Soluble TREM2 inhibits secondary nucleation of Aß fibrillization and enhances cellular uptake of fibrillar Aß.

Triggering receptor expressed on myeloid cells 2 (TREM2) is a single-pass transmembrane receptor of the immunoglobulin superfamily that is secreted in a soluble (sTREM2) form. Mutations in TREM2 have been linked to increased risk of Alzheimer's disease (AD). A prominent neuropathological component of AD is deposition of the amyloid-ß (Aß) into plaques, particularly Aß40 and Aß42. While the membrane-bound form of TREM2 is known to facilitate uptake of Aß fibrils and the polarization of microglial processes toward amyloid plaques, the role of its soluble ectodomain, particularly in interactions with monomeric or fibrillar Aß, has been less clear. Our results demonstrate that sTREM2 does not bind to monomeric Aß40 and Aß42, even at a high micromolar concentration, while it does bind to fibrillar Aß42 and Aß40 with equal affinities (2.6 ± 0.3 µM and 2.3 ± 0.4 µM). Kinetic analysis shows that sTREM2 inhibits the secondary nucleation step in the fibrillization of Aß, while having little effect on the primary nucleation pathway. Furthermore, binding of sTREM2 to fibrils markedly enhanced uptake of fibrils into human microglial and neuroglioma derived cell lines. The disease-associated sTREM2 mutant, R47H, displayed little to no effect on fibril nucleation and binding, but it decreased uptake and functional responses markedly. We also probed the structure of the WT sTREM2-Aß fibril complex using integrative molecular modeling based primarily on the cross-linking mass spectrometry data. The model shows that sTREM2 binds fibrils along one face of the structure, leaving a second, mutation-sensitive site free to mediate cellular binding and uptake.

Molecular modeling of biomolecules by paramagnetic NMR and computational hybrid methods.

The 3D atomic structures of biomolecules and their complexes are key to our understanding of biomolecular function, recognition, and mechanism. However, it is often difficult to obtain structures, particularly for systems that are complex, dynamic, disordered, or exist in environments like cell membranes. In such cases sparse data from a variety of paramagnetic NMR experiments offers one possible source of structural information. These restraints can be incorporated in computer modeling algorithms that can accurately translate the sparse experimental data into full 3D atomic structures. In this review, we discuss various types of paramagnetic NMR/computational hybrid modeling techniques that can be applied to successful modeling of not only the atomic structure of proteins but also their interacting partners. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman.

Sensitive NMR Approach for Determining the Binding Mode of Tightly Binding Ligand Molecules to Protein Targets.

Structure-guided drug design relies on detailed structural knowledge of protein-ligand complexes, but crystallization of cocomplexes is not always possible. Here we present a sensitive nuclear magnetic resonance (NMR) approach to determine the binding mode of tightly binding lead compounds in complex with difficult target proteins. In contrast to established NMR methods, it does not depend on rapid exchange between bound and free ligand or on stable isotope labeling, relying instead on a tert-butyl group as a chemical label. tert-Butyl groups are found in numerous protein ligands and deliver an exceptionally narrow and tall (1)H NMR signal. We show that a tert-butyl group also produces outstandingly intense intra- and intermolecular NOESY cross-peaks. These enable measurements of pseudocontact shifts generated by lanthanide tags attached to the protein, which in turn allows positioning of the ligand on the protein. Once the ligand has been located, assignments of intermolecular NOEs become possible even without prior resonance assignments of protein side chains. The approach is demonstrated with the dengue virus NS2B-NS3 protease in complex with a high-affinity ligand containing a tert-butyl group.

Magic angle spinning NMR structure determination of proteins from pseudocontact shifts.

Magic angle spinning solid-state NMR is a unique technique to study atomic-resolution structure of biomacromolecules which resist crystallization or are too large to study by solution NMR techniques. However, difficulties in obtaining sufficient number of long-range distance restraints using dipolar coupling based spectra hamper the process of structure determination of proteins in solid-state NMR. In this study it is shown that high-resolution structure of proteins in solid phase can be determined without the use of traditional dipolar-dipolar coupling based distance restraints by combining the measurements of pseudocontact shifts (PCSs) with Rosetta calculations. The PCSs were generated by chelating exogenous paramagnetic metal ions to a tag 4-mercaptomethyl-dipicolinic acid, which is covalently attached to different residue sites in a 56-residue immunoglobulin-binding domain of protein G (GB1). The long-range structural restraints with metal-nucleus distance of up to ∼20 Šare quantitatively extracted from experimentally observed PCSs, and these are in good agreement with the distances back-calculated using an X-ray structure model. Moreover, we demonstrate that using several paramagnetic ions with varied paramagnetic susceptibilities as well as the introduction of paramagnetic labels at different sites can dramatically increase the number of long-range restraints and cover different regions of the protein. The structure generated from solid-state NMR PCSs restraints combined with Rosetta calculations has 0.7 Šroot-mean-square deviation relative to X-ray structure.

SSEThread: Integrative threading of the DNA-PKcs sequence based on data from chemical cross-linking and hydrogen deuterium exchange.

