Structural and dynamic insights into α-synuclein dimer conformations

Parkinson disease is associated with the aggregation of the protein α-synuclein. While α-synuclein can exist in multiple oligomeric states, the dimer has been a subject of extensive debates. Here, using an array of biophysical approaches, we demonstrate that α-synuclein in vitro exhibits primarily a monomer-dimer equilibrium in nanomolar concentrations and up to a few micromolars. We then use spatial information from hetero-isotopic cross-linking mass spectrometry experiments as restrains in discrete molecular dynamics simulations to obtain the ensemble structure of dimeric species. Out of eight structural sub-populations of dimers, we identify one that is compact, stable, abundant, and exhibits partially exposed β-sheet structures. This compact dimer is the only one where the hydroxyls of tyrosine 39 are in proximity that may promote dityrosine covalent linkage upon hydroxyl radicalization, which is implicated in α-synuclein amyloid fibrils. We propose that this α-synuclein dimer features etiological relevance to Parkinson disease.

The double homeodomain protein DUX4c is associated with regenerating muscle fibers and RNA-binding proteins

BACKGROUND

 We have previously demonstrated that double homeobox 4 centromeric (DUX4C) encoded for a functional DUX4c protein upregulated in dystrophic skeletal muscles. Based on gain- and loss-of-function studies we have proposed DUX4c involvement in muscle regeneration. Here, we provide further evidence for such a role in skeletal muscles from patients affected with facioscapulohumeral muscular dystrophy (FSHD).

METHODS

DUX4c was studied at RNA and protein levels in FSHD muscle cell cultures and biopsies. Its protein partners were co-purified and identified by mass spectrometry. Endogenous DUX4c was detected in FSHD muscle sections with either its partners or regeneration markers using co-immunofluorescence or in situ proximity ligation assay.

RESULTS

We identified new alternatively spliced DUX4C transcripts and confirmed DUX4c immunodetection in rare FSHD muscle cells in primary culture. DUX4c was detected in nuclei, cytoplasm or at cell-cell contacts between myocytes and interacted sporadically with specific RNA-binding proteins involved, a.o., in muscle differentiation, repair, and mass maintenance. In FSHD muscle sections, DUX4c was found in fibers with unusual shape or central/delocalized nuclei (a regeneration feature) staining for developmental myosin heavy chain, MYOD or presenting intense desmin labeling. Some couples of myocytes/fibers locally exhibited peripheral DUX4c-positive areas that were very close to each other, but in distinct cells. MYOD or intense desmin staining at these locations suggested an imminent muscle cell fusion. We further demonstrated DUX4c interaction with its major protein partner, C1qBP, inside myocytes/myofibers that presented features of regeneration. On adjacent muscle sections, we could unexpectedly detect DUX4 (the FSHD causal protein) and its interaction with C1qBP in fusing myocytes/fibers.

CONCLUSIONS

DUX4c upregulation in FSHD muscles suggests it contributes not only to the pathology but also, based on its protein partners and specific markers, to attempts at muscle regeneration. The presence of both DUX4 and DUX4c in regenerating FSHD muscle cells suggests DUX4 could compete with normal DUX4c functions, thus explaining why skeletal muscle is particularly sensitive to DUX4 toxicity. Caution should be exerted with therapeutic agents aiming for DUX4 suppression because they might also repress the highly similar DUX4c and interfere with its physiological role.

The structural heterogeneity of α-synuclein is governed by several distinct subpopulations with interconversion times slower than milliseconds

α-Synuclein plays an important role in synaptic functions by interacting with synaptic vesicle membrane, while its oligomers and fibrils are associated with several neurodegenerative diseases. The specific monomer structures that promote its membrane binding and self-association remain elusive due to its transient nature as an intrinsically disordered protein. Here, we use inter-dye distance distributions from bulk time-resolved Förster resonance energy transfer as restraints in discrete molecular dynamics simulations to map the conformational space of the α-synuclein monomer. We further confirm the generated conformational ensemble in orthogonal experiments utilizing far-UV circular dichroism and cross-linking mass spectrometry. Single-molecule protein-induced fluorescence enhancement measurements show that within this conformational ensemble, some of the conformations of α-synuclein are surprisingly stable, exhibiting conformational transitions slower than milliseconds. Our comprehensive analysis of the conformational ensemble reveals essential structural properties and potential conformations that promote its various functions in membrane interaction or oligomer and fibril formation.

