PACSY, a relational database management system for protein structure and chemical shift analysis

Changes in Secondary Structure Upon Pr to Pfr Transition in Cyanobacterial Phytochrome Cph1 Detected by DNP NMR

Phytochromes perceive subtle changes in the light environment and convert them into biological signals by photoconversion between the red-light absorbing (Pr) and the far-red-absorbing (Pfr) states. In the primitive bacteriophytochromes this includes refolding of a tongue-like hairpin loop close to the chromophore, one strand of an antiparallel β-sheet being replaced by an α-helix. However, the strand sequence in the cyanobacterial phytochrome Cph1 is different from that of previously investigated bacteriophytochromes and has a higher β-sheet propensity. We confirm here the transition experimentally and estimate minimum helix length using dynamic nuclear polarisation (DNP) magic angle spinning NMR. Sample conditions were optimized for protein DNP NMR studies at high field, yielding Boltzmann enhancements ϵB of 19 at an NMR field of 18.801 T. Selective labelling of Trp, Ile, Arg, and Val residues with 13C and 15N enabled filtering for pairs of labelled amino acids by the 3D CANCOCA technique to identify signals of the motif 483Ile-Val-Arg485 (IVR) present in both sheet and helix. Those signals were assigned for the Pfr state of the protein. Based on the chemical shift pattern, we confirm for Cph1 the formation of a helix covering the IVR motif.

Rapid Quantification of Protein Secondary Structure Composition from a Single Unassigned 1D 13C Nuclear Magnetic Resonance Spectrum

The function of a protein is predicated upon its three-dimensional fold. Representing its complex structure as a series of repeating secondary structural elements is one of the most useful ways by which we study, characterize, and visualize a protein. Consequently, experimental methods that quantify the secondary structure content allow us to connect a protein's structure to its function. Here, we introduce an automated gradient descent-based method we refer to as secondary-structure distribution by NMR that allows for rapid quantification of the protein secondary structure composition of a protein from a single, 1D 13C NMR spectrum without chemical shift assignments. The analysis of nearly 900 proteins with known structure and chemical shifts demonstrates the capabilities of our approach. We show that these results rival alternative techniques such as FT-IR and circular dichroism that are commonly used to estimate secondary structure compositions. The resulting method requires only the primary sequence of the protein and its referenced 13C NMR spectrum. Each residue is modeled in an ensemble of secondary structures with percentage contributions from random coil, α-helix, and β-sheet secondary structures obtained by minimizing the difference between a simulated and experimental 1D 13C NMR spectrum. The capabilities of the method are demonstrated as applied to samples at natural abundance or enriched in 13C, acquired by either solution or solid-state NMR, and even on low magnetic field benchtop NMR spectrometers. This approach allows for rapid characterization of protein secondary structure across traditionally challenging to characterize states including liquid-liquid phase-separated, membrane-bound, or aggregated states.

An optimized relational database for querying structural patterns in proteins

A database is an essential component in almost any software system, and its creation involves more than just data modeling and schema design. It also includes query optimization and tuning. This paper focuses on a web system called GSP4PDB, which is used for searching structural patterns in proteins. The system utilizes a normalized relational database, which has proven to be inefficient even for simple queries. This article discusses the optimization of the GSP4PDB database by implementing two techniques: denormalization and indexing. The empirical evaluation described in the article shows that combining these techniques enhances the efficiency of the database when querying both real and artificial graph-based structural patterns.

Solid-state NMR studies of amyloids

Amyloids have special structural properties and are involved in many aspects of biological function. In particular, amyloids are the cause or hallmarks of a group of notorious and incurable neurodegenerative diseases. The extraordinary high molecular weight and aggregation states of amyloids have posed a challenge for researchers studying them. Solid-state NMR (SSNMR) has been extensively applied to study the structures and dynamics of amyloids for the past 20 or more years and brought us tremendous progress in understanding their structure and related diseases. These studies, at the same time, helped to push SSNMR technical developments in sensitivity and resolution. In this review, some interesting research studies and important technical developments are highlighted to give the reader an overview of the current state of this field.

