Backbone solution structures of proteins using residual dipolar couplings: application to a novel structural genomics target

Concurrent Identification and Characterization of Protein Structure and Continuous Internal Dynamics with REDCRAFT

Internal dynamics of proteins can play a critical role in the biological function of some proteins. Several well documented instances have been reported such as MBP, DHFR, hTS, DGCR8, and NSP1 of the SARS-CoV family of viruses. Despite the importance of internal dynamics of proteins, there currently are very few approaches that allow for meaningful separation of internal dynamics from structural aspects using experimental data. Here we present a computational approach named REDCRAFT that allows for concurrent characterization of protein structure and dynamics. Here, we have subjected DHFR (PDB-ID 1RX2), a 159-residue protein, to a fictitious, mixed mode model of internal dynamics. In this simulation, DHFR was segmented into 7 regions where 4 of the fragments were fixed with respect to each other, two regions underwent rigid-body dynamics, and one region experienced uncorrelated and melting event. The two dynamical and rigid-body segments experienced an average orientational modification of 7° and 12° respectively. Observable RDC data for backbone C′-N, N-HN, and C′-HN were generated from 102 uniformly sampled frames that described the molecular trajectory. The structure calculation of DHFR with REDCRAFT by using traditional Ramachandran restraint produced a structure with 29 Å of structural difference measured over the backbone atoms (bb-rmsd) over the entire length of the protein and an average bb-rmsd of more than 4.7 Å over each of the dynamical fragments. The same exercise repeated with context-specific dihedral restraints generated by PDBMine produced a structure with bb-rmsd of 21 Å over the entire length of the protein but with bb-rmsd of less than 3 Å over each of the fragments. Finally, utilization of the Dynamic Profile generated by REDCRAFT allowed for the identification of different dynamical regions of the protein and the recovery of individual fragments with bb-rmsd of less than 1 Å. Following the recovery of the fragments, our assembly procedure of domains (larger segments consisting of multiple fragments with a common dynamical profile) correctly assembled the four fragments that are rigid with respect to each other, categorized the two domains that underwent rigid-body dynamics, and identified one dynamical region for which no conserved structure could be defined. In conclusion, our approach was successful in identifying the dynamical domains, recovery of structure where it is meaningful, and relative assembly of the domains when possible.

REDCRAFT: A computational platform using residual dipolar coupling NMR data for determining structures of perdeuterated proteins in solution

Nuclear Magnetic Resonance (NMR) spectroscopy is one of the three primary experimental means of characterizing macromolecular structures, including protein structures. Structure determination by solution NMR spectroscopy has traditionally relied heavily on distance restraints derived from nuclear Overhauser effect (NOE) measurements. While structure determination of proteins from NOE-based restraints is well understood and broadly used, structure determination from Residual Dipolar Couplings (RDCs) is relatively less well developed. Here, we describe the new features of the protein structure modeling program REDCRAFT and focus on the new Adaptive Decimation (AD) feature. The AD plays a critical role in improving the robustness of REDCRAFT to missing or noisy data, while allowing structure determination of larger proteins from less data. In this report we demonstrate the successful application of REDCRAFT in structure determination of proteins ranging in size from 50 to 145 residues using experimentally collected data, and of larger proteins (145 to 573 residues) using simulated RDC data. In both cases, REDCRAFT uses only RDC data that can be collected from perdeuterated proteins. Finally, we compare the accuracy of structure determination from RDCs alone with traditional NOE-based methods for the structurally novel PF.2048.1 protein. The RDC-based structure of PF.2048.1 exhibited 1.0 Å BB-RMSD with respect to a high-quality NOE-based structure. Although optimal strategies would include using RDC data together with chemical shift, NOE, and other NMR data, these studies provide proof-of-principle for robust structure determination of largely-perdeuterated proteins from RDC data alone using REDCRAFT.

Residual Dipolar Couplings have the potential to improve the accuracy and reduce the time needed to characterize protein structures. In addition, RDC data have been demonstrated to concurrently elucidate structure of proteins, provide assignment of resonances, and characterize the internal dynamics of proteins. Given all the advantages associated with the study of proteins from RDC data, based on the statistics provided by the Protein Databank (PDB), surprisingly only 124 proteins (out of nearly 150,000 proteins) have utilized RDCs as part of their structure determination. Even a smaller subset of these proteins (approximately 7) have utilized RDCs as the primary source of data for structure determination. One key factor in the use of RDCs is the challenging computational and analytical aspects of this source of data. In this report, we demonstrate the success of the REDCRAFT software package in structure determination of proteins using RDC data that can be collected from small and large proteins in a routine fashion. REDCRAFT accomplishes the challenging task of structure determination from RDCs by introducing a unique search and optimization technique that is both robust and computationally tractable. Structure determination from routinely collectable RDC data using REDCRAFT can complement existing methods to provide faster and more accurate studies of larger and more complex protein structures by NMR spectroscopy in solution state.

