NMR of conotoxins: structural features and an analysis of chemical shifts of post-translationally modified amino acids

Conotoxins are small conformationally constrained peptides found in the venom of marine snails of the genus Conus. They are usually cysteine rich and frequently contain a high degree of post-translational modifications such as C-terminal amidation, hydroxylation, carboxylation, bromination, epimerisation and glycosylation. Here we review the role of NMR in determining the three-dimensional structures of conotoxins and also provide a compilation and analysis of H-1 and C-13 chemical shifts of post-translationally modified amino acids and compare them with data from common amino acids. This analysis provides a reference source for chemical shifts of post-translationally modified amino acids. Copyright (C) 2006 John Wiley & Sons, Ltd.

Identification and molecular modeling of a novel, plant-like, human purple acid phosphatase

Purple acid phosphatases are a family of binuclear metallohydrolases that have been identified in plants, animals and fungi. Only one isoform of similar to 35 kDa has been isolated from animals, where it is associated with bone resorption and microbial killing through its phosphatase activity, and hydroxyl radical production, respectively. Using the sensitive PSI-BLAST search method, sequences representing new purple acid phosphatase-like proteins have been identified in mammals, insects and nematodes. These new putative isoforms are closely related to the similar to 55 kDa purple acid phosphatase characterized from plants. Secondary structure prediction of the new human isoform further confirms its similarity to a purple acid phosphatase from the red kidney bean. A structural model for the human enzyme was constructed based on the red kidney bean purple acid phosphatase structure. This model shows that the catalytic centre observed in other purple acid phosphatases is also present in this new isoform. These observations suggest that the sequences identified in this study represent a novel subfamily of plant-like purple acid phosphatases in animals and humans. (c) 2006 Elsevier B.V. All rights reserved.

Molecular dynamics simulations of the hydrophobin SC3 at a hydrophobic/hydrophilic interface

Hydrophobins are small (similar to 100 aa) proteins that have an important role in the growth and development of mycelial fungi. They are surface active and, after secretion by the fungi, self-assemble into amphipathic membranes at hydrophobic/hydrophilic interfaces, reversing the hydrophobicity of the surface. In this study, molecular dynamics simulation techniques have been used to model the process by which a specific class I hydrophobin, SC3, binds to a range of hydrophobic/ hydrophilic interfaces. The structure of SC3 used in this investigation was modeled based on the crystal structure of the class II hydrophobin HFBII using the assumption that the disulfide pairings of the eight conserved cysteine residues are maintained. The proposed model for SC3 in aqueous solution is compact and globular containing primarily P-strand and coil structures. The behavior of this model of SC3 was investigated at an air/water, an oil/water, and a hydrophobic solid/water interface. It was found that SC3 preferentially binds to the interfaces via the loop region between the third and fourth cysteine residues and that binding is associated with an increase in a-helix formation in qualitative agreement with experiment. Based on a combination of the available experiment data and the current simulation studies, we propose a possible model for SC3 self-assembly on a hydrophobic solid/water interface.

Molecular recognition of an RNA trafficking element by heterogeneous nuclear ribonucleoprotein A2

Heterogeneous nuclear ribonucleoprotein (hnRNP) A2 is a multitasking protein involved in RNA packaging, alternative splicing of pre-mRNA. telomere maintenance, cytoplasmic RNA trafficking, and translation. It binds short segments of single-stranded nucleic acids, including the A2RE11 RNA element that is necessary and sufficient for cytoplasmic transport of a subset of rnRNAs in oligodendrocytes and neurons. We have explored the structures of hnRNP A2, its RNA recognition motifs (RRMs) and Gly-rich module, and the RRM complexes with A2RE11. Circular dichroism spectroscopy showed that the secondary structure of the first 189 residues of hnRNP A2 parallels that of the tandem beta alpha beta beta alpha beta RRMs of its paralogue, hnRNP A1, previously deduced from X-ray diffraction studies. The unusual GRD was shown to have substantial beta-sheet and beta-turn structure. Sedimentation equilibrium and circular dichroism results were consistent with the tandem RRM region being monomeric and supported earlier evidence for the binding of two A2RE11 oligoribonucleotides to this domain, in contrast to the protein dimer formed by the complex of hnRNP A1 with the telomeric ssDNA repeat. A three-dimensional structure for the N-terminal, two-RRM-containing segment of hnRNP A2 was derived by homology modeling. This structure was used to derive a model for the complex with A2RE11 using the previously described interaction of pairs of stacked nucleotides with aromatic residues on the RRM beta-sheet platforms, conserved in other RRM-RNA complexes, together with biochemical data and molecular dynamics-based observations of inter-RRM mobility.