The PROSCOOP10 Gene Encodes Two Extracellular Hydroxylated Peptides and Impacts Flowering Time in Arabidopsis

The Arabidopsis PROSCOOP genes belong to a family predicted to encode secreted pro-peptides, which undergo maturation steps to produce peptides named SCOOP. Some of them are involved in defence signalling through their perception by a receptor complex including MIK2, BAK1 and BKK1. Here, we focused on the PROSCOOP10 gene, which is highly and constitutively expressed in aerial organs. The MS/MS analyses of leaf apoplastic fluids allowed the identification of two distinct peptides (named SCOOP10#1 and SCOOP10#2) covering two different regions of PROSCOOP10. They both possess the canonical S-X-S family motif and have hydroxylated prolines. This identification in apoplastic fluids confirms the biological reality of SCOOP peptides for the first time. NMR and molecular dynamics studies showed that the SCOOP10 peptides, although largely unstructured in solution, tend to assume a hairpin-like fold, exposing the two serine residues previously identified as essential for the peptide activity. Furthermore, PROSCOOP10 mutations led to an early-flowering phenotype and increased expression of the floral integrators SOC1 and LEAFY, consistent with the de-regulated transcription of PROSCOOP10 in several other mutants displaying early- or late-flowering phenotypes. These results suggest a role for PROSCOOP10 in flowering time, highlighting the functional diversity within the PROSCOOP family.

Characterization of conformational heterogeneity via higher-dimensionality, proton-detected solid-state NMR

Site-specific heterogeneity of solid protein samples can be exploited as valuable information to answer biological questions ranging from thermodynamic properties determining fibril formation to protein folding and conformational stability upon stress. In particular, for proteins of increasing molecular weight, however, site-resolved assessment without residue-specific labeling is challenging using established methodology, which tends to rely on carbon-detected 2D correlations. Here we develop purely chemical-shift-based approaches for assessment of relative conformational heterogeneity that allows identification of each residue via four chemical-shift dimensions. High dimensionality diminishes the probability of peak overlap in the presence of multiple, heterogeneously broadened resonances. Utilizing backbone dihedral-angle reconstruction from individual contributions to the peak shape either via suitably adapted prediction routines or direct association with a relational database, the methods may in future studies afford assessment of site-specific heterogeneity of proteins without site-specific labeling.

ssPINE: Probabilistic Algorithm for Automated Chemical Shift Assignment of Solid-State NMR Data from Complex Protein Systems

The heightened dipolar interactions in solids render solid-state NMR (ssNMR) spectra more difficult to interpret than solution NMR spectra. On the other hand, ssNMR does not suffer from severe molecular weight limitations like solution NMR. In recent years, ssNMR has undergone rapid technological developments that have enabled structure-function studies of increasingly larger biomolecules, including membrane proteins. Current methodology includes stable isotope labeling schemes, non-uniform sampling with spectral reconstruction, faster magic angle spinning, and innovative pulse sequences that capture different types of interactions among spins. However, computational tools for the analysis of complex ssNMR data from membrane proteins and other challenging protein systems have lagged behind those for solution NMR. Before a structure can be determined, thousands of signals from individual types of multidimensional ssNMR spectra of samples, which may have differing isotopic composition, must be recognized, correlated, categorized, and eventually assigned to atoms in the chemical structure. To address these tedious steps, we have developed an automated algorithm for ssNMR spectra called "ssPINE". The ssPINE software accepts the sequence of the protein plus peak lists from a variety of ssNMR experiments as inputs and offers automated backbone and side-chain assignments. The alpha version of ssPINE, which we describe here, is freely available through a web submission form.

Solution structure and dynamics of the mitochondrial-targeted GTPase-activating protein (GAP) VopE by an integrated NMR/SAXS approach

The bacterial pathogen Vibrio cholerae use a type III secretion system to inject effector proteins into a host cell. Recently, a putative Toxic GTPase Activating Protein (ToxGAP) called Vibrio outer protein E (VopE) was identified as a T3SS substrate and virulence factor that affected host mitochondrial dynamics and immune response. However, biophysical and structural characterization has been absent. Here, we describe solution NMR structure of the putative GTPase-activating protein (GAP) domain (73-204) of VopE. Using size exclusion chromatography coupled with small-angle x-ray scattering and residual dipolar coupling data, we restrained the MD process to efficiently determine the overall fold and improve the quality of the output calculated structures. Comparing the structure of VopE with other ToxGAP's revealed a similar overall fold with several features unique to VopE. Specifically, the "Bulge 1," α1 helix, and noteworthy "backside linker" elements on the N-terminus are dissimilar to the other ToxGAP's. By using NMR relaxation dispersion experiments, we demonstrate that these regions undergo motions on a > 6 s-1 timescale. Based on the disposition of these mobile regions relative to the putative catalytic arginine residue, we hypothesize that the protein may undergo structural changes to bind cognate GTPases.