Targeted in situ cross-linking mass spectrometry and integrative modeling reveal the architectures of three proteins from SARS-CoV-2

Atomic structures of several proteins from the coronavirus family are still partial or unavailable. A possible reason for this gap is the instability of these proteins outside of the cellular context, thereby prompting the use of in-cell approaches. In situ cross-linking and mass spectrometry (in situ CLMS) can provide information on the structures of such proteins as they occur in the intact cell. Here, we applied targeted in situ CLMS to structurally probe Nsp1, Nsp2, and nucleocapsid (N) proteins from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and obtained cross-link sets with an average density of one cross-link per 20 residues. We then employed integrative modeling that computationally combined the cross-linking data with domain structures to determine full-length atomic models. For the Nsp2, the cross-links report on a complex topology with long-range interactions. Integrative modeling with structural prediction of individual domains by the AlphaFold2 system allowed us to generate a single consistent all-atom model of the full-length Nsp2. The model reveals three putative metal binding sites and suggests a role for Nsp2 in zinc regulation within the replication-transcription complex. For the N protein, we identified multiple intra- and interdomain cross-links. Our integrative model of the N dimer demonstrates that it can accommodate three single RNA strands simultaneously, both stereochemically and electrostatically. For the Nsp1, cross-links with the 40S ribosome were highly consistent with recent cryogenic electron microscopy structures. These results highlight the importance of cellular context for the structural probing of recalcitrant proteins and demonstrate the effectiveness of targeted in situ CLMS and integrative modeling.

Facilitating In Situ Cross-Linking and Mass Spectrometry by Antibody-Based Protein Enrichment

Cross-linking of living cells followed by mass spectrometry identification of cross-linked peptides (in situ CLMS) is an emerging technology to study protein structures in their native environment. One of the inherent difficulties of this technology is the high complexity of the samples following cell lysis. Currently, this difficulty largely limits the identification of cross-links to the more abundant proteins in the cell. Here, we describe a targeted approach in which an antibody is used to purify a specific protein-of-interest out of the cell lysate. Mass spectrometry analysis of the protein material that binds to the antibody can then identify considerably more cross-links on the target protein. By using an antibody against the CCT chaperonin, we identified over 200 cross-links that provide in situ evidence for the subunit arrangement of the CCT particle and its interactions with prefoldin. Similar targeting with an antibody against tubulin provided in situ evidence for the structure of the microtubule. Finally, the approach was also successful in identifying cross-links within a protein that expresses at a low level. These results demonstrate the general utility of antibody-based sample simplification for in situ CLMS and greatly expand the scope of protein systems that are amenable to in situ structural studies.

Open Search Strategy for Inferring the Masses of Cross-Link Adducts on Proteins

Development of new reagents for protein cross-linking is constantly ongoing. The chemical formulas for the linker adducts formed by these reagents are usually deduced from expert knowledge and then validated by mass spectrometry. Clearly, it would be more rigorous to infer the chemical compositions of the adducts directly from the data without any prior assumptions on their chemistries. Unfortunately, the analysis tools that are currently available to detect chemical modifications on linear peptides are not applicable to the case of two cross-linked peptides. Here, we show that an adaptation of the open search strategy that works on linear peptides can be used to characterize cross-link modifications in pairs of peptides. We benchmark our approach by correctly inferring the linker masses of two well-known reagents, DSS and formaldehyde, to accuracies of a few parts per million. We then investigate the cross-linking chemistries of two poorly characterized reagents: EMCS and glutaraldehyde. In the case of EMCS, we find that the expected cross-linking chemistry is accompanied by a competing chemistry that targets other amino acid types. In the case of glutaraldehyde, we find that the chemical formula of the dominant linker is C₅H₄, which indicates a ringed aromatic structure. These results demonstrate how, with very little effort, our approach can yield nontrivial insights to better characterize new cross-linkers.

