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Alternative gene splicing gives rise to N-methyl-D-aspartate (NMDA) receptor ion channels with defined functional properties and unique contributions to calcium signaling in a given chemical environment in the mammalian brain. Splice variants possessing the exon-5-encoded motif at the amino-terminal domain (ATD) of the GluN1 subunit are known to display robustly altered deactivation rates and pH sensitivity, but the underlying mechanism for this functional modification is largely unknown. Here, we show through cryoelectron microscopy (cryo-EM) that the presence of the exon 5 motif in GluN1 alters the local architecture of heterotetrameric GluN1-GluN2 NMDA receptors and creates contacts with the ligand-binding domains (LBDs) of the GluN1 and GluN2 subunits, which are absent in NMDA receptors lacking the exon 5 motif. The unique interactions established by the exon 5 motif are essential to the stability of the ATD/LBD and LBD/LBD interfaces that are critically involved in controlling proton sensitivity and deactivation.
Copyright © 2018 Elsevier Inc. All rights reserved.
BACKGROUND - Next-generation sequencing of individuals with genetic diseases often detects candidate rare variants in numerous genes, but determining which are causal remains challenging. We hypothesized that the spatial distribution of missense variants in protein structures contains information about function and pathogenicity that can help prioritize variants of unknown significance (VUS) and elucidate the structural mechanisms leading to disease.
RESULTS - To illustrate this approach in a clinical application, we analyzed 13 candidate missense variants in regulator of telomere elongation helicase 1 (RTEL1) identified in patients with Familial Interstitial Pneumonia (FIP). We curated pathogenic and neutral RTEL1 variants from the literature and public databases. We then used homology modeling to construct a 3D structural model of RTEL1 and mapped known variants into this structure. We next developed a pathogenicity prediction algorithm based on proximity to known disease causing and neutral variants and evaluated its performance with leave-one-out cross-validation. We further validated our predictions with segregation analyses, telomere lengths, and mutagenesis data from the homologous XPD protein. Our algorithm for classifying RTEL1 VUS based on spatial proximity to pathogenic and neutral variation accurately distinguished 7 known pathogenic from 29 neutral variants (ROC AUC = 0.85) in the N-terminal domains of RTEL1. Pathogenic proximity scores were also significantly correlated with effects on ATPase activity (Pearson r = -0.65, p = 0.0004) in XPD, a related helicase. Applying the algorithm to 13 VUS identified from sequencing of RTEL1 from patients predicted five out of six disease-segregating VUS to be pathogenic. We provide structural hypotheses regarding how these mutations may disrupt RTEL1 ATPase and helicase function.
CONCLUSIONS - Spatial analysis of missense variation accurately classified candidate VUS in RTEL1 and suggests how such variants cause disease. Incorporating spatial proximity analyses into other pathogenicity prediction tools may improve accuracy for other genes and genetic diseases.
Prediction of protein tertiary structures from amino acid sequence and understanding the mechanisms of how proteins fold, collectively known as "the protein folding problem," has been a grand challenge in molecular biology for over half a century. Theories have been developed that provide us with an unprecedented understanding of protein folding mechanisms. However, computational simulation of protein folding is still difficult, and prediction of protein tertiary structure from amino acid sequence is an unsolved problem. Progress toward a satisfying solution has been slow due to challenges in sampling the vast conformational space and deriving sufficiently accurate energy functions. Nevertheless, several techniques and algorithms have been adopted to overcome these challenges, and the last two decades have seen exciting advances in enhanced sampling algorithms, computational power and tertiary structure prediction methodologies. This review aims at summarizing these computational techniques, specifically conformational sampling algorithms and energy approximations that have been frequently used to study protein-folding mechanisms or to de novo predict protein tertiary structures. We hope that this review can serve as an overview on how the protein-folding problem can be studied computationally and, in cases where experimental approaches are prohibitive, help the researcher choose the most relevant computational approach for the problem at hand. We conclude with a summary of current challenges faced and an outlook on potential future directions.