POKY software tools encapsulating assignment strategies for solution and solid-state protein NMR data

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New tools support efficient analysis of solution and solid-state NMR spectra of proteins.

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POKY integrates a powerful suite of software packages for automated assignments.

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The Versatile Assigner module validates assignments through probabilistic analysis.

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The operation of these tools is supported by on-line guidance.

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The performance of these tools is evaluated in reference to competing software.

NMR spectroscopy provides structural and functional information about biomolecules and their complexes. The complexity of these systems can make the NMR data difficult to interpret, particularly for newer users of NMR technology, who may have limited understanding of the tools available and how they are used. To alleviate this problem, we have created software based on standardized workflows for both solution and solid-state NMR spectroscopy of proteins. These tools assist with manual and automated peak picking and with chemical shift assignment and validation. They provide users with an optimized path through spectral analysis that can help them perform the necessary tasks more efficiently.

Real-time observation of structure and dynamics during the liquid-to-solid transition of FUS LC

A subset of the proteins found in pathological protein fibrils also exhibit tendencies for liquid-liquid phase separation (LLPS) both in vitro and in cells. The mechanisms underlying the connection between these phase transitions have been challenging to study due to the heterogeneous and dynamic nature of the states formed during the maturation of LLPS protein droplets into gels and solid aggregates. Here, we interrogate the liquid-to-solid transition of the low-complexity domain of the RNA-binding protein FUS (FUS LC), which has been shown to adopt LLPS, gel-like, and amyloid states. We employ magic-angle-spinning NMR spectroscopy, which has allowed us to follow these transitions in real time and with residue-specific resolution. We observe the development of β-sheet structure through the maturation process and show that the final state of FUS LC fibrils produced after LLPS is distinct from that grown from fibrillar seeds. We also apply our methodology to FUS LC G156E, a clinically relevant FUS mutant that exhibits accelerated fibrillization rates. We observe significant changes in dynamics during the transformation of the FUS LC G156E construct and begin to unravel the sequence specific contributions to this phenomenon with computational studies of the phase-separated state of FUS LC and FUS LC G156E.

Mapping temperature-dependent conformational change in the voltage-sensing domain of an engineered heat-activated K+ channel

Temperature-dependent regulation of ion channel activity is critical for a variety of physiological processes ranging from immune response to perception of noxious stimuli. Our understanding of the structural mechanisms that underlie temperature sensing remains limited, in part due to the difficulty of combining high-resolution structural analysis with temperature stimulus. Here, we use NMR to compare the temperature-dependent behavior of Shaker potassium channel voltage sensor domain (WT-VSD) to its engineered temperature sensitive (TS-VSD) variant. Further insight into the molecular basis for temperature-dependent behavior is obtained by analyzing the experimental results together with molecular dynamics simulations. Our studies reveal that the overall secondary structure of the engineered TS-VSD is identical to the wild-type channels except for local changes in backbone torsion angles near the site of substitution (V369S and F370S). Remarkably however, these structural differences result in increased hydration of the voltage-sensing arginines and the S4-S5 linker helix in the TS-VSD at higher temperatures, in contrast to the WT-VSD. These findings highlight how subtle differences in the primary structure can result in large-scale changes in solvation and thereby confer increased temperature-dependent activity beyond that predicted by linear summation of solvation energies of individual substituents.

Selective One-Dimensional 13C-13C Spin-Diffusion Solid-State Nuclear Magnetic Resonance Methods to Probe Spatial Arrangements in Biopolymers Including Plant Cell Walls, Peptides, and Spider Silk

