Solution NMR structure of the 30S ribosomal protein S28E from Pyrococcus horikoshii

Sequence, structure and evolutionary analysis of cold shock domain proteins, a member of OB fold family

The cold shock domain (CSD) belongs to the oligosaccharide/oligonucleotide-binding fold superfamily which is highly conserved from prokaryotes to higher eukaryotes, and appears to function as RNA chaperones. CSD is involved in diverse cellular processes, including adaptation to low temperatures, nutrient stress, cellular growth and developmental processes. Structural Classification of Proteins (SCOP) database broadly classifies OB fold proteins into 18 different superfamilies, including nucleic acid-binding superfamily (NAB). The NAB is further divided into 17 families together with cold shock DNA-binding protein family (CSDB). The CSDB have more than 240 000 sequences in UniProt database consisting of 32 domains including CSD. Among these domains, CSD is the second largest sequence contributor (> 40 398 sequences). Herein, we have systematically analysed the relative abundance and distribution of CSD proteins based on sequences, structures, repeats and gene ontology (GO) molecular functions in all domains of life. Analysis of sequence distribution suggesting that CSDs are largely found in bacteria (83-94%) with single CSD repeat. However, repeat distribution in eukaryota varies from 1 to 5 in combination with other auxiliary domain that makes CSD proteins functionally more diverse compared to the bacterial counterparts. Further, analysis of repeats distributions on evolutionary scale suggest that existence of CSD in multiple repeats is mainly driven through speciation, gene shuffling and gene duplication events.

Automatic 13C chemical shift reference correction for unassigned protein NMR spectra

Poor chemical shift referencing, especially for ¹³C in protein Nuclear Magnetic Resonance (NMR) experiments, fundamentally limits and even prevents effective study of biomacromolecules via NMR, including protein structure determination and analysis of protein dynamics. To solve this problem, we constructed a Bayesian probabilistic framework that circumvents the limitations of previous reference correction methods that required protein resonance assignment and/or three-dimensional protein structure. Our algorithm named Bayesian Model Optimized Reference Correction (BaMORC) can detect and correct ¹³C chemical shift referencing errors before the protein resonance assignment step of analysis and without three-dimensional structure. By combining the BaMORC methodology with a new intra-peaklist grouping algorithm, we created a combined method called Unassigned BaMORC that utilizes only unassigned experimental peak lists and the amino acid sequence. Unassigned BaMORC kept all experimental three-dimensional HN(CO)CACB-type peak lists tested within ± 0.4 ppm of the correct ¹³C reference value. On a much larger unassigned chemical shift test set, the base method kept ¹³C chemical shift referencing errors to within ± 0.45 ppm at a 90% confidence interval. With chemical shift assignments, Assigned BaMORC can detect and correct ¹³C chemical shift referencing errors to within ± 0.22 at a 90% confidence interval. Therefore, Unassigned BaMORC can correct ¹³C chemical shift referencing errors when it will have the most impact, right before protein resonance assignment and other downstream analyses are started. After assignment, chemical shift reference correction can be further refined with Assigned BaMORC. These new methods will allow non-NMR experts to detect and correct ¹³C referencing error at critical early data analysis steps, lowering the bar of NMR expertise required for effective protein NMR analysis.

Detecting and accounting for multiple sources of positional variance in peak list registration analysis and spin system grouping

Peak lists derived from nuclear magnetic resonance (NMR) spectra are commonly used as input data for a variety of computer assisted and automated analyses. These include automated protein resonance assignment and protein structure calculation software tools. Prior to these analyses, peak lists must be aligned to each other and sets of related peaks must be grouped based on common chemical shift dimensions. Even when programs can perform peak grouping, they require the user to provide uniform match tolerances or use default values. However, peak grouping is further complicated by multiple sources of variance in peak position limiting the effectiveness of grouping methods that utilize uniform match tolerances. In addition, no method currently exists for deriving peak positional variances from single peak lists for grouping peaks into spin systems, i.e. spin system grouping within a single peak list. Therefore, we developed a complementary pair of peak list registration analysis and spin system grouping algorithms designed to overcome these limitations. We have implemented these algorithms into an approach that can identify multiple dimension-specific positional variances that exist in a single peak list and group peaks from a single peak list into spin systems. The resulting software tools generate a variety of useful statistics on both a single peak list and pairwise peak list alignment, especially for quality assessment of peak list datasets. We used a range of low and high quality experimental solution NMR and solid-state NMR peak lists to assess performance of our registration analysis and grouping algorithms. Analyses show that an algorithm using a single iteration and uniform match tolerances approach is only able to recover from 50 to 80% of the spin systems due to the presence of multiple sources of variance. Our algorithm recovers additional spin systems by reevaluating match tolerances in multiple iterations. To facilitate evaluation of the algorithms, we developed a peak list simulator within our nmrstarlib package that generates user-defined assigned peak lists from a given BMRB entry or database of entries. In addition, over 100,000 simulated peak lists with one or two sources of variance were generated to evaluate the performance and robustness of these new registration analysis and peak grouping algorithms.

