Structure calculation, refinement and validation using CcpNmr Analysis

CcpNmr Analysis provides a streamlined pipeline for both NMR chemical shift assignment and structure determination of biological macromolecules. In addition, it encompasses tools to analyse the many additional experiments that make NMR such a pivotal technique for research into complex biological questions. This report describes how CcpNmr Analysis can seamlessly link together all of the tasks in the NMR structure-determination process. It details each of the stages from generating NMR restraints [distance, dihedral,hydrogen bonds and residual dipolar couplings (RDCs)],exporting these to and subsequently re-importing them from structure-calculation software (such as the programs CYANA or ARIA) and analysing and validating the results obtained from the structure calculation to, ultimately, the streamlined deposition of the completed assignments and the refined ensemble of structures into the PDBe repository. Until recently, such solution-structure determination by NMR has been quite a laborious task, requiring multiple stages and programs. However, with the new enhancements to CcpNmr Analysis described here, this process is now much more intuitive and efficient and less error-prone

Inflammatory proteins in plasma are associated with severity of Alzheimer's disease.

Published onlineComparative StudyResearch Support, Non-U.S. Gov'tThis is a freely-available open access publication. Please cite the published version which is available via the DOI link in this record.Markers of Alzheimer's disease (AD) are being widely sought with a number of studies suggesting blood measures of inflammatory proteins as putative biomarkers. Here we report findings from a panel of 27 cytokines and related proteins in over 350 subjects with AD, subjects with Mild Cognitive Impairment (MCI) and elderly normal controls where we also have measures of longitudinal change in cognition and baseline neuroimaging measures of atrophy. In this study, we identify five inflammatory proteins associated with evidence of atrophy on MR imaging data particularly in whole brain, ventricular and entorhinal cortex measures. In addition, we observed six analytes that showed significant change (over a period of one year) in people with fast cognitive decline compared to those with intermediate and slow decline. One of these (IL-10) was also associated with brain atrophy in AD. In conclusion, IL-10 was associated with both clinical and imaging evidence of severity of disease and might therefore have potential to act as biomarker of disease progression.National Institute for Health Research (NIHR) Mental Health Biomedical Research Centre and Dementia Biomedical Research Unit at South London and Maudsley NHS Foundation Trust and King’s College LondonEuropean Union of the Sixth Framework progra

NMR structure of an acyl-carrier protein from Borrelia burgdorferi

The high-resolution NMR structure of the acyl-carrier protein from the pathogen B. burgdorferi determined to a r.m.s. deviation of 0.4 Å over the protein backbone is reported. The NMR structure was determined using multidimensional NMR spectroscopy and consists of four α-helices and two 310-helices. Structural comparison reveals that this protein is highly similar to the acyl-carrier protein from A. aeolicus

Determination of helix orientations in a flexible DNA by multi-frequency EPR spectroscopy

