) fit utilizes a fast polar Fourier search scheme, whose main advantage is the ability to search over uniformly and adaptively sampled subsets of the space of rigid-body motions. PF(2) fit also implements a new reranking search and scoring methodology that considerably improves alignment metrics in results obtained from the initial search.

Integrative Modeling of Macromolecular Assemblies from Low to Near-Atomic Resolution

While conventional high-resolution techniques in structural biology are challenged by the size and flexibility of many biological assemblies, recent advances in low-resolution techniques such as cryo-electron microscopy (cryo-EM) and small angle X-ray scattering (SAXS) have opened up new avenues to define the structures of such assemblies. By systematically combining various sources of structural, biochemical and biophysical information, integrative modeling approaches aim to provide a unified structural description of such assemblies, starting from high-resolution structures of the individual components and integrating all available information from low-resolution experimental methods. In this review, we describe integrative modeling approaches, which use complementary data from either cryo-EM or SAXS. Specifically, we focus on the popular molecular dynamics flexible fitting (MDFF) method, which has been widely used for flexible fitting into cryo-EM maps. Second, we describe hybrid molecular dynamics, Rosetta Monte-Carlo and minimum ensemble search (MES) methods that can be used to incorporate SAXS into pseudoatomic structural models. We present concise descriptions of the two methods and their most popular alternatives, along with select illustrative applications to protein/nucleic acid assemblies involved in DNA replication and repair.

Structural and Physical Basis for Anti-IgE Therapy

Omalizumab, an anti-IgE antibody, used to treat severe allergic asthma and chronic idiopathic urticaria, binds to IgE in blood or membrane-bound on B lymphocytes but not to IgE bound to its high (FcεRI) or low (CD23) affinity receptor. Mutagenesis studies indicate overlapping FcεRI and omalizumab-binding sites in the Cε3 domain, but crystallographic studies show FcεRI and CD23-binding sites that are far apart, so how can omalizumab block IgE from binding both receptors? We report a 2.42-Å omalizumab-Fab structure, a docked IgE-Fc/omalizumab-Fab structure consistent with available experimental data, and the free energy contributions of IgE residues to binding omalizumab, CD23, and FcεRI. These results provide a structural and physical basis as to why omalizumab cannot bind receptor-bound IgE and why omalizumab-bound IgE cannot bind to CD23/FcεRI. They reveal the key IgE residues and their roles in binding omalizumab, CD23, and FcεRI.

Maturation of the HIV-1 core by a non-diffusional phase transition

The formation of the HIV-1 core is the final step in the viral maturation pathway, resulting in the formation of infectious virus. Most current models for HIV-1 core formation suggest that, upon proteolytic cleavage from the immature Gag, capsid (CA) dissociates into the viral interior before reforming into the core. Here we present evidence for an alternate view of core formation by taking advantage of our serendipitous observation of large membrane-enclosed structures in HIV-1 supernatants from infected cells. Cryo-electron tomographic studies show that these structures, which contain ordered arrays of what is likely the membrane-associated matrix protein, contain multiple cores that can be captured at different stages of maturation. Our studies suggest that HIV maturation involves a non-diffusional phase transition in which the detaching layer of the cleaved CA lattice is gradually converted into a roll that ultimately forms the surface of the mature conical core.

Long range Debye-Hückel correction for computation of grid-based electrostatic forces between biomacromolecules

Background

Brownian dynamics (BD) simulations can be used to study very large molecular systems, such as models of the intracellular environment, using atomic-detail structures. Such simulations require strategies to contain the computational costs, especially for the computation of interaction forces and energies. A common approach is to compute interaction forces between macromolecules by precomputing their interaction potentials on three-dimensional discretized grids. For long-range interactions, such as electrostatics, grid-based methods are subject to finite size errors. We describe here the implementation of a Debye-Hückel correction to the grid-based electrostatic potential used in the SDA BD simulation software that was applied to simulate solutions of bovine serum albumin and of hen egg white lysozyme.