Protein-protein and peptide-protein docking and refinement using ATTRACT in CAPRI

The ATTRACT coarse-grained docking approach in combination with various types of atomistic, flexible refinement methods has been applied to predict protein-protein and peptide-protein complexes in CAPRI rounds 28-36. For a large fraction of CAPRI targets (12 out of 18), at least one model of acceptable or better quality was generated, corresponding to a success rate of 67%. In particular, for several peptide-protein complexes excellent predictions were achieved. In several cases, a combination of template-based modeling and extensive molecular dynamics-based refinement yielded medium and even high quality solutions. In one particularly challenging case, the structure of an ubiquitylation enzyme bound to the nucleosome was correctly predicted as a set of acceptable quality solutions. Based on the experience with the CAPRI targets, new interface refinement approaches and methods for ab-initio peptide-protein docking have been developed. Failures and possible improvements of the docking method with respect to scoring and protein flexibility will also be discussed. Proteins 2017; 85:391-398. © 2016 Wiley Periodicals, Inc.

Identification of the Rps28 binding motif from yeast Edc3 involved in the autoregulatory feedback loop controlling RPS28B mRNA decay

In the yeast Saccharomyces cerevisiae, the Edc3 protein was previously reported to participate in the auto-regulatory feedback loop controlling the level of the RPS28B messenger RNA (mRNA). We show here that Edc3 binds directly and tightly to the globular core of Rps28 ribosomal protein. This binding occurs through a motif that is present exclusively in Edc3 proteins from yeast belonging to the Saccharomycetaceae phylum. Functional analyses indicate that the ability of Edc3 to interact with Rps28 is not required for its general function and for its role in the regulation of the YRA1 pre-mRNA decay. In contrast, this interaction appears to be exclusively required for the auto-regulatory mechanism controlling the RPS28B mRNA decay. These observations suggest a plausible model for the evolutionary appearance of a Rps28 binding motif in Edc3.

A creature with a hundred waggly tails: intrinsically disordered proteins in the ribosome

Intrinsic disorder (i.e., lack of a unique 3-D structure) is a common phenomenon, and many biologically active proteins are disordered as a whole, or contain long disordered regions. These intrinsically disordered proteins/regions constitute a significant part of all proteomes, and their functional repertoire is complementary to functions of ordered proteins. In fact, intrinsic disorder represents an important driving force for many specific functions. An illustrative example of such disorder-centric functional class is RNA-binding proteins. In this study, we present the results of comprehensive bioinformatics analyses of the abundance and roles of intrinsic disorder in 3,411 ribosomal proteins from 32 species. We show that many ribosomal proteins are intrinsically disordered or hybrid proteins that contain ordered and disordered domains. Predicted globular domains of many ribosomal proteins contain noticeable regions of intrinsic disorder. We also show that disorder in ribosomal proteins has different characteristics compared to other proteins that interact with RNA and DNA including overall abundance, evolutionary conservation, and involvement in protein-protein interactions. Furthermore, intrinsic disorder is not only abundant in the ribosomal proteins, but we demonstrate that it is absolutely necessary for their various functions.