Two-dimensional (2D) and 3D through-space ¹³C-¹³C homonuclear spin-diffusion techniques are powerful solid-state nuclear magnetic resonance (NMR) tools for extracting structural information from ¹³C-enriched biomolecules, but necessarily long acquisition times restrict their applications. In this work, we explore the broad utility and underutilized power of a chemical shift-selective one-dimensional (1D) version of a 2D ¹³C-¹³C spin-diffusion solid-state NMR technique. The method, which is called 1D dipolar-assisted rotational resonance (DARR) difference, is applied to a variety of biomaterials including lignocellulosic plant cell walls, microcrystalline peptide fMLF, and black widow dragline spider silk. 1D ¹³C-¹³C spin-diffusion methods described here apply in select cases in which the 1D ¹³C solid-state NMR spectrum displays chemical shift-resolved moieties. This is analogous to the selective 1D nuclear Overhauser effect spectroscopy (NOESY) experiment utilized in liquid-state NMR as a faster (1D instead of 2D) and often less ambiguous (direct sampling of the time domain data, coupled with increased signal averaging) alternative to 2D NOESY. Selective 1D ¹³C-¹³C spin-diffusion methods are more time-efficient than their 2D counterparts such as proton-driven spin diffusion (PDSD) and dipolar-assisted rotational resonance. The additional time gained enables measurements of ¹³C-¹³C spin-diffusion buildup curves and extraction of spin-diffusion time constants T_SD, yielding detailed structural information. Specifically, selective 1D DARR difference buildup curves applied to ¹³C-enriched hybrid poplar woody stems confirm strong spatial interaction between lignin and acetylated xylan polymers within poplar plant secondary cell walls, and an interpolymer distance of ∼0.45-0.5 nm was estimated. Additionally, Tyr/Gly long-range correlations were observed on isotopically enriched black widow spider dragline silks.

Characterization of the Pilotin-Secretin Complex from the Salmonella enterica Type III Secretion System Using Hybrid Structural Methods

The type III secretion system (T3SS) is a multi-membrane-spanning protein channel used by Gram-negative pathogenic bacteria to secrete effectors directly into the host cell cytoplasm. In the many species reliant on the T3SS for pathogenicity, proper assembly of the outer membrane secretin pore depends on a diverse family of lipoproteins called pilotins. We present structural and biochemical data on the Salmonella enterica pilotin InvH and the S domain of its cognate secretin InvG. Characterization of InvH by X-ray crystallography revealed a dimerized, α-helical pilotin. Size-exclusion-coupled multi-angle light scattering and small-angle X-ray scattering provide supporting evidence for the formation of an InvH homodimer in solution. Structures of the InvH-InvG heterodimeric complex determined by X-ray crystallography and NMR spectroscopy indicate a predominantly hydrophobic interface. Knowledge of the interaction between InvH and InvG brings us closer to understanding the mechanisms by which pilotins assemble the secretin pore.

PINE-SPARKY.2 for automated NMR-based protein structure research

Summary

Nuclear magnetic resonance (NMR) spectroscopy, along with X-ray crystallography and cryoelectron microscopy, is one of the three major tools that enable the determination of atomic-level structural models of biological macromolecules. Of these, NMR has the unique ability to follow important processes in solution, including conformational changes, internal dynamics and protein-ligand interactions. As a means for facilitating the handling and analysis of spectra involved in these types of NMR studies, we have developed PINE-SPARKY.2, a software package that integrates and automates discrete tasks that previously required interaction with separate software packages. The graphical user interface of PINE-SPARKY.2 simplifies chemical shift assignment and verification, automated detection of secondary structural elements, predictions of flexibility and hydrophobic cores, and calculation of three-dimensional structural models.

Availability and implementation

PINE-SPARKY.2 is available in the latest version of NMRFAM-SPARKY from the National Magnetic Resonance Facility at Madison (http://pine.nmrfam.wisc.edu/download_packages.html), the NMRbox Project (https://nmrbox.org) and to subscribers to the SBGrid (https://sbgrid.org). For a detailed description of the program, see http://www.nmrfam.wisc.edu/pine-sparky2.htm.