Results

We found that the inclusion of the long-range electrostatic correction increased the accuracy of both the protein-protein interaction profiles and the protein diffusion coefficients at low ionic strength.

Conclusions

An advantage of this method is the low additional computational cost required to treat long-range electrostatic interactions in large biomacromolecular systems. Moreover, the implementation described here for BD simulations of protein solutions can also be applied in implicit solvent molecular dynamics simulations that make use of gridded interaction potentials.

Protein-Protein Docking Using EMAP in CHARMM and Support Vector Machine: Application to Ab/Ag Complexes

In this work, we have (i) evaluated the ability of the EMAP method implemented in the CHARMM program to generate the correct conformation of Ab/Ag complex structures and (ii) developed a support vector machine (SVM) classifier to detect native conformations among the thousands of refined Ab/Ag configurations using the individual components of the binding free energy based on a thermodynamic cycle as input features in training the SVM. Tests on 24 Ab/Ag complexes from the protein-protein docking benchmark version 3.0 showed that based on CAPRI evaluation criteria, EMAP could generate medium-quality native conformations in each case. Furthermore, the SVM classifier could rank medium/high-quality native conformations mostly in the top six among the thousands of refined Ab/Ag configurations. Thus, Ab-Ag docking can be performed using different levels of protein representations, from grid-based (EMAP) to polar hydrogen (united-atom) to all-atom representation within the same program. The scripts used and the trained SVM are available at the www.charmm.org forum script repository.

Targeted conformational search with map-restrained self-guided Langevin dynamics: application to flexible fitting into electron microscopic density maps

We present a map-restrained self-guided Langevin dynamics (MapSGLD) simulation method for efficient targeted conformational search. The targeted conformational search represents simulations under restraints defined by experimental observations and/or by user specified structural requirements. Through map-restraints, this method provides an efficient way to maintain substructures and to set structure targets during conformational searching. With an enhanced conformational searching ability of self-guided Langevin dynamics, this approach is suitable for simulating large-scale conformational changes, such as the formation of macromolecular assemblies and transitions between different conformational states. Using several examples, we illustrate the application of this method in flexible fitting of atomic structures into density maps derived from cryo-electron microscopy.

Conformational shift of a major poliovirus antigen confirmed by immuno-cryogenic electron microscopy

Small, interfacial conformational changes occur in some Ag-Ab interactions. Using cryogenic electron microscopy (cryo-EM), we have demonstrated such changes in a major antigenic site of a poliovirus capsid protein. During cell entry, native human poliovirus (160S particle) converts to a cell entry intermediate (135S particle) and later to an RNA-released (80S) particle. By mixing particles with Fabs of the neutralizing C3 mAb, we labeled the external loop connecting the B and C β-strands (BC loop) of the capsid protein VP1 (residues 95-105) in the 160S and 135S states. We then determined three-dimensional structures by cryo-EM and enhanced their interpretability by fitting high-resolution coordinates of C3 Fab and the capsid proteins into the density maps. Binding of C3 to either 160S or 135S particles caused residues of the BC loop, located on the tip of a prominent peak known as the "mesa," to move by an estimated 5 Å. C3 Abs are neutralizing and can bind bivalently. The orientation of the bound Fabs in our reconstructions suggests that C3 neutralizes poliovirus by binding two adjacent BC loops on the same mesa and inhibiting conformational changes in the viral capsid.

Computational methods for constructing protein structure models from 3D electron microscopy maps

Protein structure determination by cryo-electron microscopy (EM) has made significant progress in the past decades. Resolutions of EM maps have been improving as evidenced by recently reported structures that are solved at high resolutions close to 3Å. Computational methods play a key role in interpreting EM data. Among many computational procedures applied to an EM map to obtain protein structure information, in this article we focus on reviewing computational methods that model protein three-dimensional (3D) structures from a 3D EM density map that is constructed from two-dimensional (2D) maps. The computational methods we discuss range from de novo methods, which identify structural elements in an EM map, to structure fitting methods, where known high resolution structures are fit into a low-resolution EM map. A list of available computational tools is also provided.