Structure Calculation and Reconstruction of Discrete-State Dynamics from Residual Dipolar Couplings

Residual dipolar couplings (RDCs) acquired by nuclear magnetic resonance (NMR) spectroscopy are an indispensable source of information in investigation of molecular structures and dynamics. Here, we present a comprehensive strategy for structure calculation and reconstruction of discrete-state dynamics from RDC data that is based on the singular value decomposition (SVD) method of order tensor estimation. In addition to structure determination, we provide a mechanism of producing an ensemble of conformations for the dynamical regions of a protein from RDC data. The developed methodology has been tested on simulated RDC data with ±1 Hz of error from an 83 residue α protein (PDB ID 1A1Z ) and a 213 residue α/β protein DGCR8 (PDB ID 2YT4 ). In nearly all instances, our method reproduced the structure of the protein including the conformational ensemble to within less than 2 Å. On the basis of our investigations, arc motions with more than 30° of rotation are identified as internal dynamics and are reconstructed with sufficient accuracy. Furthermore, states with relative occupancies above 20% are consistently recognized and reconstructed successfully. Arc motions with a magnitude of 15° or relative occupancy of less than 10% are consistently unrecognizable as dynamical regions within the context of ±1 Hz of error.

Improvements to REDCRAFT: a software tool for simultaneous characterization of protein backbone structure and dynamics from residual dipolar couplings

Within the past two decades, there has been an increase in the acquisition of residual dipolar couplings (RDC) for investigations of biomolecular structures. Their use however is still not as widely adopted as the traditional methods of structure determination by NMR, despite their potential for extending the limits in studies that examine both the structure and dynamics of biomolecules. This is in part due to the difficulties associated with the analysis of this information-rich data type. The software analysis tool REDCRAFT was previously introduced to address some of these challenges. Here we describe and evaluate a number of additional features that have been incorporated in order to extend its computational and analytical capabilities. REDCRAFT's more traditional enhancements integrate a modified steric collision term, as well as structural refinement in the rotamer space. Other, non-traditional improvements include: the filtering of viable structures based on relative order tensor estimates, decimation of the conformational space based on structural similarity, and forward/reverse folding of proteins. Utilizing REDCRAFT's newest features we demonstrate de-novo folding of proteins 1D3Z and 1P7E to within less than 1.6 Å of the corresponding X-ray structures, using as many as four RDCs per residue and as little as two RDCs per residue, in two alignment media. We also show the successful folding of a structure to less than 1.6 Å of the X-ray structure using {C(i-1)-N(i), N(i)-H(i), and C(i-1)-H(i)} RDCs in one alignment medium, and only {N(i)-H(i)} in the second alignment medium (a set of data which can be collected on deuterated samples). The program is available for download from our website at http://ifestos.cse.sc.edu .

Dynafold: a dynamic programming approach to protein backbone structure determination from minimal sets of Residual Dipolar Couplings

Residual Dipolar Couplings (RDCs) are a source of NMR data that can provide a powerful set of constraints on the orientation of inter-nuclear vectors, and are quickly becoming a larger part of the experimental toolset for molecular biologists. However, few reliable protocols exist for the determination of protein backbone structures from small sets of RDCs. DynaFold is a new dynamic programming algorithm designed specifically for this task, using minimal sets of RDCs collected in multiple alignment media. DynaFold was first tested utilizing synthetic data generated for the N--H , C(α)--H(α), and C--N vectors of 1BRF, 1F53, 110M, and 3LAY proteins, with up to ±1 Hz error in three alignment media, and was able to produce structures with less than 1.9 Å of the original structures. DynaFold was then tested using experimental data, obtained from the Biological Magnetic Resonance Bank, for proteins PDBID:1P7E and 1D3Z using RDC data from two alignment media. This exercise yielded structures within 1.0 Å of their respective published structures in segments with high data density, and less than 1.9 Å over the entire protein. The same sets of RDC data were also used in comparisons with traditional methods for analysis of RDCs, which failed to match the accuracy of DynaFold's approach to structure determination.