Contact

whlee@nmrfam.wisc.edu or markley@nmrfam.wisc.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

I-PINE web server: an integrative probabilistic NMR assignment system for proteins

Various methods for understanding the structural and dynamic properties of proteins rely on the analysis of their NMR chemical shifts. These methods require the initial assignment of NMR signals to particular atoms in the sequence of the protein, a step that can be very time-consuming. The probabilistic interaction network of evidence (PINE) algorithm for automated assignment of backbone and side chain chemical shifts utilizes a Bayesian probabilistic network model that analyzes sequence data and peak lists from multiple NMR experiments. PINE, which is one of the most popular and reliable automated chemical shift assignment algorithms, has been available to the protein NMR community for longer than a decade. We announce here a new web server version of PINE, called Integrative PINE (I-PINE), which supports more types of NMR experiments than PINE (including three-dimensional nuclear Overhauser enhancement and four-dimensional J-coupling experiments) along with more comprehensive visualization of chemical shift based analysis of protein structure and dynamics. The I-PINE server is freely accessible at http://i-pine.nmrfam.wisc.edu . Help pages and tutorial including browser capability are available at: http://i-pine.nmrfam.wisc.edu/instruction.html . Sample data that can be used for testing the web server are available at: http://i-pine.nmrfam.wisc.edu/examples.html .

Characterising side chains in large proteins by protonless 13C-detected NMR spectroscopy

Side chains cover protein surfaces and are fundamental to processes as diverse as substrate recognition, protein folding and enzyme catalysis. However, characterisation of side-chain motions has so far been restricted to small proteins and methyl-bearing side chains. Here we present a class of methods, based on ¹³C-detected NMR spectroscopy, to more generally quantify motions and interactions of side chains in medium-to-large proteins. A single, uniformly isotopically labelled sample is sufficient to characterise the side chains of six different amino acid types. Side-chain conformational dynamics on the millisecond time-scale can be quantified by incorporating chemical exchange saturation transfer (CEST) into the presented methods, whilst long-range ¹³C-¹³C scalar couplings reporting on nanosecond to millisecond motions can be quantified in proteins as large as 80 kDa. The presented class of methods promises characterisation of side-chain behaviour at a level that has so far been reserved for the protein backbone.

Analysis of side-chain motions by NMR has so far been restricted to small proteins and methyl-bearing side chains. Here, the authors present NMR methods based on ¹³C direct detection of highly deuterated protein samples that yield sharp and well-resolved signals and allow the characterisation of side-chain conformational dynamics of six different amino acid types in medium-to-large proteins.

Structural database resources for biological macromolecules

This Briefing reviews the widely used, currently active, up-to-date databases derived from the worldwide Protein Data Bank (PDB) to facilitate browsing, finding and exploring its entries. These databases contain visualization and analysis tools tailored to specific kinds of molecules and interactions, often including also complex metrics precomputed by experts or external programs, and connections to sequence and functional annotation databases. Importantly, updates of most of these databases involves steps of curation and error checks based on specific expertise about the subject molecules or interactions, and removal of sequence redundancy, both leading to better data sets for mining studies compared with the full list of raw PDB entries. The article presents the databases in groups such as those aimed to facilitate browsing through PDB entries, their molecules and their general information, those built to link protein structure with sequence and dynamics, those specific for transmembrane proteins, nucleic acids, interactions of biomacromolecules with each other and with small molecules or metal ions, and those concerning specific structural features or specific protein families. A few webservers directly connected to active databases, and a few databases that have been discontinued but would be important to have back, are also briefly commented on. Along the Briefing, sample cases where these databases have been used to aid structural studies or advance our knowledge about biological macromolecules are referenced. A few specific examples are also given where using these databases is easier and more informative than using raw PDB data.

The AUDANA algorithm for automated protein 3D structure determination from NMR NOE data

We introduce AUDANA (Automated Database-Assisted NOE Assignment), an algorithm for determining three-dimensional structures of proteins from NMR data that automates the assignment of 3D-NOE spectra, generates distance constraints, and conducts iterative high temperature molecular dynamics and simulated annealing. The protein sequence, chemical shift assignments, and NOE spectra are the only required inputs. Distance constraints generated automatically from ambiguously assigned NOE peaks are validated during the structure calculation against information from an enlarged version of the freely available PACSY database that incorporates information on protein structures deposited in the Protein Data Bank (PDB). This approach yields robust sets of distance constraints and 3D structures. We evaluated the performance of AUDANA with input data for 14 proteins ranging in size from 6 to 25 kDa that had 27-98 % sequence identity to proteins in the database. In all cases, the automatically calculated 3D structures passed stringent validation tests. Structures were determined with and without database support. In 9/14 cases, database support improved the agreement with manually determined structures in the PDB and in 11/14 cases, database support lowered the r.m.s.d. of the family of 20 structural models.