Weak intra-ring allosteric communications of the archaeal chaperonin thermosome revealed by normal mode analysis

Chaperonins are molecular machines that use ATP-driven cycles to assist misfolded substrate proteins to reach the native state. During the functional cycle, these machines adopt distinct nucleotide-dependent conformational states, which reflect large-scale allosteric changes in individual subunits. Distinct allosteric kinetics has been described for the two chaperonin classes. Bacterial (group I) chaperonins, such as GroEL, undergo concerted subunit motions within each ring, whereas archaeal and eukaryotic chaperonins (group II) undergo sequential subunit motions. We study these distinct mechanisms through a comparative normal mode analysis of monomer and double-ring structures of the archaeal chaperonin thermosome and GroEL. We find that thermosome monomers of each type exhibit common low-frequency behavior of normal modes. The observed distinct higher-frequency modes are attributed to functional specialization of these subunit types. The thermosome double-ring structure has larger contribution from higher-frequency modes, as it is found in the GroEL case. We find that long-range intersubunit correlation of amino-acid pairs is weaker in the thermosome ring than in GroEL. Overall, our results indicate that distinct allosteric behavior of the two chaperonin classes originates from different wiring of individual subunits as well as of the intersubunit communications.

The pleckstrin homology (PH) domain of the Arf exchange factor Brag2 is an allosteric binding site

Brag2, a Sec7 domain (sec7d)-containing guanine nucleotide exchange factor, regulates cell adhesion and tumor cell invasion. Brag2 catalyzes nucleotide exchange, converting Arf·GDP to Arf·GTP. Brag2 contains a pleckstrin homology (PH) domain, and its nucleotide exchange activity is stimulated by phosphatidylinositol 4,5-bisphosphate (PIP(2)). Here we determined kinetic parameters for Brag2 and examined the basis for regulation by phosphoinositides. Using myristoylated Arf1·GDP as a substrate, the k(cat) was 1.8 ± 0.1/s as determined by single turnover kinetics, and the K(m) was 0.20 ± 0.07 μm as determined by substrate saturation kinetics. PIP(2) decreased the K(m) and increased the k(cat) of the reaction. The effect of PIP(2) required the PH domain of Brag2 and the N terminus of Arf and was largely independent of Arf myristoylation. Structural analysis indicated that the linker between the sec7d and the PH domain in Brag2 may directly contact Arf. In support, we found that a Brag2 fragment containing the sec7d and the linker was more active than sec7d alone. We conclude that Brag2 is allosterically regulated by PIP(2) binding to the PH domain and that activity depends on the interdomain linker. Thus, the PH domain and the interdomain linker of Brag2 may be targets for selectively regulating the activity of Brag2.

Extracellular complexes of the hematopoietic human and mouse CSF-1 receptor are driven by common assembly principles

The hematopoietic colony stimulating factor-1 receptor (CSF-1R or FMS) is essential for the cellular repertoire of the mammalian immune system. Here, we report a structural and mechanistic consensus for the assembly of human and mouse CSF-1:CSF-1R complexes. The EM structure of the complete extracellular assembly of the human CSF-1:CSF-1R complex reveals how receptor dimerization by CSF-1 invokes a ternary complex featuring extensive homotypic receptor contacts and striking structural plasticity at the extremities of the complex. Studies by small-angle X-ray scattering of unliganded hCSF-1R point to large domain rearrangements upon CSF-1 binding, and provide structural evidence for the relevance of receptor predimerization at the cell surface. Comparative structural and binding studies aiming to dissect the assembly principles of human and mouse CSF-1R complexes, including a quantification of the CSF-1/CSF-1R species cross-reactivity, show that bivalent cytokine binding to receptor coupled to ensuing receptor-receptor interactions are common denominators in extracellular complex formation.