Structure of the Human Core Centromeric Nucleosome Complex

Centromeric nucleosomes are at the interface of the chromosome and the kinetochore that connects to spindle microtubules in mitosis. The core centromeric nucleosome complex (CCNC) harbors the histone H3 variant, CENP-A, and its binding proteins, CENP-C (through its central domain; CD) and CENP-N (through its N-terminal domain; NT). CENP-C can engage nucleosomes through two domains: the CD and the CENP-C motif (CM). CENP-CCD is part of the CCNC by virtue of its high specificity for CENP-A nucleosomes and ability to stabilize CENP-A at the centromere. CENP-CCM is thought to engage a neighboring nucleosome, either one containing conventional H3 or CENP-A, and a crystal structure of a nucleosome complex containing two copies of CENP-CCM was reported. Recent structures containing a single copy of CENP-NNT bound to the CENP-A nucleosome in the absence of CENP-C were reported. Here, we find that one copy of CENP-N is lost for every two copies of CENP-C on centromeric chromatin just prior to kinetochore formation. We present the structures of symmetric and asymmetric forms of the CCNC that vary in CENP-N stoichiometry. Our structures explain how the central domain of CENP-C achieves its high specificity for CENP-A nucleosomes and how CENP-C and CENP-N sandwich the histone H4 tail. The natural centromeric DNA path in our structures corresponds to symmetric surfaces for CCNC assembly, deviating from what is observed in prior structures using artificial sequences. At mitosis, we propose that CCNC asymmetry accommodates its asymmetric connections at the chromosome/kinetochore interface. VIDEO ABSTRACT.

First Community-Wide, Comparative Cross-Linking Mass Spectrometry Study

The number of publications in the field of chemical cross-linking combined with mass spectrometry (XL-MS) to derive constraints for protein three-dimensional structure modeling and to probe protein-protein interactions has increased during the last years. As the technique is now becoming routine for in vitro and in vivo applications in proteomics and structural biology there is a pressing need to define protocols as well as data analysis and reporting formats. Such consensus formats should become accepted in the field and be shown to lead to reproducible results. This first, community-based harmonization study on XL-MS is based on the results of 32 groups participating worldwide. The aim of this paper is to summarize the status quo of XL-MS and to compare and evaluate existing cross-linking strategies. Our study therefore builds the framework for establishing best practice guidelines to conduct cross-linking experiments, perform data analysis, and define reporting formats with the ultimate goal of assisting scientists to generate accurate and reproducible XL-MS results.

Integrative Structure Modeling: Overview and Assessment

Integrative structure modeling computationally combines data from multiple sources of information with the aim of obtaining structural insights that are not revealed by any single approach alone. In the first part of this review, we survey the commonly used sources of structural information and the computational aspects of model building. Throughout the past decade, integrative modeling was applied to various biological systems, with a focus on large protein complexes. Recent progress in the field of cryo-electron microscopy (cryo-EM) has resolved many of these complexes to near-atomic resolution. In the second part of this review, we compare a range of published integrative models with their higher-resolution counterparts with the aim of critically assessing their accuracy. This comparison gives a favorable view of integrative modeling and demonstrates its ability to yield accurate and informative results. We discuss possible roles of integrative modeling in the new era of cryo-EM and highlight future challenges and directions.

Automatic Inference of Sequence from Low-Resolution Crystallographic Data

At resolutions worse than 3.5 Å, the electron density is weak or nonexistent at the locations of the side chains. Consequently, the assignment of the protein sequences to their correct positions along the backbone is a difficult problem. In this work, we propose a fully automated computational approach to assign sequence at low resolution. It is based on our surprising observation that standard reciprocal-space indicators, such as the initial unrefined R value, are sensitive enough to detect an erroneous sequence assignment of even a single backbone position. Our approach correctly determines the amino acid type for 15%, 13%, and 9% of the backbone positions in crystallographic datasets with resolutions of 4.0 Å, 4.5 Å, and 5.0 Å, respectively. We implement these findings in an application for threading a sequence onto a backbone structure. For the three resolution ranges, the application threads 83%, 81%, and 64% of the sequences exactly as in the deposited PDB structures.

Architecture of an RNA polymerase II transcription pre-initiation complex

The protein density and arrangement of subunits of a complete, 32-protein, RNA polymerase II (pol II) transcription pre-initiation complex (PIC) were determined by means of cryogenic electron microscopy and a combination of chemical cross-linking and mass spectrometry. The PIC showed a marked division in two parts, one containing all the general transcription factors (GTFs) and the other pol II. Promoter DNA was associated only with the GTFs, suspended above the pol II cleft and not in contact with pol II. This structural principle of the PIC underlies its conversion to a transcriptionally active state; the PIC is poised for the formation of a transcription bubble and descent of the DNA into the pol II cleft.