One of the challenging problems in tertiary structure prediction of helical membrane proteins (HMPs) is the determination of rotation of α-helices around the helix normal. Incorrect prediction of helix rotations substantially disrupts native residue-residue contacts while inducing only a relatively small effect on the overall fold. We previously developed a method for predicting residue contact numbers (CNs), which measure the local packing density of residues within the protein tertiary structure. In this study, we tested the idea of incorporating predicted CNs as restraints to guide the sampling of helix rotation. For a benchmark set of 15 HMPs with simple to rather complicated folds, the average contact recovery (CR) of best-sampled models was improved for all targets, the likelihood of sampling models with CR greater than 20% was increased for 13 targets, and the average RMSD100 of best-sampled models was improved for 12 targets. This study demonstrated that explicit incorporation of CNs as restraints improves the prediction of helix-helix packing. Proteins 2017; 85:1212-1221. © 2017 Wiley Periodicals, Inc.
© 2017 Wiley Periodicals, Inc.
Antibodies capable of neutralizing divergent influenza A viruses could form the basis of a universal vaccine. Here, from subjects enrolled in an H5N1 DNA/MIV-prime-boost influenza vaccine trial, we sorted hemagglutinin cross-reactive memory B cells and identified three antibody classes, each capable of neutralizing diverse subtypes of group 1 and group 2 influenza A viruses. Co-crystal structures with hemagglutinin revealed that each class utilized characteristic germline genes and convergent sequence motifs to recognize overlapping epitopes in the hemagglutinin stem. All six analyzed subjects had sequences from at least one multidonor class, and-in half the subjects-multidonor-class sequences were recovered from >40% of cross-reactive B cells. By contrast, these multidonor-class sequences were rare in published antibody datasets. Vaccination with a divergent hemagglutinin can thus increase the frequency of B cells encoding broad influenza A-neutralizing antibodies. We propose the sequence signature-quantified prevalence of these B cells as a metric to guide universal influenza A immunization strategies.
Published by Elsevier Inc.
Ionotropic glutamate receptor (iGluR) family members are integrated into supramolecular complexes that modulate their location and function at excitatory synapses. However, a lack of structural information beyond isolated receptors or fragments thereof currently limits the mechanistic understanding of physiological iGluR signaling. Here, we report structural and functional analyses of the prototypical molecular bridge linking postsynaptic iGluR δ2 (GluD2) and presynaptic β-neurexin 1 (β-NRX1) via Cbln1, a C1q-like synaptic organizer. We show how Cbln1 hexamers "anchor" GluD2 amino-terminal domain dimers to monomeric β-NRX1. This arrangement promotes synaptogenesis and is essential for D: -serine-dependent GluD2 signaling in vivo, which underlies long-term depression of cerebellar parallel fiber-Purkinje cell (PF-PC) synapses and motor coordination in developing mice. These results lead to a model where protein and small-molecule ligands synergistically control synaptic iGluR function.
Copyright © 2016, American Association for the Advancement of Science.
1,N(6)-Ethenodeoxyadenosine (1,N(6)-ϵdA) is the major etheno lesion formed in the reaction of DNA with epoxides substituted with good leaving groups (e.g. vinyl chloride epoxide). This lesion is also formed endogenously in DNA from lipid oxidation. Recombinant human DNA polymerase η (hpol η) can replicate oligonucleotide templates containing 1,N(6)-ϵdA. In steady-state kinetic analysis, hpol η preferred to incorporate dATP and dGTP, compared with dTTP. Mass spectral analysis of incorporation products also showed preferred purine (A, G) incorporation and extensive -1 frameshifts, suggesting pairing of the inserted purine and slippage before further replication. Five x-ray crystal structures of hpol η ternary complexes were determined, three at the insertion and two at the extension stage. Two insertion complexes revealed incoming non-hydrolyzable dATP or dGTP analogs not pairing with but instead in a staggered configuration relative to 1,N(6)-ϵdA in the anti conformation, thus opposite the 5'-T in the template, explaining the proclivity for frameshift misincorporation. In another insertion complex, dTTP was positioned opposite 1,N(6)-ϵdA, and the adduct base was in the syn conformation, with formation of two hydrogen bonds. At the extension stage, with either an incorporated dA or dT opposite 1,N(6)-ϵdA and 2'-deoxythymidine-5'-[(α,β)-imido]triphosphate opposite the 5'-A, the 3'-terminal nucleoside of the primer was disordered, consistent with the tendency not to incorporate dTTP opposite 1,N(6)-ϵdA. Collectively, the results show a preference for purine pairing opposite 1,N(6)-ϵdA and for -1 frameshifts.