Accurate flexible fitting of high-resolution protein structures into cryo-electron microscopy maps using coarse-grained pseudo-energy minimization

Cryo-electron microscopy (cryo-EM) has been widely used to explore conformational states of large biomolecular assemblies. The detailed interpretation of cryo-EM data requires the flexible fitting of a known high-resolution protein structure into a low-resolution cryo-EM map. To this end, we have developed what we believe is a new method based on a two-bead-per-residue protein representation, and a modified form of the elastic network model that allows large-scale conformational changes while maintaining pseudobonds and secondary structures. Our method minimizes a pseudo-energy which linearly combines various terms of the modified elastic network model energy with a cryo-EM-fitting score and a collision energy that penalizes steric collisions. Unlike previous flexible fitting efforts using the lowest few normal modes, our method effectively utilizes all normal modes so that both global and local structural changes can be fully modeled. We have validated our method for a diverse set of 10 pairs of protein structures using simulated cryo-EM maps with a range of resolutions and in the absence/presence of random noise. We have shown that our method is both accurate and efficient compared with alternative techniques, and its performance is robust to the addition of random noise. Our method is also shown to be useful for the flexible fitting of three experimental cryo-EM maps.

Exploring the spatial and temporal organization of a cell's proteome

To increase our current understanding of cellular processes, such as cell signaling and division, knowledge is needed about the spatial and temporal organization of the proteome at different organizational levels. These levels cover a wide range of length and time scales: from the atomic structures of macromolecules for inferring their molecular function, to the quantitative description of their abundance, and spatial distribution in the cell. Emerging new experimental technologies are greatly increasing the availability of such spatial information on the molecular organization in living cells. This review addresses three fields that have significantly contributed to our understanding of the proteome's spatial and temporal organization: first, methods for the structure determination of individual macromolecular assemblies, specifically the fitting of atomic structures into density maps generated from electron microscopy techniques; second, research that visualizes the spatial distributions of these complexes within the cellular context using cryo electron tomography techniques combined with computational image processing; and third, methods for the spatial modeling of the dynamic organization of the proteome, specifically those methods for simulating reaction and diffusion of proteins and complexes in crowded intracellular fluids. The long-term goal is to integrate the varied data about a proteome's organization into a spatially explicit, predictive model of cellular processes.

Scoring functions for cryoEM density fitting

In fitting atomic structures into cryoEM density maps of macromolecular assemblies, the cross-correlation function (CCF) is the most prevalent method of scoring the goodness-of-fit. However, there are still many possible, less studied ways of scoring fits. In this paper, we introduce four scores new to cryoEM fitting and compare their performance to three known scores. Our benchmark consists of (a) 4 protein assemblies with simulated maps at 5-20 Å resolution, including the heptameric ring of GroEL; and (b) 4 experimental maps of GroEL at ∼6-23 Å resolution with corresponding fitted atomic models. We perturb each fit 1000 times and assess each new fit with each score. The correlation between a score and the Cα RMSD of each fit from the "correctly" fitted structure shows that the CCF is one of the best scores, but in certain situations could be augmented or even replaced by other scores. For instance, our implementation of a score based on mutual information outperforms or is comparable to the CCF in almost all test cases, and our new "envelope score" works as well as the CCF at sub-nanometer resolution but is an order of magnitude faster to calculate. The results also suggest that the width of the Gaussian function used to blur the atomic structure into a density map can significantly affect the fitting process. Finally, we show that our score-testing method, when combined with the Laplacian CCF or the mutual information scores, can be used as a statistical tool for improving cryoEM density fitting.

The structure of avian polyomavirus reveals variably sized capsids, non-conserved inter-capsomere interactions, and a possible location of the minor capsid protein VP4

Avian polyomavirus (APV) causes a fatal, multi-organ disease among several bird species. Using cryogenic electron microscopy and other biochemical techniques, we investigated the structure of APV and compared it to that of mammalian polyomaviruses, particularly JC polyomavirus and simian virus 40. The structure of the pentameric major capsid protein (VP1) is mostly conserved; however, APV VP1 has a unique, truncated C-terminus that eliminates an intercapsomere-connecting β-hairpin observed in other polyomaviruses. We postulate that the terminal β-hairpin locks other polyomavirus capsids in a stable conformation and that absence of the hairpin leads to the observed capsid size variation in APV. Plug-like density features were observed at the base of the VP1 pentamers, consistent with the known location of minor capsid proteins VP2 and VP3. However, the plug density is more prominent in APV and may include VP4, a minor capsid protein unique to bird polyomaviruses.

