Solution NMR structures of immunoglobulin-like domains 7 and 12 from obscurin-like protein 1 contribute to the structural coverage of the Human Cancer Protein Interaction Network.

High-quality solution NMR structures of immunoglobulin-like domains 7 and 12 from human obscurin-like protein 1 were solved. The two domains share 30% sequence identity and their structures are, as expected, rather similar. The new structures contribute to structural coverage of human cancer associated proteins. Mutations of Arg 812 in domain 7 cause the rare 3-M syndrome, and this site is located in a surface area predicted to be involved in protein-protein interactions.

Assessment of template-based protein structure predictions in CASP10.

Template-based modeling (TBM) is a major component of the critical assessment of protein structure prediction (CASP). In CASP10, some 41,740 predicted models submitted by 150 predictor groups were assessed as TBM predictions. The accuracy of protein structure prediction was assessed by geometric comparison with experimental X-ray crystal and NMR structures using a composite score that included both global alignment metrics and distance-matrix-based metrics. These included GDT-HA and GDC-all global alignment scores, and the superimposition-independent LDDT distance-matrix-based score. In addition, a superimposition-independent RPF metric, similar to that described previously for comparing protein models against experimental NMR data, was used for comparing predicted protein structure models against experimental protein structures. To score well on all four of these metrics, models must feature accurate predictions of both backbone and side-chain conformations. Performance rankings were determined independently for server and the combined server plus human-curated predictor groups. Final rankings were made using paired head-to-head Student's t-test analysis of raw metric scores among the top 25 performing groups in each category.

The expanded FindCore method for identification of a core atom set for assessment of protein structure prediction.

Maximizing the scientific impact of NMR-based structure determination requires robust and statistically sound methods for assessing the precision of NMR-derived structures. In particular, a method to define a core atom set for calculating superimpositions and validating structure predictions is critical to the use of NMR-derived structures as targets in the CASP competition. FindCore (Snyder and Montelione, Proteins 2005;59:673-686) is a superimposition independent method for identifying a core atom set and partitioning that set into domains. However, as FindCore optimizes superimposition by sensitively excluding not-well-defined atoms, the FindCore core may not comprise all atoms suitable for use in certain applications of NMR structures, including the CASP assessment process. Adapting the FindCore approach to assess predicted models against experimental NMR structures in CASP10 required modification of the FindCore method. This paper describes conventions and a standard protocol to calculate an "Expanded FindCore" atom set suitable for validation and application in biological and biophysical contexts. A key application of the Expanded FindCore method is to identify a core set of atoms in the experimental NMR structure for which it makes sense to validate predicted protein structure models. We demonstrate the application of this Expanded FindCore method in characterizing well-defined regions of 18 NMR-derived CASP10 target structures. The Expanded FindCore protocol defines "expanded core atom sets" that match an expert's intuition of which parts of the structure are sufficiently well defined to use in assessing CASP model predictions. We also illustrate the impact of this analysis on the CASP GDT assessment scores.

Definition and classification of evaluation units for CASP10.

For the 10th experiment on Critical Assessment of the techniques of protein Structure Prediction (CASP), the prediction target proteins were broken into independent evaluation units (EUs), which were then classified into template-based modeling (TBM) or free modeling (FM) categories. We describe here how the EUs were defined and classified, what issues arose in the process, and how we resolved them. EUs are frequently not the whole target proteins but the constituting structural domains. However, the assessors from CASP7 on combined more than one domain into 1 EU for some targets, which implied that the assessment also included evaluation of the prediction of the relative position and orientation of these domains. In CASP10, we followed and expanded this notion by defining multidomain EUs for a number of targets. These included 3 EUs, each made of two domains of familiar fold but arranged in a novel manner and for which the focus of evaluation was the interdomain arrangement. An EU was classified to the TBM category if a template could be found by sequence similarity searches and to FM if a structural template could not be found by structural similarity searches. The EUs that did not fall cleanly in either of these cases were classified case-by-case, often including consideration of the overall quality and characteristics of the predictions.

Hidden Structural States of Proteins Revealed by Conformer Selection with AlphaFold-NMR.