Post-print (lokagerð höfundar)Distance measurements are performed between a pair of spin labels attached to nucleic acids using Pulsed Electron–Electron Double Resonance (PELDOR, also called DEER) spectroscopy which is a complementary tool to other structure determination methods in structural biology. The rigid spin label Ç, when incorporated pairwise into two helical parts of a nucleic acid molecule, allows the determination of both the mutual orientation and the distance between those labels, since Ç moves rigidly with the helix to which it is attached. We have developed a two-step protocol to investigate the conformational flexibility of flexible nucleic acid molecules by multi-frequency PELDOR. In the first step, a library with a broad collection of conformers, which are in agreement with topological constraints, NMR restraints and distances derived from PELDOR, was created. In the second step, a weighted structural ensemble of these conformers was chosen, such that it fits the multi-frequency PELDOR time traces of all doubly Ç-labelled samples simultaneously. This ensemble reflects the global structure and the conformational flexibility of the two-way DNA junction. We demonstrate this approach on a flexible bent DNA molecule, consisting of two short helical parts with a five adenine bulge at the center. The kink and twist motions between both helical parts were quantitatively determined and showed high flexibility, in agreement with a Förster Resonance Energy Transfer (FRET) study on a similar bent DNA motif. The approach presented here should be useful to describe the relative orientation of helical motifs and the conformational flexibility of nucleic acid structures, both alone and in complexes with proteins and other molecules.This work was supported by the SFB 902 Molecular Principles of RNA-based Regulation. C. M. G. gratefully acknowledges support by the Fonds der Chemischen Industrie. P. G. gratefully acknowledges financial support by a Grant-in-Aid for Scientific Research of the Japan Society for the Promotion of Science (JSPS), and a Eurostars grant by the Swiss Confederation. S. Th. S. gratefully acknowledges financial support from the Icelandic Research Fund (173727). We gratefully acknowledge Friedrich A. Gollmick (Friedrich-Schiller-University, Jena, Germany) for providing the original NMR data. We thank Burkhard Endeward, Vasyl Denysenkov and Dmitry Akhmetzyanov for support in carrying out the experiments and helpful discussions.Peer reviewe

Efficient determination of the accessible conformation space of multi-domain complexes based on EPR PELDOR data

Many proteins can adopt multiple conformations which are important for their function. This is also true for proteins and domains that are covalently linked to each other. One important example is ubiquitin, which can form chains of different conformations depending on which of its lysine side chains is used to form an isopeptide bond with the C-terminus of another ubiquitin molecule. Similarly, ubiquitin gets covalently attached to active-site residues of E2 ubiquitin-conjugating enzymes. Due to weak interactions between ubiquitin and its interaction partners, these covalent complexes adopt multiple conformations. Understanding the function of these complexes requires the characterization of the entire accessible conformation space and its modulation by interaction partners. Long-range (1.8-10 nm) distance restraints obtained by EPR spectroscopy in the form of probability distributions are ideally suited for this task as not only the mean distance but also information about the conformation dynamics is encoded in the experimental data. Here we describe a computational method that we have developed based on well-established structure determination software using NMR restraints to calculate the accessible conformation space using PELDOR/DEER data

Farseer-NMR: automatic treatment, analysis and plotting of large, multi-variable NMR data

We present Farseer-NMR (https://git.io/vAueU), a software package to treat, evaluate and combine NMR spectroscopic data from sets of protein-derived peaklists covering a range of experimental conditions. The combined advances in NMR and molecular biology enable the study of complex biomolecular systems such as flexible proteins or large multibody complexes, which display a strong and functionally relevant response to their environmental conditions, e.g. the presence of ligands, site-directed mutations, post translational modifications, molecular crowders or the chemical composition of the solution. These advances have created a growing need to analyse those systems’ responses to multiple variables. The combined analysis of NMR peaklists from large and multivariable datasets has become a new bottleneck in the NMR analysis pipeline, whereby information-rich NMR-derived parameters have to be manually generated, which can be tedious, repetitive and prone to human error, or even unfeasible for very large datasets. There is a persistent gap in the development and distribution of software focused on peaklist treatment, analysis and representation, and specifically able to handle large multivariable datasets, which are becoming more commonplace. In this regard, Farseer-NMR aims to close this longstanding gap in the automated NMR user pipeline and, altogether, reduce the time burden of analysis of large sets of peaklists from days/weeks to seconds/minutes. We have implemented some of the most common, as well as new, routines for calculation of NMR parameters and several publication-quality plotting templates to improve NMR data representation. Farseer-NMR has been written entirely in Python and its modular code base enables facile extension