Preliminary crystallographic characterization of an RNA helicase from Kunjin virus

Kunjin virus is a member of the Flavivirus genus and is an Australian variant of West Nile virus. The C-terminal domain of the Kunjin virus NS3 protein displays helicase activity. The protein is thought to separate daughter and template RNA strands, assisting the initiation of replication by unwinding RNA secondary structure in the 3' nontranslated region. Expression, purification and preliminary crystallographic characterization of the NS3 helicase domain are reported. It is shown that Kunjin virus helicase may adopt a dimeric assembly in absence of nucleic acids, oligomerization being a means to provide the helicases with multiple nucleic acid-binding capability, facilitating translocation along the RNA strands. Kunjin virus NS3 helicase domain is an attractive model for studying the molecular mechanisms of flavivirus replication, while simultaneously providing a new basis for the rational development of anti-flaviviral compounds.

Predicting residue-wise contact orders in proteins by support vector regression

Background: The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. Results: We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. Conclusion: The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences.

Predicting the solvent accessibility of transmembrane residues from protein sequence

In this study, we propose a novel method to predict the solvent accessible surface areas of transmembrane residues. For both transmembrane alpha-helix and beta-barrel residues, the correlation coefficients between the predicted and observed accessible surface areas are around 0.65. On the basis of predicted accessible surface areas, residues exposed to the lipid environment or buried inside a protein can be identified by using certain cutoff thresholds. We have extensively examined our approach based on different definitions of accessible surface areas and a variety of sets of control parameters. Given that experimentally determining the structures of membrane proteins is very difficult and membrane proteins are actually abundant in nature, our approach is useful for theoretically modeling membrane protein tertiary structures, particularly for modeling the assembly of transmembrane domains. This approach can be used to annotate the membrane proteins in proteomes to provide extra structural and functional information.

STAR: predicting recombination sites from amino acid sequence

Background: Designing novel proteins with site-directed recombination has enormous prospects. By locating effective recombination sites for swapping sequence parts, the probability that hybrid sequences have the desired properties is increased dramatically. The prohibitive requirements for applying current tools led us to investigate machine learning to assist in finding useful recombination sites from amino acid sequence alone. Results: We present STAR, Site Targeted Amino acid Recombination predictor, which produces a score indicating the structural disruption caused by recombination, for each position in an amino acid sequence. Example predictions contrasted with those of alternative tools, illustrate STAR'S utility to assist in determining useful recombination sites. Overall, the correlation coefficient between the output of the experimentally validated protein design algorithm SCHEMA and the prediction of STAR is very high (0.89). Conclusion: STAR allows the user to explore useful recombination sites in amino acid sequences with unknown structure and unknown evolutionary origin. The predictor service is available from http://pprowler.itee.uq.edu.au/star.

The effect of box shape on the dynamic properties of proteins simulated under periodic boundary conditions

The effect of the box shape on the dynamic behavior of proteins simulated under periodic boundary conditions is evaluated. In particular, the influence of simulation boxes defined by the near-densest lattice packing (NDLP) in conjunction with rotational constraints is compared to that of standard box types without these constraints. Three different proteins of varying size, shape, and secondary structure content were examined in the study. The statistical significance of differences in RMSD, radius of gyration, solvent-accessible surface, number of hydrogen bonds, and secondary structure content between proteins, box types, and the application or not of rotational constraints has been assessed. Furthermore, the differences in the collective modes for each protein between different boxes and the application or not of rotational constraints have been examined. In total 105 simulations were performed, and the results compared using a three-way multivariate analysis of variance (MANOVA) for properties derived from the trajectories and a three-way univariate analysis of variance (ANOVA) for collective modes. It is shown that application of roto-translational constraints does not have a statistically significant effect on the results obtained from the different simulations. However, the choice of simulation box was found to have a small (5-10%), but statistically significant effect on the behavior of two of the three proteins included in the study. (c) 2005 Wiley Periodicals, Inc.

Predicting structural disruption of proteins caused by crossover

We present a machine learning model that predicts a structural disruption score from a protein’s primary structure. SCHEMA was introduced by Frances Arnold and colleagues as a method for determining putative recombination sites of a protein on the basis of the full (PDB) description of its structure. The present method provides an alternative to SCHEMA that is able to determine the same score from sequence data only. Circumventing the need for resolving the full structure enables the exploration of yet unresolved and even hypothetical sequences for protein design efforts. Deriving the SCHEMA score from a primary structure is achieved using a two step approach: first predicting a secondary structure from the sequence and then predicting the SCHEMA score from the predicted secondary structure. The correlation coefficient for the prediction is 0.88 and indicates the feasibility of replacing SCHEMA with little loss of precision. ©2005 IEEE

Searching oligo sets of human chromosome 12 using evolutionary strategies

DNA microarray is a powerful tool to measure the level of a mixed population of nucleic acids at one time, which has great impact in many aspects of life sciences research. In order to distinguish nucleic acids with very similar composition by hybridization, it is necessary to design probes with high specificities, i.e. uniqueness, and also sensitivities, i.e., suitable melting temperature and no secondary structure. We make use of available biology tools to gain necessary sequence information of human chromosome 12, and combined with evolutionary strategy (ES) to find unique subsequences representing all predicted exons. The results are presented and discussed.