A creature with a hundred waggly tails: intrinsically disordered proteins in the ribosome

Intrinsic disorder (i.e., lack of a unique 3-D structure) is a common phenomenon, and many biologically active proteins are disordered as a whole, or contain long disordered regions. These intrinsically disordered proteins/regions constitute a significant part of all proteomes, and their functional repertoire is complementary to functions of ordered proteins. In fact, intrinsic disorder represents an important driving force for many specific functions. An illustrative example of such disorder-centric functional class is RNA-binding proteins. In this study, we present the results of comprehensive bioinformatics analyses of the abundance and roles of intrinsic disorder in 3,411 ribosomal proteins from 32 species. We show that many ribosomal proteins are intrinsically disordered or hybrid proteins that contain ordered and disordered domains. Predicted globular domains of many ribosomal proteins contain noticeable regions of intrinsic disorder. We also show that disorder in ribosomal proteins has different characteristics compared to other proteins that interact with RNA and DNA including overall abundance, evolutionary conservation, and involvement in protein–protein interactions. Furthermore, intrinsic disorder is not only abundant in the ribosomal proteins, but we demonstrate that it is absolutely necessary for their various functions.

Relative stabilities of conserved and non-conserved structures in the OB-fold superfamily

The OB-fold is a diverse structure superfamily based on a beta-barrel motif that is often supplemented with additional non-conserved secondary structures. Previous deletion mutagenesis and NMR hydrogen exchange studies of three OB-fold proteins showed that the structural stabilities of sites within the conserved beta-barrels were larger than sites in non-conserved segments. In this work we examined a database of 80 representative domain structures currently classified as OB-folds, to establish the basis of this effect. Residue-specific values were obtained for the number of Calpha-Calpha distance contacts, sequence hydrophobicities, crystallographic B-factors, and theoretical B-factors calculated from a Gaussian Network Model. All four parameters point to a larger average flexibility for the non-conserved structures compared to the conserved beta-barrels. The theoretical B-factors and contact densities show the highest sensitivity. Our results suggest a model of protein structure evolution in which novel structural features develop at the periphery of conserved motifs. Core residues are more resistant to structural changes during evolution since their substitution would disrupt a larger number of interactions. Similar factors are likely to account for the differences in stability to unfolding between conserved and non-conserved structures.

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.

Acidic C-terminal tail of the ssDNA-binding protein of bacteriophage T7 and ssDNA compete for the same binding surface

ssDNA-binding proteins are key components of the machinery that mediates replication, recombination, and repair. Prokaryotic ssDNA-binding proteins share a conserved DNA-binding fold and an acidic C-terminal tail. It has been proposed that in the absence of ssDNA, the C-terminal tail contacts the ssDNA-binding cleft, therefore predicting that the binding of ssDNA and the C-terminal tail is mutually exclusive. Using chemical cross-linking, competition studies, and NMR chemical-shift mapping, we demonstrate that: (i) the C-terminal peptide of the gene 2.5 protein cross-links to the core of the protein only in the absence of ssDNA, (ii) the cross-linked species fails to bind to ssDNA, and (iii) a C-terminal peptide and ssDNA bind to the same overall surface of the protein. We propose that the protection of the DNA-binding cleft by the electrostatic shield of the C-terminal tail observed in prokaryotic ssDNA-binding proteins, ribosomal proteins, and high-mobility group proteins is an evolutionarily conserved mechanism. This mechanism prevents random binding of charged molecules to the nucleic acid-binding pocket and coordinates nucleic acid-protein and protein-protein interactions.

A topology-constrained distance network algorithm for protein structure determination from NOESY data

This article formulates the multidimensional nuclear Overhauser effect spectroscopy (NOESY) interpretation problem using graph theory and presents a novel, bottom-up, topology-constrained distance network analysis algorithm for NOESY cross peak interpretation using assigned resonances. AutoStructure is a software suite that implements this topology-constrained distance network analysis algorithm and iteratively generates structures using the three-dimensional (3D) protein structure calculation programs XPLOR/CNS or DYANA. The minimum input for AutoStructure includes the amino acid sequence, a list of resonance assignments, and lists of 2D, 3D, and/or 4D-NOESY cross peaks. AutoStructure can also analyze homodimeric proteins when X-filtered NOESY experiments are available. The quality of input data and final 3D structures is evaluated using recall, precision, and F-measure (RPF) scores, a statistical measure of goodness of fit with the input data. AutoStructure has been tested on three protein NMR data sets for which high-quality structures have previously been solved by an expert, and yields comparable high-quality distance constraint lists and 3D protein structures in hours. We also compare several protein structures determined using AutoStructure with corresponding homologous proteins determined with other independent methods. The program has been used in more than two dozen protein structure determinations, several of which have already been published.