The eNMR platform for structural biology

The e-NMR project is a European cooperation initiative that aims at providing the bio-NMR user community with a software platform integrating and streamlining the computational approaches necessary for the analysis of bio-NMR data. The e-NMR platform is based on a Grid computational infrastructure. A main focus of the current implementation of the e-NMR platform is on streamlining structure determination protocols. Indeed, to facilitate the use of NMR spectroscopy in the life sciences, the eNMR consortium has set out to provide protocolized services through easy-to-use web interfaces, while still retaining sufficient flexibility to handle specific requests by expert users. Various programs relevant for structural biology applications are already available through the e-NMR portal, including HADDOCK, XPLOR-NIH, CYANA and csRosetta. The implementation of these services, and in particular the distribution of calculations to the GRID infrastructure, has required the development of specific tools. However, the GRID infrastructure is maintained completely transparent to the users. With more than 150 registered users, eNMR is currently the second largest European Virtual Organization in the life sciences

Robust, Integrated Computational Control of NMR Experiments to Achieve Optimal Assignment by ADAPT-NMR

ADAPT-NMR (Assignment-directed Data collection Algorithm utilizing a Probabilistic Toolkit in NMR) represents a groundbreaking prototype for automated protein structure determination by nuclear magnetic resonance (NMR) spectroscopy. With a [13C,15N]-labeled protein sample loaded into the NMR spectrometer, ADAPT-NMR delivers complete backbone resonance assignments and secondary structure in an optimal fashion without human intervention. ADAPT-NMR achieves this by implementing a strategy in which the goal of optimal assignment in each step determines the subsequent step by analyzing the current sum of available data. ADAPT-NMR is the first iterative and fully automated approach designed specifically for the optimal assignment of proteins with fast data collection as a byproduct of this goal. ADAPT-NMR evaluates the current spectral information, and uses a goal-directed objective function to select the optimal next data collection step(s) and then directs the NMR spectrometer to collect the selected data set. ADAPT-NMR extracts peak positions from the newly collected data and uses this information in updating the analysis resonance assignments and secondary structure. The goal-directed objective function then defines the next data collection step. The procedure continues until the collected data support comprehensive peak identification, resonance assignments at the desired level of completeness, and protein secondary structure. We present test cases in which ADAPT-NMR achieved results in two days or less that would have taken two months or more by manual approaches

Robust structure-based resonance assignment for functional protein studies by NMR

High-throughput functional protein NMR studies, like protein interactions or dynamics, require an automated approach for the assignment of the protein backbone. With the availability of a growing number of protein 3D structures, a new class of automated approaches, called structure-based assignment, has been developed quite recently. Structure-based approaches use primarily NMR input data that are not based on J-coupling and for which connections between residues are not limited by through bonds magnetization transfer efficiency. We present here a robust structure-based assignment approach using mainly HN–HN NOEs networks, as well as 1H–15N residual dipolar couplings and chemical shifts. The NOEnet complete search algorithm is robust against assignment errors, even for sparse input data. Instead of a unique and partly erroneous assignment solution, an optimal assignment ensemble with an accuracy equal or near to 100% is given by NOEnet. We show that even low precision assignment ensembles give enough information for functional studies, like modeling of protein-complexes. Finally, the combination of NOEnet with a low number of ambiguous J-coupling sequential connectivities yields a high precision assignment ensemble. NOEnet will be available under: http://www.icsn.cnrs-gif.fr/download/nmr

Structural mechanism of JH delivery in hemolymph by JHBP of silkworm, Bombyx mori

Juvenile hormone (JH) plays crucial roles in many aspects of the insect life. All the JH actions are initiated by transport of JH in the hemolymph as a complex with JH-binding protein (JHBP) to target tissues. Here, we report structural mechanism of JH delivery by JHBP based upon the crystal and solution structures of apo and JH-bound JHBP. In solution, apo-JHBP exists in equilibrium of multiple conformations with different orientations of the gate helix for the hormone-binding pocket ranging from closed to open forms. JH-binding to the gate-open form results in the fully closed JHBP-JH complex structure where the bound JH is completely buried inside the protein. JH-bound JHBP opens the gate helix to release the bound hormone likely by sensing the less polar environment at the membrane surface of target cells. This is the first report that provides structural insight into JH signaling