Recent advances in molecular modeling using deep learning can revolutionize our understanding of dynamic protein structures. NMR is particularly well-suited for determining dynamic features of biomolecular structures. The conventional process for determining biomolecular structures from experimental NMR data involves its representation as conformation-dependent restraints, followed by generation of structural models guided by these spatial restraints. Here we describe an alternative approach: generating a distribution of realistic protein conformational models using artificial intelligence-(AI-) based methods and then selecting the sets of conformers that best explain the experimental data. We applied this conformational selection approach to redetermine the solution NMR structure of the enzyme Gaussia luciferase. First, we generated a diverse set of conformer models using AlphaFold2 (AF2) with an enhanced sampling protocol. The models that best-fit NOESY and chemical shift data were then selected with a Bayesian scoring metric. The resulting models include features of both the published NMR structure and the standard AF2 model generated without enhanced sampling. This "AlphaFold-NMR" protocol also generated an alternative "open" conformational state that fits nearly as well to the overall NMR data but accounts for some NOESY data that is not consistent with first "closed" conformational state; while other NOESY data consistent with this second state are not consistent with the first conformational state. The structure of this "open" structural state differs from that of the "closed" state primarily by the position of a thumb-shaped loop between α-helices H5 and H6, revealing a cryptic surface pocket. These alternative conformational states of Gluc are supported by "double recall" analysis of NOESY data and AF2 models. Additional structural states are also indicated by backbone chemical shift data indicating partially-disordered conformations for the C-terminal segment. Considered as a multistate ensemble, these multiple states of Gluc together fit the NOESY and chemical shift data better than the "restraint-based" NMR structure and provide novel insights into its structure-dynamic-function relationships. This study demonstrates the potential of AI-based modeling with enhanced sampling to generate conformational ensembles followed by conformer selection with experimental data as an alternative to conventional restraint satisfaction protocols for protein NMR structure determination.

The structure of vimentin linker 1 and rod 1B domains characterized by site-directed spin-labeling electron paramagnetic resonance (SDSL-EPR) and X-ray crystallography.

Despite the passage of ∼30 years since the complete primary sequence of the intermediate filament (IF) protein vimentin was reported, the structure remains unknown for both an individual protomer and the assembled filament. In this report, we present data describing the structure of vimentin linker 1 (L1) and rod 1B. Electron paramagnetic resonance spectra collected from samples bearing site-directed spin labels demonstrate that L1 is not a flexible segment between coiled-coils (CCs) but instead forms a rigid, tightly packed structure. An x-ray crystal structure of a construct containing L1 and rod 1B shows that it forms a tetramer comprising two equivalent parallel CC dimers that interact with one another in the form of a symmetrical anti-parallel dimer. Remarkably, the parallel CC dimers are themselves asymmetrical, which enables them to tetramerize rather than undergoing higher order oligomerization. This functionally vital asymmetry in the CC structure, encoded in the primary sequence of rod 1B, provides a striking example of evolutionary exploitation of the structural plasticity of proteins. EPR and crystallographic data consistently suggest that a very short region within L1 represents a minor local distortion in what is likely to be a continuous CC from the end of rod 1A through the entirety of rod 1B. The concordance of this structural model with previously published cross-linking and spectral data supports the conclusion that the crystallographic oligomer represents a native biological structure.

ATPase active-site electrostatic interactions control the global conformation of the 100 kDa SecA translocase.