Comparison of different torsion angle approaches for NMR structure determination

A new procedure for NMR structure determination, based on the Internal Coordinate Molecular Dynamics (ICMD) approach, is presented. The method finds biopolymer conformations that satisfy usual NMR-derived restraints by using high temperature dynamics in torsion angle space. A variable target function algorithm gradually increases the number of NOE-based restraints applied, with the treatment of ambiguous and floating restraints included. This soft procedure allows combining artificially high temperature with a general purpose force-field including Coulombic and Lennard-Jones non-bonded interactions, which improves the quality of the ensemble of conformations obtained in the gas-phase. The new method is compared to existing algorithms by using the structures of eight ribosomal proteins earlier obtained with state-of-the-art procedures and included into the RECOORD database [Nederveen, A., Doreleijers, J., Vranken, W., Miller, Z., Spronk, C., Nabuurs, S., Guntert, P., Livny, M., Markley, M., Nilges, M., Ulrich, E., Kaptein, R. and Bonvin, A.M. (2005) Proteins, 59, 662-672]. For the majority of tested proteins, the ICMD algorithm shows similar convergence and somewhat better quality Z scores for the phi, psi distributions. The new method is more computationally demanding although the overall load is reasonable.

AutoLink: automated sequential resonance assignment of biopolymers from NMR data by relative-hypothesis-prioritization-based simulated logic

We have developed a new computer algorithm for determining the backbone resonance assignments for biopolymers. The approach we have taken, relative hypothesis prioritization, is implemented as a Lua program interfaced to the recently developed computer-aided resonance assignment (CARA) program. Our program can work with virtually any spectrum type, and is especially good with NOESY data. The results of the program are displayed in an easy-to-read, color-coded, graphic representation, allowing users to assess the quality of the results in minutes. Here we report the application of the program to two RNA recognition motifs of Apobec-1 Complementation Factor. The assignment of these domains demonstrates AutoLink's ability to deliver accurate resonance assignments from very minimal data and with minimal user intervention.

An integrated platform for automated analysis of protein NMR structures

Recent developments provide automated analysis of NMR assignments and three-dimensional (3D) structures of proteins. These approaches are generally applicable to proteins ranging from about 50 to 150 amino acids. In this chapter, we summarize progress by the Northeast Structural Genomics Consortium in standardizing the NMR data collection process for protein structure determination and in building an integrated platform for automated protein NMR structure analysis. Our integrated platform includes the following principal steps: (1) standardized NMR data collection, (2) standardized data processing (including spectral referencing and Fourier transformation), (3) automated peak picking and peak list editing, (4) automated analysis of resonance assignments, (5) automated analysis of NOESY data together with 3D structure determination, and (6) methods for protein structure validation. In particular, the software AutoStructure for automated NOESY data analysis is described in this chapter, together with a discussion of practical considerations for its use in high-throughput structure production efforts. The critical area of data quality assessment has evolved significantly over the past few years and involves evaluation of both intermediate and final peak lists, resonance assignments, and structural information derived from the NMR data. Methods for quality control of each of the major automated analysis steps in our platform are also discussed. Despite significant remaining challenges, when good quality data are available, automated analysis of protein NMR assignments and structures with this platform is both fast and reliable.

Solution structure of ribosomal protein S28E from Methanobacterium thermoautotrophicum

The ribosomal protein S28E from the archaeon Methanobacterium thermoautotrophicum is a component of the 30S ribosomal subunit. Sequence homologs of S28E are found only in archaea and eukaryotes. Here we report the three-dimensional solution structure of S28E by NMR spectroscopy. S28E contains a globular region and a long C-terminal tail protruding from the core. The globular region consists of four antiparallel beta-strands that are arranged in a Greek-key topology. Unique features of S28E include an extended loop L2-3 that folds back onto the protein and a 12-residue charged C-terminal tail with no regular secondary structure and greater flexibility relative to the rest of the protein. The structural and surface resemblance to OB-fold family of proteins and the presence of highly conserved basic residues suggest that S28E may bind to RNA. A broad positively charged surface extending over one side of the beta-barrel and into the flexible C terminus may present a putative binding site for RNA.