Publication of nuclear magnetic resonance experimental data with semantic web technology and the application thereof to biomedical research of proteins

Background

The nuclear magnetic resonance (NMR) spectroscopic data for biological macromolecules archived at the BioMagResBank (BMRB) provide a rich resource of biophysical information at atomic resolution. The NMR data archived in NMR-STAR ASCII format have been implemented in a relational database. However, it is still fairly difficult for users to retrieve data from the NMR-STAR files or the relational database in association with data from other biological databases.

Findings

To enhance the interoperability of the BMRB database, we present a full conversion of BMRB entries to two standard structured data formats, XML and RDF, as common open representations of the NMR-STAR data. Moreover, a SPARQL endpoint has been deployed. The described case study demonstrates that a simple query of the SPARQL endpoints of the BMRB, UniProt, and Online Mendelian Inheritance in Man (OMIM), can be used in NMR and structure-based analysis of proteins combined with information of single nucleotide polymorphisms (SNPs) and their phenotypes.

Conclusions

We have developed BMRB/XML and BMRB/RDF and demonstrate their use in performing a federated SPARQL query linking the BMRB to other databases through standard semantic web technologies. This will facilitate data exchange across diverse information resources.

Electronic supplementary material

The online version of this article (doi:10.1186/s13326-016-0057-1) contains supplementary material, which is available to authorized users.

Integrative NMR for biomolecular research

NMR spectroscopy is a powerful technique for determining structural and functional features of biomolecules in physiological solution as well as for observing their intermolecular interactions in real-time. However, complex steps associated with its practice have made the approach daunting for non-specialists. We introduce an NMR platform that makes biomolecular NMR spectroscopy much more accessible by integrating tools, databases, web services, and video tutorials that can be launched by simple installation of NMRFAM software packages or using a cross-platform virtual machine that can be run on any standard laptop or desktop computer. The software package can be downloaded freely from the NMRFAM software download page ( http://pine.nmrfam.wisc.edu/download_packages.html ), and detailed instructions are available from the Integrative NMR Video Tutorial page ( http://pine.nmrfam.wisc.edu/integrative.html ).

Conformationally selective multidimensional chemical shift ranges in proteins from a PACSY database purged using intrinsic quality criteria

We have determined refined multidimensional chemical shift ranges for intra-residue correlations ((13)C-(13)C, (15)N-(13)C, etc.) in proteins, which can be used to gain type-assignment and/or secondary-structure information from experimental NMR spectra. The chemical-shift ranges are the result of a statistical analysis of the PACSY database of >3000 proteins with 3D structures (1,200,207 (13)C chemical shifts and >3 million chemical shifts in total); these data were originally derived from the Biological Magnetic Resonance Data Bank. Using relatively simple non-parametric statistics to find peak maxima in the distributions of helix, sheet, coil and turn chemical shifts, and without the use of limited "hand-picked" data sets, we show that ~94% of the (13)C NMR data and almost all (15)N data are quite accurately referenced and assigned, with smaller standard deviations (0.2 and 0.8 ppm, respectively) than recognized previously. On the other hand, approximately 6% of the (13)C chemical shift data in the PACSY database are shown to be clearly misreferenced, mostly by ca. -2.4 ppm. The removal of the misreferenced data and other outliers by this purging by intrinsic quality criteria (PIQC) allows for reliable identification of secondary maxima in the two-dimensional chemical-shift distributions already pre-separated by secondary structure. We demonstrate that some of these correspond to specific regions in the Ramachandran plot, including left-handed helix dihedral angles, reflect unusual hydrogen bonding, or are due to the influence of a following proline residue. With appropriate smoothing, significantly more tightly defined chemical shift ranges are obtained for each amino acid type in the different secondary structures. These chemical shift ranges, which may be defined at any statistical threshold, can be used for amino-acid type assignment and secondary-structure analysis of chemical shifts from intra-residue cross peaks by inspection or by using a provided command-line Python script (PLUQin), which should be useful in protein structure determination. The refined chemical shift distributions are utilized in a simple quality test (SQAT) that should be applied to new protein NMR data before deposition in a databank, and they could benefit many other chemical-shift based tools.