From electron microscopy maps to atomic structures using normal mode-based fitting

Electron microscopy (EM) has made possible to solve the structure of many proteins. However, the resolution of some of the EM maps is too low for interpretation at the atomic level, which is particularly important to describe function. We describe methods that combine low-resolution EM data with atomic structures for different conformations of the same protein in order to produce atomic models compatible with the EM map.We illustrate these methods with EM data from decavanadate-induced tubular crystals of a pseudo-phosphorylated intermediate of Ca-ATPase and the various atomic structures of other intermediates available in the Protein Data Bank (PDB). Determination of atomic structure permits not only to analyse protein-protein interactions in the crystals, but also to localize residues in the proximity of the crystallizing agent both within Ca-ATPase and between Ca-ATPase molecules.

Interactions of the acidic domain and SRF interacting motifs with the NKX3.1 homeodomain

NKX3.1 is a prostate tumor suppressor belonging to the NK-2 family of homeodomain (HD) transcription factors. NK-2 family members often possess a stretch of 10-15 residues enriched in acidic amino acids, the acidic domain (AD), in the flexible, disordered region N-terminal to the HD. Interactions between the N-terminal region of NKX3.1 and its homeodomain affect protein stability and DNA binding. CD spectroscopy measuring the thermal unfolding of NKX3.1 constructs showed a 2 degrees C intramolecular stabilization of the HD by the N-terminal region containing the acidic domain (residues 85-96). CD of mixtures of various N-terminal peptides with a construct containing just the HD showed that the acidic domain and the following region, the SRF interacting (SI) motif (residues 99-105), was necessary for this stabilization. Phosphorylation of the acidic domain is known to slow proteasomal degradation of NKX3.1 in prostate cells, and NMR spectroscopy was used to measure and map the interaction of the HD with phosphorylated and nonphosphorylated forms of the AD peptide. The interaction with the phosphorylated AD peptide was considerably stronger (K(d) = 0.5 +/- 0.2 mM), resulting in large chemical shift perturbations for residues Ser150 and Arg175 in the HD, as well as a 2 degrees C increase in the HD thermal stability compared to that of the nonphosphorylated form. NKX3.1 constructs with AD phosphorylation site threonine residues (89 and 93) mutated to glutamate were 4 degrees C more stable than HD alone. Using polymer theory, effective concentrations for interactions between domains connected by flexible linkers are predicted to be in the millimolar range, and thus, the weak intramolecular interactions observed here could conceivably modulate or compete with stronger, intermolecular interactions with the NKX3.1 HD.

CHARMM: the biomolecular simulation program

CHARMM (Chemistry at HARvard Molecular Mechanics) is a highly versatile and widely used molecular simulation program. It has been developed over the last three decades with a primary focus on molecules of biological interest, including proteins, peptides, lipids, nucleic acids, carbohydrates, and small molecule ligands, as they occur in solution, crystals, and membrane environments. For the study of such systems, the program provides a large suite of computational tools that include numerous conformational and path sampling methods, free energy estimators, molecular minimization, dynamics, and analysis techniques, and model-building capabilities. The CHARMM program is applicable to problems involving a much broader class of many-particle systems. Calculations with CHARMM can be performed using a number of different energy functions and models, from mixed quantum mechanical-molecular mechanical force fields, to all-atom classical potential energy functions with explicit solvent and various boundary conditions, to implicit solvent and membrane models. The program has been ported to numerous platforms in both serial and parallel architectures. This article provides an overview of the program as it exists today with an emphasis on developments since the publication of the original CHARMM article in 1983.