SecA is an intensively studied mechanoenzyme that uses ATP hydrolysis to drive processive extrusion of secreted proteins through a protein-conducting channel in the cytoplasmic membrane of eubacteria. The ATPase motor of SecA is strongly homologous to that in DEAD-box RNA helicases. It remains unclear how local chemical events in its ATPase active site control the overall conformation of an ~100 kDa multidomain enzyme and drive protein transport. In this paper, we use biophysical methods to establish that a single electrostatic charge in the ATPase active site controls the global conformation of SecA. The enzyme undergoes an ATP-modulated endothermic conformational transition (ECT) believed to involve similar structural mechanics to the protein transport reaction. We have characterized the effects of an isosteric glutamate-to-glutamine mutation in the catalytic base, a mutation which mimics the immediate electrostatic consequences of ATP hydrolysis in the active site. Calorimetric studies demonstrate that this mutation facilitates the ECT in Escherichia coli SecA and triggers it completely in Bacillus subtilis SecA. Consistent with the substantial increase in entropy observed in the course of the ECT, hydrogen-deuterium exchange mass spectrometry demonstrates that it increases protein backbone dynamics in domain-domain interfaces at remote locations from the ATPase active site. The catalytic glutamate is one of ~250 charged amino acids in SecA, and yet neutralization of its side chain charge is sufficient to trigger a global order-disorder transition in this 100 kDa enzyme. The intricate network of structural interactions mediating this effect couples local electrostatic changes during ATP hydrolysis to global conformational and dynamic changes in SecA. This network forms the foundation of the allosteric mechanochemistry that efficiently harnesses the chemical energy stored in ATP to drive complex mechanical processes.

Solution NMR structure of the ribosomal protein RP-L35Ae from Pyrococcus furiosus.

The ribosome consists of small and large subunits each composed of dozens of proteins and RNA molecules. However, the functions of many of the individual protomers within the ribosome are still unknown. In this article, we describe the solution NMR structure of the ribosomal protein RP-L35Ae from the archaeon Pyrococcus furiosus. RP-L35Ae is buried within the large subunit of the ribosome and belongs to Pfam protein domain family PF01247, which is highly conserved in eukaryotes, present in a few archaeal genomes, but absent in bacteria. The protein adopts a six-stranded anti-parallel ß-barrel analogous to the "tRNA binding motif" fold. The structure of the P. furiosus RP-L35Ae presented in this article constitutes the first structural representative from this protein domain family.

Comparing classical pathways and modern networks: towards the development of an edge ontology.

Pathways are integral to systems biology. Their classical representation has proven useful but is inconsistent in the meaning assigned to each arrow (or edge) and inadvertently implies the isolation of one pathway from another. Conversely, modern high-throughput (HTP) experiments offer standardized networks that facilitate topological calculations. Combining these perspectives, classical pathways can be embedded within large-scale networks and thus demonstrate the crosstalk between them. As more diverse types of HTP data become available, both perspectives can be effectively merged, embedding pathways simultaneously in multiple networks. However, the original problem still remains - the current edge representation is inadequate to accurately convey all the information in pathways. Therefore, we suggest that a standardized and well-defined edge ontology is necessary and propose a prototype as a starting point for reaching this goal.

SpecDB: A relational database for archiving biomolecular NMR spectral data.

NMR is a valuable experimental tool in the structural biologist's toolkit to elucidate the structures, functions, and motions of biomolecules. The progress of machine learning, particularly in structural biology, reveals the critical importance of large, diverse, and reliable datasets in developing new methods and understanding in structural biology and science more broadly. Biomolecular NMR research groups produce large amounts of data, and there is renewed interest in organizing these data to train new, sophisticated machine learning architectures and to improve biomolecular NMR analysis pipelines. The foundational data type in NMR is the free-induction decay (FID). There are opportunities to build sophisticated machine learning methods to tackle long-standing problems in NMR data processing, resonance assignment, dynamics analysis, and structure determination using NMR FIDs. Our goal in this study is to provide a lightweight, broadly available tool for archiving FID data as it is generated at the spectrometer, and grow a new resource of FID data and associated metadata. This study presents a relational schema for storing and organizing the metadata items that describe an NMR sample and FID data, which we call Spectral Database (SpecDB). SpecDB is implemented in SQLite and includes a Python software library providing a command-line application to create, organize, query, backup, share, and maintain the database. This set of software tools and database schema allow users to store, organize, share, and learn from NMR time domain data. SpecDB is freely available under an open source license at https://github.rpi.edu/RPIBioinformatics/SpecDB.

Accurate automated protein NMR structure determination using unassigned NOESY data.