Probabilistic validation of protein NMR chemical shift assignments

Data validation plays an important role in ensuring the reliability and reproducibility of studies. NMR investigations of the functional properties, dynamics, chemical kinetics, and structures of proteins depend critically on the correctness of chemical shift assignments. We present a novel probabilistic method named ARECA for validating chemical shift assignments that relies on the nuclear Overhauser effect data . ARECA has been evaluated through its application to 26 case studies and has been shown to be complementary to, and usually more reliable than, approaches based on chemical shift databases. ARECA is available online at http://areca.nmrfam.wisc.edu/.

NMRFAM-SPARKY: enhanced software for biomolecular NMR spectroscopy

SPARKY (Goddard and Kneller, SPARKY 3) remains the most popular software program for NMR data analysis, despite the fact that development of the package by its originators ceased in 2001. We have taken over the development of this package and describe NMRFAM-SPARKY, which implements new functions reflecting advances in the biomolecular NMR field. NMRFAM-SPARKY has been repackaged with current versions of Python and Tcl/Tk, which support new tools for NMR peak simulation and graphical assignment determination. These tools, along with chemical shift predictions from the PACSY database, greatly accelerate protein side chain assignments. NMRFAM-SPARKY supports automated data format interconversion for interfacing with a variety of web servers including, PECAN , PINE, TALOS-N, CS-Rosetta, SHIFTX2 and PONDEROSA-C/S.

AVAILABILITY AND IMPLEMENTATION

The software package, along with binary and source codes, if desired, can be downloaded freely from http://pine.nmrfam.wisc.edu/download_packages.html. Instruction manuals and video tutorials can be found at http://www.nmrfam.wisc.edu/nmrfam-sparky-distribution.htm.

CONTACT

whlee@nmrfam.wisc.edu or markley@nmrfam.wisc.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

pH-induced conformational change of IscU at low pH correlates with protonation/deprotonation of two conserved histidine residues

IscU, the scaffold protein for the major iron–sulfur cluster biosynthesis pathway in microorganisms and mitochondria (ISC pathway), plays important roles in the formation of [2Fe–2S] and [4Fe–4S] clusters and their delivery to acceptor apo-proteins. Our laboratory has shown that IscU populates two distinct, functionally relevant conformational states, a more structured state (S) and a more dynamic state (D), that differ by cis/trans isomerizations about two peptidyl-prolyl peptide bonds [Kim, J. H., Tonelli, M., and Markley, J. L. (2012) Proc. Natl. Acad. Sci. U.S.A., 109, 454–459. Dai Z., Tonelli, M., and Markley, J. L. (2012) Biochemistry, 51, 9595–9602. Cai, K., Frederick, R. O., Kim, J. H., Reinen, N. M., Tonelli, M., and Markley, J. L. (2013) J. Biol. Chem., 288, 28755–28770]. Here, we report our findings on the pH dependence of the D ⇄ S equilibrium for Escherichia coli IscU in which the D-state is stabilized at low and high pH values. We show that the lower limb of the pH dependence curve results from differences in the pK_a values of two conserved histidine residues (His10 and His105) in the two states. The net proton affinity of His10 is about 50 times higher and that of His105 is 13 times higher in the D-state than in the S-state. The origin of the high limb of the D ⇄ S pH dependence remains to be determined. These results show that changes in proton inventory need to be taken into account in the steps in iron–sulfur cluster assembly and transfer that involve transitions of IscU between its S- and D-states.

Resonance assignment of the NMR spectra of disordered proteins using a multi-objective non-dominated sorting genetic algorithm