Interpretation of very low resolution X-ray electron-density maps using core objects

A novel approach to obtaining structural information from macromolecular X-ray data extending to resolutions as low as 20 A is presented. Following a simple map-segmentation procedure, the approximate shapes of the domains forming the structure are identified. A pattern-recognition comparative analysis of these shapes and those derived from the structures of domains from the PDB results in candidate structural models that can be used for a fit into the density map. It is shown that the placed candidate models can be employed for subsequent phase extension to higher resolution.

Role of HAMP domains in chemotaxis signaling by bacterial chemoreceptors

Bacterial chemoreceptors undergo conformational changes in response to variations in the concentration of extracellular ligands. These changes in chemoreceptor structure initiate a series of signaling events that ultimately result in regulation of rotation of the flagellar motor. Here we have used cryo-electron tomography combined with 3D averaging to determine the in situ structure of chemoreceptor assemblies in Escherichia coli cells that have been engineered to overproduce the serine chemoreceptor Tsr. We demonstrate that chemoreceptors are organized as trimers of receptor dimers and display two distinct conformations that differ principally in arrangement of the HAMP domains within each trimer. Ligand binding and methylation alter the distribution of chemoreceptors between the two conformations, with serine binding favoring the "expanded" conformation and chemoreceptor methylation favoring the "compact" conformation. The distinct positions of chemoreceptor HAMP domains within the context of a trimeric unit are thus likely to represent important aspects of chemoreceptor structural changes relevant to chemotaxis signaling. Based on these results, we propose that the compact and expanded conformations represent the "kinase-on" and "kinase-off" states of chemoreceptor trimers, respectively.

Multiscale methods for macromolecular simulations

In this article we review the key modeling tools available for simulating biomolecular systems. We consider recent developments and representative applications of mixed quantum mechanics/molecular mechanics (QM/MM), elastic network models (ENMs), coarse-grained molecular dynamics, and grid-based tools for calculating interactions between essentially rigid protein assemblies. We consider how the different length scales can be coupled, both in a sequential fashion (e.g. a coarse-grained or grid model using parameterization from MD simulations), and via concurrent approaches, where the calculations are performed together and together control the progression of the simulation. We suggest how the concurrent coupling approach familiar in the context of QM/MM calculations can be generalized, and describe how this has been done in the CHARMM macromolecular simulation package.

Multiple subunit fitting into a low-resolution density map of a macromolecular complex using a gaussian mixture model

Recently, electron microscopy measurement of single particles has enabled us to reconstruct a low-resolution 3D density map of large biomolecular complexes. If structures of the complex subunits can be solved by x-ray crystallography at atomic resolution, fitting these models into the 3D density map can generate an atomic resolution model of the entire large complex. The fitting of multiple subunits, however, generally requires large computational costs; therefore, development of an efficient algorithm is required. We developed a fast fitting program, “gmfit”, which employs a Gaussian mixture model (GMM) to represent approximated shapes of the 3D density map and the atomic models. A GMM is a distribution function composed by adding together several 3D Gaussian density functions. Because our model analytically provides an integral of a product of two distribution functions, it enables us to quickly calculate the fitness of the density map and the atomic models. Using the integral, two types of potential energy function are introduced: the attraction potential energy between a 3D density map and each subunit, and the repulsion potential energy between subunits. The restraint energy for symmetry is also employed to build symmetrical origomeric complexes. To find the optimal configuration of subunits, we randomly generated initial configurations of subunit models, and performed a steepest-descent method using forces and torques of the three potential energies. Comparison between an original density map and its GMM showed that the required number of Gaussian distribution functions for a given accuracy depended on both resolution and molecular size. We then performed test fitting calculations for simulated low-resolution density maps of atomic models of homodimer, trimer, and hexamer, using different search parameters. The results indicated that our method was able to rebuild atomic models of a complex even for maps of 30 Å resolution if sufficient numbers (eight or more) of Gaussian distribution functions were employed for each subunit, and the symmetric restraints were assigned for complexes with more than three subunits. As a more realistic test, we tried to build an atomic model of the GroEL/ES complex by fitting 21-subunit atomic models into the 3D density map obtained by cryoelectron microscopy using the C7 symmetric restraints. A model with low root mean-square deviations (14.7 Å) was obtained as the lowest-energy model, showing that our fitting method was reasonably accurate. Inclusion of other restraints from biological and biochemical experiments could further enhance the accuracy.