The crystal structures of the eukaryotic chaperonin CCT reveal its functional partitioning

In eukaryotes, CCT is essential for the correct and efficient folding of many cytosolic proteins, most notably actin and tubulin. Structural studies of CCT have been hindered by the failure of standard crystallographic analysis to resolve its eight different subunit types at low resolutions. Here, we exhaustively assess the R value fit of all possible CCT models to available crystallographic data of the closed and open forms with resolutions of 3.8 Å and 5.5 Å, respectively. This unbiased analysis finds the native subunit arrangements with overwhelming significance. The resulting structures provide independent crystallographic proof of the subunit arrangement of CCT and map major asymmetrical features of the particle onto specific subunits. The actin and tubulin substrates both bind around subunit CCT6, which shows other structural anomalies. CCT is thus clearly partitioned, both functionally and evolutionary, into a substrate-binding side that is opposite to the ATP-hydrolyzing side.

Structure-based identification of catalytic residues

The identification of catalytic residues is an essential step in functional characterization of enzymes. We present a purely structural approach to this problem, which is motivated by the difficulty of evolution-based methods to annotate structural genomics targets that have few or no homologs in the databases. Our approach combines a state-of-the-art support vector machine (SVM) classifier with novel structural features that augment structural clues by spatial averaging and Z scoring. Special attention is paid to the class imbalance problem that stems from the overwhelming number of non-catalytic residues in enzymes compared to catalytic residues. This problem is tackled by: (1) optimizing the classifier to maximize a performance criterion that considers both Type I and Type II errors in the classification of catalytic and non-catalytic residues; (2) under-sampling non-catalytic residues before SVM training; and (3) during SVM training, penalizing errors in learning catalytic residues more than errors in learning non-catalytic residues. Tested on four enzyme datasets, one specifically designed by us to mimic the structural genomics scenario and three previously evaluated datasets, our structure-based classifier is never inferior to similar structure-based classifiers and comparable to classifiers that use both structural and evolutionary features. In addition to the evaluation of the performance of catalytic residue identification, we also present detailed case studies on three proteins. This analysis suggests that many false positive predictions may correspond to binding sites and other functional residues. A web server that implements the method, our own-designed database, and the source code of the programs are publicly available at http://www.cs.bgu.ac.il/∼meshi/functionPrediction.

Consistent refinement of submitted models at CASP using a knowledge-based potential

Protein structure refinement is an important but unsolved problem; it must be solved if we are to predict biological function that is very sensitive to structural details. Specifically, critical assessment of techniques for protein structure prediction (CASP) shows that the accuracy of predictions in the comparative modeling category is often worse than that of the template on which the homology model is based. Here we describe a refinement protocol that is able to consistently refine submitted predictions for all categories at CASP7. The protocol uses direct energy minimization of the knowledge-based potential of mean force that is based on the interaction statistics of 167 atom types (Summa and Levitt, Proc Natl Acad Sci USA 2007; 104:3177-3182). Our protocol is thus computationally very efficient; it only takes a few minutes of CPU time to run typical protein models (300 residues). We observe an average structural improvement of 1% in GDT_TS, for predictions that have low and medium homology to known PDB structures (Global Distance Test score or GDT_TS between 50 and 80%). We also observe a marked improvement in the stereochemistry of the models. The level of improvement varies amongst the various participants at CASP, but we see large improvements (>10% increase in GDT_TS) even for models predicted by the best performing groups at CASP7. In addition, our protocol consistently improved the best predicted models in the refinement category at CASP7 and CASP8. These improvements in structure and stereochemistry prove the usefulness of our computationally inexpensive, powerful and automatic refinement protocol.