Archaeal ubiquitin-like SAMP3 is isopeptide-linked to proteins via a UbaA-dependent mechanism

SAMP1 and SAMP2 are ubiquitin-like proteins that function as protein modifiers and are required for the production of sulfur-containing biomolecules in the archaeon Haloferax volcanii. Here we report a novel small archaeal modifier protein (named SAMP3) with a β-grasp fold and C-terminal diglycine motif characteristic of ubiquitin that is functional in protein conjugation in Hfx. volcanii. SAMP3 conjugates were dependent on the ubiquitin-activating E1 enzyme homolog of archaea (UbaA) for synthesis and were cleaved by the JAMM/MPN+ domain metalloprotease HvJAMM1. Twenty-three proteins (28 lysine residues) were found to be isopeptide-linked to the C-terminal carboxylate of SAMP3, and 331 proteins were reproducibly found associated with SAMP3 in a UbaA-dependent manner based on tandem mass spectrometry (MS/MS) analysis. The molybdopterin (MPT) synthase large subunit homolog MoaE, found samp3ylated at conserved active site lysine residues in MS/MS analysis, was also shown to be covalently bound to SAMP3 by immunoprecipitation and tandem affinity purifications. HvJAMM1 was demonstrated to catalyze the cleavage of SAMP3 from MoaE, suggesting a mechanism of controlling MPT synthase activity. The levels of samp3ylated proteins and samp3 transcripts were found to be increased by the addition of dimethyl sulfoxide to aerobically growing cells. Thus, we propose a model in which samp3ylation is covalent and reversible and controls the activity of enzymes such as MPT synthase. Sampylation of MPT synthase may govern the levels of molybdenum cofactor available and thus facilitate the scavenging of oxygen prior to the transition to respiration with molybdenum-cofactor-containing terminal reductases that use alternative electron acceptors such as dimethyl sulfoxide. Overall, our study of SAMP3 provides new insight into the diversity of functional ubiquitin-like protein modifiers and the network of ubiquitin-like protein targets in Archaea.

Protein structure validation and identification from unassigned residual dipolar coupling data using 2D-PDPA

More than 90% of protein structures submitted to the PDB each year are homologous to some previously characterized protein structure. The extensive resources that are required for structural characterization of proteins can be justified for the 10% of the novel structures, but not for the remaining 90%. This report presents the 2D-PDPA method, which utilizes unassigned residual dipolar coupling in order to address the economics of structure determination of routine proteins by reducing the data acquisition and processing time. 2D-PDPA has been demonstrated to successfully identify the correct structure of an array of proteins that range from 46 to 445 residues in size from a library of 619 decoy structures by using unassigned simulated RDC data. When using experimental data, 2D-PDPA successfully identified the correct NMR structures from the same library of decoy structures. In addition, the most homologous X-ray structure was also identified as the second best structural candidate. Finally, success of 2D-PDPA in identifying and evaluating the most appropriate structure from a set of computationally predicted structures in the case of a previously uncharacterized protein Pf2048.1 has been demonstrated. This protein exhibits less than 20% sequence identity to any protein with known structure and therefore presents a compelling and practical application of our proposed work.

Prokaryotic proteasomes: nanocompartments of degradation

Proteasomes are self-compartmentalized energy-dependent proteolytic machines found in Archaea, Actinobacteria species of bacteria and eukaryotes. Proteasomes consist of two separate protein complexes, the core particle that hydrolyzes peptide bonds and an AAA+ ATPase domain responsible for the binding, unfolding and translocation of protein substrates into the core particle for degradation. Similarly to eukaryotes, proteasomes play a central role in protein degradation and can be essential in Archaea. Core particles associate with and utilize a variety of ATPase complexes to carry out protein degradation in Archaea. In actinobacterial species, such as Mycobacterium tuberculosis, proteasome-mediated degradation is associated with pathogenesis and does not appear to be essential. Interestingly, both actinobacterial species and Archaea use small proteins to covalently modify proteins, prokaryotic ubiquitin-like proteins (Pup) in Actinobacteria and ubiquitin-like small archaeal modifier proteins (SAMP) in Archaea. These modifications may play a role in proteasome targeting similar to the ubiquitin-proteasome system in eukaryotes.

Ubiquitin-like proteins and their roles in archaea

This review highlights the finding that ubiquitin-like (Ubl) proteins of archaea (termed SAMPs) function not only as sulfur carriers but also as protein modifiers. UbaA (an E1 ubiquitin-activating enzyme homolog of archaea) is required for the SAMPs to be covalently attached to proteins. The SAMPs and UbaA are also needed to form sulfur-containing biomolecules (e.g., thiolated tRNA and molybdenum cofactor). These findings provide a new perspective on how Ubl proteins can serve as both sulfur carriers and protein modifiers in the absence of canonical E2 ubiquitin conjugating or E3 ubiquitin ligase enzyme homologs.