X-ray crystallography and electron microscopy maps resolved to 3-8 Šare generally sufficient for tracing the path of the polypeptide chain in space, while often insufficient for unambiguously registering the sequence on the path (i.e., threading). Frequently, however, additional information is available from other biophysical experiments, physical principles, statistical analyses, and other prior models. Here, we formulate an integrative approach for sequence assignment to a partial backbone model as an optimization problem, which requires three main components: the representation of the system, the scoring function, and the optimization method. The method is implemented in the open source Integrative Modeling Platform (IMP) (https://integrativemodeling.org), allowing a number of different terms in the scoring function. We apply this method to localizing the sequence assignment within a 199-residue disordered region of three structured and sequence unassigned helices in the DNA-PKcs crystallographic structure, using chemical crosslinks, hydrogen deuterium exchange, and sequence connectivity. The resulting ensemble of threading models provides two major solutions, one of which suggests that the crucial ABCDE cluster of phosphorylation sites cannot undergo intra-molecular autophosphorylation without a conformational rearrangement. The ensemble of solutions embodies the most accurate and precise sequence threading given the available information.

Protein Structure Determination by Assembling Super-Secondary Structure Motifs Using Pseudocontact Shifts.

Computational and nuclear magnetic resonance hybrid approaches provide efficient tools for 3D structure determination of small proteins, but currently available algorithms struggle to perform with larger proteins. Here we demonstrate a new computational algorithm that assembles the 3D structure of a protein from its constituent super-secondary structural motifs (Smotifs) with the help of pseudocontact shift (PCS) restraints for backbone amide protons, where the PCSs are produced from different metal centers. The algorithm, DINGO-PCS (3D assembly of Individual Smotifs to Near-native Geometry as Orchestrated by PCSs), employs the PCSs to recognize, orient, and assemble the constituent Smotifs of the target protein without any other experimental data or computational force fields. Using a universal Smotif database, the DINGO-PCS algorithm exhaustively enumerates any given Smotif. We benchmarked the program against ten different protein targets ranging from 100 to 220 residues with different topologies. For nine of these targets, the method was able to identify near-native Smotifs.

3D Computational Modeling of Proteins Using Sparse Paramagnetic NMR Data.

Computational modeling of proteins using evolutionary or de novo approaches offers rapid structural characterization, but often suffers from low success rates in generating high quality models comparable to the accuracy of structures observed in X-ray crystallography or nuclear magnetic resonance (NMR) spectroscopy. A computational/experimental hybrid approach incorporating sparse experimental restraints in computational modeling algorithms drastically improves reliability and accuracy of 3D models. This chapter discusses the use of structural information obtained from various paramagnetic NMR measurements and demonstrates computational algorithms implementing pseudocontact shifts as restraints to determine the structure of proteins at atomic resolution.

Pseudocontact Shift-Driven Iterative Resampling for 3D Structure Determinations of Large Proteins.

Pseudocontact shifts (PCSs) induced by paramagnetic lanthanides produce pronounced effects in nuclear magnetic resonance spectra, which are easily measured and which deliver valuable long-range structure restraints. Even sparse PCS data greatly enhance the success rate of 3D (3-dimensional) structure predictions of proteins by the modeling program Rosetta. The present work extends this approach to 3D structures of larger proteins, comprising more than 200 residues, which are difficult to model by Rosetta without additional experimental restraints. The new algorithm improves the fragment assembly method of Rosetta by utilizing PCSs generated from paramagnetic lanthanide ions attached at four different sites as the only experimental restraints. The sparse PCS data are utilized at multiple stages, to identify native-like local structures, to rank the best structural models and to rebuild the fragment libraries. The fragment libraries are refined iteratively until convergence. The PCS-driven iterative resampling algorithm is strictly data dependent and shown to generate accurate models for a benchmark set of eight different proteins, ranging from 100 to 220 residues, using solely PCSs of backbone amide protons.

Capturing conformational States in proteins using sparse paramagnetic NMR data.

Capturing conformational changes in proteins or protein-protein complexes is a challenge for both experimentalists and computational biologists. Solution nuclear magnetic resonance (NMR) is unique in that it permits structural studies of proteins under greatly varying conditions, and thus allows us to monitor induced structural changes. Paramagnetic effects are increasingly used to study protein structures as they give ready access to rich structural information of orientation and long-range distance restraints from the NMR signals of backbone amides, and reliable methods have become available to tag proteins with paramagnetic metal ions site-specifically and at multiple sites. In this study, we show how sparse pseudocontact shift (PCS) data can be used to computationally model conformational states in a protein system, by first identifying core structural elements that are not affected by the environmental change, and then computationally completing the remaining structure based on experimental restraints from PCS. The approach is demonstrated on a 27 kDa two-domain NS2B-NS3 protease system of the dengue virus serotype 2, for which distinct closed and open conformational states have been observed in crystal structures. By changing the input PCS data, the observed conformational states in the dengue virus protease are reproduced without modifying the computational procedure. This data driven Rosetta protocol enables identification of conformational states of a protein system, which are otherwise difficult to obtain either experimentally or computationally.

Three-dimensional protein fold determination from backbone amide pseudocontact shifts generated by lanthanide tags at multiple sites.

Site-specific attachment of paramagnetic lanthanide ions to a protein generates pseudocontact shifts (PCS) in the nuclear magnetic resonance (NMR) spectra of the protein that are easily measured as changes in chemical shifts. By labeling the protein with lanthanide tags at four different sites, PCSs are observed for most amide protons and accurate information is obtained about their coordinates in three-dimensional space. The approach is demonstrated with the chaperone ERp29, for which large differences have been reported between X-ray and NMR structures of the C-terminal domain, ERp29-C. The results unambiguously show that the structure of rat ERp29-C in solution is similar to the crystal structure of human ERp29-C. PCSs of backbone amides were the only structural restraints required. Because these can be measured for more dilute protein solutions than other NMR restraints, the approach greatly widens the range of proteins amenable to structural studies in solution.