Chemoreceptors in Caulobacter crescentus: trimers of receptor dimers in a partially ordered hexagonally packed array

Chemoreceptor arrays are macromolecular complexes that form extended assemblies primarily at the poles of bacterial cells and mediate chemotaxis signal transduction, ultimately controlling cellular motility. We have used cryo-electron tomography to determine the spatial distribution and molecular architecture of signaling molecules that comprise chemoreceptor arrays in wild-type Caulobacter crescentus cells. We demonstrate that chemoreceptors are organized as trimers of receptor dimers, forming partially ordered hexagonally packed arrays of signaling complexes in the cytoplasmic membrane. This novel organization at the threshold between order and disorder suggests how chemoreceptors and associated molecules are arranged in signaling assemblies to respond dynamically in the activation and adaptation steps of bacterial chemotaxis.

Electron microscopy and image processing: an essential tool for structural analysis of macromolecules

Macromolecular electron microscopy (EM) deals with macromolecular complexes and their placement within the cell-linking the molecular and cellular worlds as a bridge between atomic-resolution X-ray crystallographic or NMR studies and lower resolution light microscopy. The amount of specimen required is typically 10(2) to 10(3) times less than for X-ray crystallography or NMR. Electron micrographs of frozen-hydrated specimens portray native structures. Computer averaging yields enhanced images with reduced noise. Three-dimensional reconstructions may be computed from multiple views. Under favorable circumstances, resolutions of 7 to 10 A are achieved. Fitting atomic-resolution coordinates of components into three-dimensional density maps gives pseudo-atomic models of a complex's structure and interactions. Time-resolved experiments describe conformational changes. Electron tomography allows reconstruction of pleiomorphic complexes and sub-cellular structures. Electron crystallography has produced near-atomic resolution models of two-dimensional arrays, notably of membrane proteins.

Dynamic interaction between Arf GAP and PH domains of ASAP1 in the regulation of GAP activity

ASAP family Arf GAPs induce the hydrolysis of GTP bound to the Ras superfamily protein Arf1, regulate cell adhesion and migration and have been implicated in carcinogenesis. The ASAP proteins have a core catalytic domain of PH, Arf GAP and Ank repeat domains. The PH domain is necessary for both biological and catalytic functions of ASAP1 and has been proposed to be integrally folded with the Arf GAP domain. Protection studies and analytical ultracentrifugation studies previously reported indicated that the domains are, at least partly, folded together. Here, using NMR spectroscopy and biochemical analysis, we have further tested this hypothesis and characterized the interdomain interaction. A comparison of NMR spectra of three recombinant proteins comprised of either the isolated PH domain of ASAP1, the Arf GAP and ankyrin repeat domain or all three domains indicated that the PH domain did interact with the Arf GAP and Ank repeat domains; however, we found a significant amount of dynamic independence between the PH and Arf GAP domains, consistent with the interactions being transient. In contrast, the Arf GAP and Ank repeat domains form a relatively rigid structure. The PH-Arf GAP domain interaction partially occluded the phosphoinositide binding site in the soluble protein, but binding studies indicated the PIP2 binding site was accessible in ASAP1 bound to a lipid bilayer surface. Phosphoinositide binding altered the conformation of the PH domain, but had little effect on the structure of the Arf GAP domain. Mutations in a loop of the PH domain that contacts the Arf GAP domain affected PIP2 binding and the K(m) and k(cat) for converting Arf1 GTP to Arf1 GDP. Based on these results, we generated a homology model of a composite PH/Arf GAP/Ank repeat domain structure. We propose that the PH domain contributes to Arf GAP activity by either binding to or positioning Arf1 GTP that is simultaneously bound to the Arf GAP domain.