A novel strategy for NMR resonance assignment and protein structure determination

The quality of protein structures determined by nuclear magnetic resonance (NMR) spectroscopy is contingent on the number and quality of experimentally-derived resonance assignments, distance and angular restraints. Two key features of protein NMR data have posed challenges for the routine and automated structure determination of small to medium sized proteins; (1) spectral resolution - especially of crowded nuclear Overhauser effect spectroscopy (NOESY) spectra, and (2) the reliance on a continuous network of weak scalar couplings as part of most common assignment protocols. In order to facilitate NMR structure determination, we developed a semi-automated strategy that utilizes non-uniform sampling (NUS) and multidimensional decomposition (MDD) for optimal data collection and processing of selected, high resolution multidimensional NMR experiments, combined it with an ABACUS protocol for sequential and side chain resonance assignments, and streamlined this procedure to execute structure and refinement calculations in CYANA and CNS, respectively. Two graphical user interfaces (GUIs) were developed to facilitate efficient analysis and compilation of the data and to guide automated structure determination. This integrated method was implemented and refined on over 30 high quality structures of proteins ranging from 5.5 to 16.5 kDa in size.

Simultaneous structure and dynamics of a membrane protein using REDCRAFT: membrane-bound form of Pf1 coat protein

A strategy for simultaneous study of the structure and internal dynamics of a membrane protein is described using the REDCRAFT algorithm. The membrane-bound form of the Pf1 major coat protein (mbPf1) was used as an example. First, synthetic data is utilized to validate the simultaneous study of structure and dynamics with REDCRAFT using dihedral restraints and backbone N-H RDCs from two different alignments. Subsequently, the validated analysis is applied to experimental data and confirms that REDCRAFT produces meaningful structures from sparse RDC data. Furthermore, simulated data from a two-state jump motion is used to illustrate the necessity for simultaneous consideration of structure and dynamics. Disregarding internal dynamics during the course of structure determination is shown to produce an average-state that is not related to the two intermediate states. During the analysis of RDC data from the dynamic model, REDCRAFT appropriately identifies the region separating the static and dynamic domains of the protein. Finally, analysis of experimental data strongly suggests the existence of internal motion between the amphipathic and the transmembrane helices of the membrane-bound form of the protein. The ability to perform fragmented structure determination of each domain without a priori assumption of the order tensors allows an independent determination of the order tensors, which yields a more comprehensive description of protein structure and dynamics and is particularly relevant to the study of membrane proteins.

Calmodulin regulates Ca2+-sensing receptor-mediated Ca2+ signaling and its cell surface expression

The Ca(2+)-sensing receptor (CaSR) is a member of family C of the GPCRs responsible for sensing extracellular Ca(2+) ([Ca(2+)](o)) levels, maintaining extracellular Ca(2+) homeostasis, and transducing Ca(2+) signaling from the extracellular milieu to the intracellular environment. In the present study, we have demonstrated a Ca(2+)-dependent, stoichiometric interaction between CaM and a CaM-binding domain (CaMBD) located within the C terminus of CaSR (residues 871-898). Our studies suggest a wrapping around 1-14-like mode of interaction that involves global conformational changes in both lobes of CaM with concomitant formation of a helical structure in the CaMBD. More importantly, the Ca(2+)-dependent association between CaM and the C terminus of CaSR is critical for maintaining proper responsiveness of intracellular Ca(2+) responses to changes in extracellular Ca(2+) and regulating cell surface expression of the receptor.

Efficient and accurate estimation of relative order tensors from lambda-maps

The rapid increase in the availability of RDC data from multiple alignment media in recent years has necessitated the development of more sophisticated analyses that extract the RDC data's full information content. This article presents an analysis of the distribution of RDCs from two media (2D-RDC data), using the information obtained from a lambda-map. This article also introduces an efficient algorithm, which leverages these findings to extract the order tensors for each alignment medium using unassigned RDC data in the absence of any structural information. The results of applying this 2D-RDC analysis method to synthetic and experimental data are reported in this article. The relative order tensor estimates obtained from the 2D-RDC analysis are compared to order tensors obtained from the program REDCAT after using assignment and structural information. The final comparisons indicate that the relative order tensors estimated from the unassigned 2D-RDC method very closely match the results from methods that require assignment and structural information. The presented method is successful even in cases with small datasets. The results of analyzing experimental RDC data for the protein 1P7E are presented to demonstrate the potential of the presented work in accurately estimating the principal order parameters from RDC data that incompletely sample the RDC space. In addition to the new algorithm, a discussion of the uniqueness of the solutions is presented; no more than two clusters of distinct solutions have been shown to satisfy each lambda-map.