Differentiable, multi-dimensional, knowledge-based energy terms for torsion angle probabilities and propensities

Rotatable torsion angles are the major degrees of freedom in proteins. Adjacent angles are highly correlated and energy terms that rely on these correlations are intensively used in molecular modeling. However, the utility of torsion based terms is not yet fully exploited. Many of these terms do not capture the full scale of the correlations. Other terms, which rely on lookup tables, cannot be used in the context of force-driven algorithms because they are not fully differentiable. This study aims to extend the usability of torsion terms by presenting a set of high-dimensional and fully-differentiable energy terms that are derived from high-resolution structures. The set includes terms that describe backbone conformational probabilities and propensities, side-chain rotamer probabilities, and an elaborate term that couples all the torsion angles within the same residue. The terms are constructed by cubic spline interpolation with periodic boundary conditions that enable full differentiability and high computational efficiency. We show that the spline implementation does not compromise the accuracy of the original database statistics. We further show that the side-chain relevant terms are compatible with established rotamer probabilities. Despite their very local characteristics, the new terms are often able to identify native and native-like structures within decoy sets. Finally, force-based minimization of NMR structures with the new terms improves their torsion angle statistics with minor structural distortion (0.5 A RMSD on average). The new terms are freely available in the MESHI molecular modeling package. The spline coefficients are also available as a documented MATLAB file.

Prediction of structural stability of short beta-hairpin peptides by molecular dynamics and knowledge-based potentials

BACKGROUND

The structural stability of peptides in solution strongly affects their binding affinities and specificities. Thus, in peptide biotechnology, an increase in the structural stability is often desirable. The present work combines two orthogonal computational techniques, Molecular Dynamics and a knowledge-based potential, for the prediction of structural stability of short peptides (< 20 residues) in solution.

RESULTS

We tested the new approach on four families of short beta-hairpin peptides: TrpZip, MBH, bhpW and EPO, whose structural stabilities have been experimentally measured in previous studies. For all four families, both computational techniques show considerable correlation (r > 0.65) with the experimentally measured stabilities. The consensus of the two techniques shows higher correlation (r > 0.82).

CONCLUSION

Our results suggest a prediction scheme that can be used to estimate the relative structural stability within a peptide family. We discuss the applicability of this predictive approach for in-silico screening of combinatorial peptide libraries.

MESHI: a new library of Java classes for molecular modeling

Adapting a modular and object-oriented approach in the design of molecular modeling packages may reduce the software development barrier between ideas and their programed applications. Towards this goal we developed MESHI, a new, strictly object-oriented, molecular modeling suite written in Java. MESHI provides a comprehensive library of extendable classes for all the essential components of molecular modeling: molecular and geometry elements, energy functions and optimization methods.

AVAILABILITY

MESHI and its related documentation are freely available at http://www.cs.bgu.ac.il/~meshi; the MESHI API is available at http://www.cs.bgu.ac.il/~meshi/API CONTACT: keasar@cs.bgu.ac.il

SUPPLEMENTARY INFORMATION

The Supplementary information includes (1) a detailed description of several key packages and classes, and (2) a brief presentation of results achieved by using the MESHI application--Beautify--in the CASP6 experiment.

The neocortical microcircuit as a tabula rasa

The neocortex has a high capacity for plasticity. To understand the full scope of this capacity, it is essential to know how neurons choose particular partners to form synaptic connections. By using multineuron whole-cell recordings and confocal microscopy we found that axons of layer V neocortical pyramidal neurons do not preferentially project toward the dendrites of particular neighboring pyramidal neurons; instead, axons promiscuously touch all neighboring dendrites without any bias. Functional synaptic coupling of a small fraction of these neurons is, however, correlated with the existence of synaptic boutons at existing touch sites. These data provide the first direct experimental evidence for a tabula rasa-like structural matrix between neocortical pyramidal neurons and suggests that pre- and postsynaptic interactions shape the conversion between touches and synapses to form specific functional microcircuits. These data also indicate that the local neocortical microcircuit has the potential to be differently rewired without the need for remodeling axonal or dendritic arbors.

Deriving physical connectivity from neuronal morphology

A model is presented that allows prediction of the probability for the formation of appositions between the axons and dendrites of any two neurons based only on their morphological statistics and relative separation. Statistics of axonal and dendritic morphologies of single neurons are obtained from 3D reconstructions of biocytin-filled cells, and a statistical representation of the same cell type is obtained by averaging across neurons according to the model. A simple mathematical formulation is applied to the axonal and dendritic statistical representations to yield the probability for close appositions. The model is validated by a mathematical proof and by comparison of predicted appositions made by layer 5 pyramidal neurons in the rat somatosensory cortex with real anatomical data. The model could be useful for studying microcircuit connectivity and for designing artificial neural networks.