Conventional NMR structure determination requires nearly complete assignment of the cross peaks of a refined NOESY peak list. Depending on the size of the protein and quality of the spectral data, this can be a time-consuming manual process requiring several rounds of peak list refinement and structure determination. Programs such as Aria, CYANA, and AutoStructure can generate models using unassigned NOESY data but are very sensitive to the quality of the input peak lists and can converge to inaccurate structures if the signal-to-noise of the peak lists is low. Here, we show that models with high accuracy and reliability can be produced by combining the strengths of the high-resolution structure prediction program Rosetta with global measures of the agreement between structure models and experimental data. A first round of models generated using CS-Rosetta (Rosetta supplemented with backbone chemical shift information) are filtered on the basis of their goodness-of-fit with unassigned NOESY peak lists using the DP-score, and the best fitting models are subjected to high resolution refinement with the Rosetta rebuild-and-refine protocol. This hybrid approach uses both local backbone chemical shift and the unassigned NOESY data to direct Rosetta trajectories toward the native structure and produces more accurate models than AutoStructure/CYANA or CS-Rosetta alone, particularly when using raw unedited NOESY peak lists. We also show that when accurate manually refined NOESY peak lists are available, Rosetta refinement can consistently increase the accuracy of models generated using CYANA and AutoStructure.

A microscale protein NMR sample screening pipeline.

As part of efforts to develop improved methods for NMR protein sample preparation and structure determination, the Northeast Structural Genomics Consortium (NESG) has implemented an NMR screening pipeline for protein target selection, construct optimization, and buffer optimization, incorporating efficient microscale NMR screening of proteins using a micro-cryoprobe. The process is feasible because the newest generation probe requires only small amounts of protein, typically 30-200 microg in 8-35 microl volume. Extensive automation has been made possible by the combination of database tools, mechanization of key process steps, and the use of a micro-cryoprobe that gives excellent data while requiring little optimization and manual setup. In this perspective, we describe the overall process used by the NESG for screening NMR samples as part of a sample optimization process, assessing optimal construct design and solution conditions, as well as for determining protein rotational correlation times in order to assess protein oligomerization states. Database infrastructure has been developed to allow for flexible implementation of new screening protocols and harvesting of the resulting output. The NESG micro NMR screening pipeline has also been used for detergent screening of membrane proteins. Descriptions of the individual steps in the NESG NMR sample design, production, and screening pipeline are presented in the format of a standard operating procedure.

NMR and X-RAY structures of human E2-like ubiquitin-fold modifier conjugating enzyme 1 (UFC1) reveal structural and functional conservation in the metazoan UFM1-UBA5-UFC1 ubiquination pathway.

For cell regulation, E2-like ubiquitin-fold modifier conjugating enzyme 1 (Ufc1) is involved in the transfer of ubiquitin-fold modifier 1 (Ufm1), a ubiquitin like protein which is activated by E1-like enzyme Uba5, to various target proteins. Thereby, Ufc1 participates in the very recently discovered Ufm1-Uba5-Ufc1 ubiquination pathway which is found in metazoan organisms. The structure of human Ufc1 was solved by using both NMR spectroscopy and X-ray crystallography. The complementary insights obtained with the two techniques provided a unique basis for understanding the function of Ufc1 at atomic resolution. The Ufc1 structure consists of the catalytic core domain conserved in all E2-like enzymes and an additional N-terminal helix. The active site Cys(116), which forms a thio-ester bond with Ufm1, is located in a flexible loop that is highly solvent accessible. Based on the Ufc1 and Ufm1 NMR structures, a model could be derived for the Ufc1-Ufm1 complex in which the C-terminal Gly(83) of Ufm1 may well form the expected thio-ester with Cys(116), suggesting that Ufm1-Ufc1 functions as described for other E1-E2-E3 machineries. alpha-helix 1 of Ufc1 adopts different conformations in the crystal and in solution, suggesting that this helix plays a key role to mediate specificity.

Construct optimization for protein NMR structure analysis using amide hydrogen/deuterium exchange mass spectrometry.