© 2016 by The American Society for Biochemistry and Molecular Biology, Inc.
Basement membranes are defining features of the cellular microenvironment; however, little is known regarding their assembly outside cells. We report that extracellular Cl(-) ions signal the assembly of collagen IV networks outside cells by triggering a conformational switch within collagen IV noncollagenous 1 (NC1) domains. Depletion of Cl(-) in cell culture perturbed collagen IV networks, disrupted matrix architecture, and repositioned basement membrane proteins. Phylogenetic evidence indicates this conformational switch is a fundamental mechanism of collagen IV network assembly throughout Metazoa. Using recombinant triple helical protomers, we prove that NC1 domains direct both protomer and network assembly and show in Drosophila that NC1 architecture is critical for incorporation into basement membranes. These discoveries provide an atomic-level understanding of the dynamic interactions between extracellular Cl(-) and collagen IV assembly outside cells, a critical step in the assembly and organization of basement membranes that enable tissue architecture and function. Moreover, this provides a mechanistic framework for understanding the molecular pathobiology of NC1 domains.
© 2016 Cummings et al.
Despite impressive successes in protein design, designing a well-folded protein of more 100 amino acids de novo remains a formidable challenge. Exploiting the promising biophysical features of the artificial protein Octarellin V, we improved this protein by directed evolution, thus creating a more stable and soluble protein: Octarellin V.1. Next, we obtained crystals of Octarellin V.1 in complex with crystallization chaperons and determined the tertiary structure. The experimental structure of Octarellin V.1 differs from its in silico design: the (αβα) sandwich architecture bears some resemblance to a Rossman-like fold instead of the intended TIM-barrel fold. This surprising result gave us a unique and attractive opportunity to test the state of the art in protein structure prediction, using this artificial protein free of any natural selection. We tested 13 automated webservers for protein structure prediction and found none of them to predict the actual structure. More than 50% of them predicted a TIM-barrel fold, i.e. the structure we set out to design more than 10years ago. In addition, local software runs that are human operated can sample a structure similar to the experimental one but fail in selecting it, suggesting that the scoring and ranking functions should be improved. We propose that artificial proteins could be used as tools to test the accuracy of protein structure prediction algorithms, because their lack of evolutionary pressure and unique sequences features.
Copyright © 2016 Elsevier Inc. All rights reserved.
In silico prediction of a protein's tertiary structure remains an unsolved problem. The community-wide Critical Assessment of Protein Structure Prediction (CASP) experiment provides a double-blind study to evaluate improvements in protein structure prediction algorithms. We developed a protein structure prediction pipeline employing a three-stage approach, consisting of low-resolution topology search, high-resolution refinement, and molecular dynamics simulation to predict the tertiary structure of proteins from the primary structure alone or including distance restraints either from predicted residue-residue contacts, nuclear magnetic resonance (NMR) nuclear overhauser effect (NOE) experiments, or mass spectroscopy (MS) cross-linking (XL) data. The protein structure prediction pipeline was evaluated in the CASP11 experiment on twenty regular protein targets as well as thirty-three 'assisted' protein targets, which also had distance restraints available. Although the low-resolution topology search module was able to sample models with a global distance test total score (GDT_TS) value greater than 30% for twelve out of twenty proteins, frequently it was not possible to select the most accurate models for refinement, resulting in a general decay of model quality over the course of the prediction pipeline. In this study, we provide a detailed overall analysis, study one target protein in more detail as it travels through the protein structure prediction pipeline, and evaluate the impact of limited experimental data.