A multi-objective genetic algorithm is introduced to predict the assignment of protein solid-state NMR (SSNMR) spectra with partial resonance overlap and missing peaks due to broad linewidths, molecular motion, and low sensitivity. This non-dominated sorting genetic algorithm II (NSGA-II) aims to identify all possible assignments that are consistent with the spectra and to compare the relative merit of these assignments. Our approach is modeled after the recently introduced Monte-Carlo simulated-annealing (MC/SA) protocol, with the key difference that NSGA-II simultaneously optimizes multiple assignment objectives instead of searching for possible assignments based on a single composite score. The multiple objectives include maximizing the number of consistently assigned peaks between multiple spectra ("good connections"), maximizing the number of used peaks, minimizing the number of inconsistently assigned peaks between spectra ("bad connections"), and minimizing the number of assigned peaks that have no matching peaks in the other spectra ("edges"). Using six SSNMR protein chemical shift datasets with varying levels of imperfection that was introduced by peak deletion, random chemical shift changes, and manual peak picking of spectra with moderately broad linewidths, we show that the NSGA-II algorithm produces a large number of valid and good assignments rapidly. For high-quality chemical shift peak lists, NSGA-II and MC/SA perform similarly well. However, when the peak lists contain many missing peaks that are uncorrelated between different spectra and have chemical shift deviations between spectra, the modified NSGA-II produces a larger number of valid solutions than MC/SA, and is more effective at distinguishing good from mediocre assignments by avoiding the hazard of suboptimal weighting factors for the various objectives. These two advantages, namely diversity and better evaluation, lead to a higher probability of predicting the correct assignment for a larger number of residues. On the other hand, when there are multiple equally good assignments that are significantly different from each other, the modified NSGA-II is less efficient than MC/SA in finding all the solutions. This problem is solved by a combined NSGA-II/MC algorithm, which appears to have the advantages of both NSGA-II and MC/SA. This combination algorithm is robust for the three most difficult chemical shift datasets examined here and is expected to give the highest-quality de novo assignment of challenging protein NMR spectra.

Conformational analysis of the full-length M2 protein of the influenza A virus using solid-state NMR

The influenza A M2 protein forms a proton channel for virus infection and mediates virus assembly and budding. While extensive structural information is known about the transmembrane helix and an adjacent amphipathic helix, the conformation of the N-terminal ectodomain and the C-terminal cytoplasmic tail remains largely unknown. Using two-dimensional (2D) magic-angle-spinning solid-state NMR, we have investigated the secondary structure and dynamics of full-length M2 (M2FL) and found them to depend on the membrane composition. In 2D (13)C DARR correlation spectra, 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC)-bound M2FL exhibits several peaks at β-sheet chemical shifts, which result from water-exposed extramembrane residues. In contrast, M2FL bound to cholesterol-containing membranes gives predominantly α-helical chemical shifts. Two-dimensional J-INADEQUATE spectra and variable-temperature (13)C spectra indicate that DMPC-bound M2FL is highly dynamic while the cholesterol-containing membranes significantly immobilize the protein at physiological temperature. Chemical-shift prediction for various secondary-structure models suggests that the β-strand is located at the N-terminus of the DMPC-bound protein, while the cytoplasmic domain is unstructured. This prediction is confirmed by the 2D DARR spectrum of the ectodomain-truncated M2(21-97), which no longer exhibits β-sheet chemical shifts in the DMPC-bound state. We propose that the M2 conformational change results from the influence of cholesterol, and the increased helicity of M2FL in cholesterol-rich membranes may be relevant for M2 interaction with the matrix protein M1 during virus assembly and budding. The successful determination of the β-strand location suggests that chemical-shift prediction is a promising approach for obtaining structural information of disordered proteins before resonance assignment.

Practical use of chemical shift databases for protein solid-state NMR: 2D chemical shift maps and amino-acid assignment with secondary-structure information

We introduce a Python-based program that utilizes the large database of (13)C and (15)N chemical shifts in the Biological Magnetic Resonance Bank to rapidly predict the amino acid type and secondary structure from correlated chemical shifts. The program, called PACSYlite Unified Query (PLUQ), is designed to help assign peaks obtained from 2D (13)C-(13)C, (15)N-(13)C, or 3D (15)N-(13)C-(13)C magic-angle-spinning correlation spectra. We show secondary-structure specific 2D (13)C-(13)C correlation maps of all twenty amino acids, constructed from a chemical shift database of 262,209 residues. The maps reveal interesting conformation-dependent chemical shift distributions and facilitate searching of correlation peaks during amino-acid type assignment. Based on these correlations, PLUQ outputs the most likely amino acid types and the associated secondary structures from inputs of experimental chemical shifts. We test the assignment accuracy using four high-quality protein structures. Based on only the Cα and Cβ chemical shifts, the highest-ranked PLUQ assignments were 40-60 % correct in both the amino-acid type and the secondary structure. For three input chemical shifts (CO-Cα-Cβ or N-Cα-Cβ), the first-ranked assignments were correct for 60 % of the residues, while within the top three predictions, the correct assignments were found for 80 % of the residues. PLUQ and the chemical shift maps are expected to be useful at the first stage of sequential assignment, for combination with automated sequential assignment programs, and for highly disordered proteins for which secondary structure analysis is the main goal of structure determination.