Disordered or unstructured regions of proteins, while often very important biologically, can pose significant challenges for resonance assignment and three-dimensional structure determination of the ordered regions of proteins by NMR methods. In this article, we demonstrate the application of (1)H/(2)H exchange mass spectrometry (DXMS) for the rapid identification of disordered segments of proteins and design of protein constructs that are more suitable for structural analysis by NMR. In this benchmark study, DXMS is applied to five NMR protein targets chosen from the Northeast Structural Genomics project. These data were then used to design optimized constructs for three partially disordered proteins. Truncated proteins obtained by deletion of disordered N- and C-terminal tails were evaluated using (1)H-(15)N HSQC and (1)H-(15)N heteronuclear NOE NMR experiments to assess their structural integrity. These constructs provide significantly improved NMR spectra, with minimal structural perturbations to the ordered regions of the protein structure. As a representative example, we compare the solution structures of the full length and DXMS-based truncated construct for a 77-residue partially disordered DUF896 family protein YnzC from Bacillus subtilis, where deletion of the disordered residues (ca. 40% of the protein) does not affect the native structure. In addition, we demonstrate that throughput of the DXMS process can be increased by analyzing mixtures of up to four proteins without reducing the sequence coverage for each protein. Our results demonstrate that DXMS can serve as a central component of a process for optimizing protein constructs for NMR structure determination.

The solution structure of ribosomal protein S17E from Methanobacterium thermoautotrophicum: a structural homolog of the FF domain.

The ribosomal protein S17E from the archaeon Methanobacterium thermoautotrophicum is a component of the 30S ribosomal subunit. S17E is a 62-residue protein conserved in archaea and eukaryotes and has no counterparts in bacteria. Mammalian S17E is a phosphoprotein component of eukaryotic ribosomes. Archaeal S17E proteins range from 59 to 79 amino acids, and are about half the length of the eukaryotic homologs which have an additional C-terminal region. Here we report the three-dimensional solution structure of S17E. S17E folds into a small three-helix bundle strikingly similar to the FF domain of human HYPA/FBP11, a novel phosphopeptide-binding fold. S17E bears a conserved positively charged surface acting as a robust scaffold for molecular recognition. The structure of M. thermoautotrophicum S17E provides a template for homology modeling of eukaryotic S17E proteins in the family.

Solution NMR structure of the NlpC/P60 domain of lipoprotein Spr from Escherichia coli: structural evidence for a novel cysteine peptidase catalytic triad.

Escherichia coli Spr is a membrane-anchored cell wall hydrolase. The solution NMR structure of the C-terminal NlpC/P60 domain of E. coli Spr described here reveals that the protein adopts a papain-like alpha+beta fold and identifies a substrate-binding cleft featuring several highly conserved residues. The active site features a novel Cys-His-His catalytic triad that appears to be a unique structural signature of this cysteine peptidase family. Moreover, the relative orientation of these catalytic residues is similar to that observed in the analogous Ser-His-His triad, a variant of the classic Ser-His-Asp charge relay system, suggesting the convergent evolution of a catalytic mechanism in quite distinct peptidase families.

Solution structure of Archaeglobus fulgidis peptidyl-tRNA hydrolase (Pth2) provides evidence for an extensive conserved family of Pth2 enzymes in archea, bacteria, and eukaryotes.

The solution structure of protein AF2095 from the thermophilic archaea Archaeglobus fulgidis, a 123-residue (13.6-kDa) protein, has been determined by NMR methods. The structure of AF2095 is comprised of four alpha-helices and a mixed beta-sheet consisting of four parallel and anti-parallel beta-strands, where the alpha-helices sandwich the beta-sheet. Sequence and structural comparison of AF2095 with proteins from Homo sapiens, Methanocaldococcus jannaschii, and Sulfolobus solfataricus reveals that AF2095 is a peptidyl-tRNA hydrolase (Pth2). This structural comparison also identifies putative catalytic residues and a tRNA interaction region for AF2095. The structure of AF2095 is also similar to the structure of protein TA0108 from archaea Thermoplasma acidophilum, which is deposited in the Protein Data Bank but not functionally annotated. The NMR structure of AF2095 has been further leveraged to obtain good-quality structural models for 55 other proteins. Although earlier studies have proposed that the Pth2 protein family is restricted to archeal and eukaryotic organisms, the similarity of the AF2095 structure to human Pth2, the conservation of key active-site residues, and the good quality of the resulting homology models demonstrate a large family of homologous Pth2 proteins that are conserved in eukaryotic, archaeal, and bacterial organisms, providing novel insights in the evolution of the Pth and Pth2 enzyme families.