Receptor-based modeling and 3D-QSAR for a quantitative production of the butyrylcholinesterase inhibitors based on genetic algorithm

Three-dimensional quantitative structure-activity relationship (3D-QSAR) models have been constructed using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) for a series of structurally related steroidal alkaloids as butyrylcholinesterase (BuChE) inhibitors. Docking studies were employed to position the inhibitors into the BuChE active site to determine the most probable binding mode. The strategy was to explore multiple inhibitor conformations in producing a more reliable 3D-QSAR model. These multiple conformations were derived using the FlexS program. The conformation selection step for CoMFA was done by genetic algorithm. The genetic algorithm based CoMFA approach was found to be the best. Both CoMFA and CoMSIA yielded significant cross-validated q(2) values of 0.701 and 0.627 and the r(2) values of 0.979 and 0.982, respectively. These statistically significant models were validated by a test set of five compounds. Comparison of CoMFA and CoMSIA contour maps helped to identify structural requirements for the inhibitors and serves as a basis for the design of the next generation of the inhibitor analogues. The results demonstrate that the combination of ligand-based and receptor-based modeling with use of a genetic algorithm is a powerful approach to build 3D-QSAR models. These data can be used for the lead optimization process with respect to inhibition enhancement which is important for the drug discovery and development for Alzheimer's disease.

Extended polypeptide linkers establish the spatial architecture of a pyruvate dehydrogenase multienzyme complex

Icosahedral pyruvate dehydrogenase (PDH) enzyme complexes are molecular machines consisting of a central E2 core decorated by a shell of peripheral enzymes (E1 and E3) found localized at a distance of approximately 75-90 A from the core. Using a combination of biochemical, biophysical, and cryo-electron microscopic techniques, we show here that the gap between the E2 core and the shell of peripheral enzymes is maintained by the flexible but extended conformation adopted by 60 linker polypeptides that radiate outwards from the inner E2 core, irrespective of the E1 or E3 occupancy. The constancy of the gap is thus not due to protein-protein interactions in the outer protein shell. The extended nature of the E2 inner-linker regions thereby creates the restricted annular space in which the lipoyl domains of E2 that carry catalytic intermediates shuttle between E1, E2, and E3 active sites, while their conformational flexibility facilitates productive encounters.

Combining efficient conformational sampling with a deformable elastic network model facilitates structure refinement at low resolution

Structural studies of large proteins and protein assemblies are a difficult and pressing challenge in molecular biology. Experiments often yield only low-resolution or sparse data that are not sufficient to fully determine atomistic structures. We have developed a general geometry-based algorithm that efficiently samples conformational space under constraints imposed by low-resolution density maps obtained from electron microscopy or X-ray crystallography experiments. A deformable elastic network (DEN) is used to restrain the sampling to prior knowledge of an approximate structure. The DEN restraints dramatically reduce over-fitting, especially at low resolution. Cross-validation is used to optimally weight the structural information and experimental data. Our algorithm is robust even for noise-added density maps and has a large radius of convergence for our test case. The DEN restraints can also be used to enhance reciprocal space simulated annealing refinement.

Integrating diverse data for structure determination of macromolecular assemblies

To understand the cell, we need to determine the macromolecular assembly structures, which may consist of tens to hundreds of components. First, we review the varied experimental data that characterize the assemblies at several levels of resolution. We then describe computational methods for generating the structures using these data. To maximize completeness, resolution, accuracy, precision, and efficiency of the structure determination, a computational approach is required that uses spatial information from a variety of experimental methods. We propose such an approach, defined by its three main components: a hierarchical representation of the assembly, a scoring function consisting of spatial restraints derived from experimental data, and an optimization method that generates structures consistent with the data. This approach is illustrated by determining the configuration of the 456 proteins in the nuclear pore complex (NPC) from baker's yeast. With these tools, we are poised to integrate structural information gathered at multiple levels of the biological hierarchy--from atoms to cells--into a common framework.