Estimation of relative order tensors, and reconstruction of vectors in space using unassigned RDC data and its application

Advances in NMR instrumentation and pulse sequence design have resulted in easier acquisition of Residual Dipolar Coupling (RDC) data. However, computational and theoretical analysis of this type of data has continued to challenge the international community of investigators because of their complexity and rich information content. Contemporary use of RDC data has required a-priori assignment, which significantly increases the overall cost of structural analysis. This article introduces a novel algorithm that utilizes unassigned RDC data acquired from multiple alignment media (nD-RDC, n3) for simultaneous extraction of the relative order tensor matrices and reconstruction of the interacting vectors in space. Estimation of the relative order tensors and reconstruction of the interacting vectors can be invaluable in a number of endeavors. An example application has been presented where the reconstructed vectors have been used to quantify the fitness of a template protein structure to the unknown protein structure. This work has other important direct applications such as verification of the novelty of an unknown protein and validation of the accuracy of an available protein structure model in drug design. More importantly, the presented work has the potential to bridge the gap between experimental and computational methods of structure determination.

Rapid classification of protein structure models using unassigned backbone RDCs and probability density profile analysis (PDPA)

A method of identifying the best structural model for a protein of unknown structure from a list of structural candidates using unassigned 15N1H residual dipolar coupling (RDC) data and probability density profile analysis (PDPA) is described. Ten candidate structures have been obtained for the structural genomics target protein PF2048.1 using ROBETTA. 15N1H residual dipolar couplings have been measured from NMR spectra of the protein in two alignment media and these data have been analyzed using PDPA to rank the models in terms of their ability to represent the actual structure. A number of advantages in using this method to characterize a protein structure become apparent. RDCs can easily and rapidly be acquired, and without the need for assignment, the cost and duration of data acquisition is greatly reduced. The approach is quite robust with respect to imprecise and missing data. In the case of PF2048.1, a 79 residue protein, only 58 and 55 of the total RDC data were observed. The method can accelerate structure determination at higher resolution using traditional NMR spectroscopy by providing a starting point for the addition of NOEs and other NMR structural data.

REDCRAFT: a tool for simultaneous characterization of protein backbone structure and motion from RDC data

REDCRAFT, a new open source software tool that accommodates the analysis of RDC data for simultaneous structure and dynamics characterization of proteins is presented in this article. Simultaneous consideration of structure and motion is believed to be necessary for accurate representation of the solution-state of a protein. REDCRAFT is designed to primarily utilize RDC data from multiple alignment media in two stages. During Stage-I, a list of possible torsion angles joining any two neighboring peptide planes is ranked based on their fitness to experimental constraints; in Stage-II, a dipeptide fragment is extended by addition of one peptide plane at a time. The algorithm adopted by REDCRAFT is very efficient and can produce a structure for an 80 residue protein within two hours on a typical desktop computer. REDCRAFT exhibits robustness with respect to noise and missing data. REDCRAFT describes the overall alignment of the molecule in the form of an order tensor matrix and is capable of identifying peptide fragments with internal dynamics. Identification of the location of internal motion will permit a more accurate structural representation. Experimental data from two proteins as well as simulated data are presented to illustrate the capabilities of REDCRAFT in both structure determination and identification of the dynamical regions.

The impact of extremophiles on structural genomics (and vice versa)

The advent of the complete genome sequences of various organisms in the mid-1990s raised the issue of how one could determine the function of hypothetical proteins. While insight might be obtained from a 3D structure, the chances of being able to predict such a structure is limited for the deduced amino acid sequence of any uncharacterized gene. A template for modeling is required, but there was only a low probability of finding a protein closely-related in sequence with an available structure. Thus, in the late 1990s, an international effort known as structural genomics (SG) was initiated, its primary goal to "fill sequence-structure space" by determining the 3D structures of representatives of all known protein families. This was to be achieved mainly by X-ray crystallography and it was estimated that at least 5,000 new structures would be required. While the proteins (genes) for SG have subsequently been derived from hundreds of different organisms, extremophiles and particularly thermophiles have been specifically targeted due to the increased stability and ease of handling of their proteins, relative to those from mesophiles. This review summarizes the significant impact that extremophiles and proteins derived from them have had on SG projects worldwide. To what extent SG has influenced the field of extremophile research is also discussed.