Structural characterization of recombinant human CD81 produced in Pichia pastoris

Human CD81 (hCD81) protein has been recombinantly produced in the methylotrophic yeast Pichia pastoris. The purified protein, produced at a yield of 1.75 mg/L of culture, was shown to interact with Hepatitis C virus E2 glycoprotein. Immunofluorescent and flow cytometric staining of P. pastoris protoplasts with monoclonal antibodies specific for the second extracellular loop (EC2) of hCD81 confirmed the antigenicity of the recombinant molecule. Full-length hCD81 was solubilized with an array of detergents and subsequently characterized using circular dichroism (CD) and analytical ultracentrifugation. These biophysical techniques confirmed that the protein solution comprises a homogenous species possessing a highly-defined alpha-helical secondary structure. The predicted alpha-helical content of the protein from CD analysis (77.1%) fits remarkably well with what would be expected (75.2%) from knowledge of the protein sequence together with the data from the crystal structure of the second extracellular loop. This study represents the first biophysical characterization of a full-length recombinant tetraspanin, and opens the way for structure-activity analyses of this ubiquitous family of transmembrane proteins.

Hypercoiling and hydrophobically associating polymers : interfacial synthesis, surface properties and pharmaceutical applications

The objective of the work described was to identify and synthesize a range of biodegradable hypercoiling or hydrophobically associating polymers to mimic natural apoproteins, such as those found in lung surfactant or plasma apolipoproteins. Stirred interfacial polymerization was used to synthesize potentially biodegradable aromatic polyamides (Mw of 12,000-26,000) based on L-Iysine, L-Iysine ethyl ester, L-ornithine and DL-diaminopropionic acid, by reaction with isophthaloyl chloride. A similar technique was used to synthesize aliphatic polyamides based on L-Iysine ethyl ester and either adipoyl chloride or glutaryl chloride resulting in the synthesis of poly(lysine ethyl ester adipamide) [PLETESA] or poly(lysine ethyl ester glutaramide) (Mw of 126,000 and 26,000, respectively). PLETESA was found to be soluble in both polar and non-polar solvents and the hydrophobic/hydrophilic balance could be modified by partial saponification (66-75%) of the ethyl ester side chains. Surface or interfacial tension/pH profiles were used to assess the conformation of both the poly(isophthalamides) and partially saponified PLETESA in aqueous solution. The results demonstrated that a loss of charge from the polymer was accompanied by an initial fall in surface activity, followed by a rise in activity, and ultimately, by polymer precipitation. These observations were explained by a collapse of the polymer chains into non-surface active intramolecular coils, followed by a transition to an amphipathic conformation, and finally to a collapsed hydrophobe. 2-Dimensional NMR analysis of polymer conformation in polar and non-polar solvents revealed intramolecular associations between the hydrophobic groups within partially saponified PLETESA. Unsaponified PLETESA appeared to form a coiled structure in polar solvents where the ethyl ester side chains were contained within the polymer coil. The implications of the secondary structure of PLETESA and potential biomedical applications are discussed.

Phenotypic effect of mutations in evolving populations of RNA molecules

Background. The secondary structure of folded RNA sequences is a good model to map phenotype onto genotype, as represented by the RNA sequence. Computational studies of the evolution of ensembles of RNA molecules towards target secondary structures yield valuable clues to the mechanisms behind adaptation of complex populations. The relationship between the space of sequences and structures, the organization of RNA ensembles at mutation-selection equilibrium, the time of adaptation as a function of the population parameters, the presence of collective effects in quasispecies, or the optimal mutation rates to promote adaptation all are issues that can be explored within this framework. Results. We investigate the effect of microscopic mutations on the phenotype of RNA molecules during their in silico evolution and adaptation. We calculate the distribution of the effects of mutations on fitness, the relative fractions of beneficial and deleterious mutations and the corresponding selection coefficients for populations evolving under different mutation rates. Three different situations are explored: the mutation-selection equilibrium (optimized population) in three different fitness landscapes, the dynamics during adaptation towards a goal structure (adapting population), and the behavior under periodic population bottlenecks (perturbed population). Conclusions. The ratio between the number of beneficial and deleterious mutations experienced by a population of RNA sequences increases with the value of the mutation rate µ at which evolution proceeds. In contrast, the selective value of mutations remains almost constant, independent of µ, indicating that adaptation occurs through an increase in the amount of beneficial mutations, with little variations in the average effect they have on fitness. Statistical analyses of the distribution of fitness effects reveal that small effects, either beneficial or deleterious, are well described by a Pareto distribution. These results are robust under changes in the fitness landscape, remarkably when, in addition to selecting a target secondary structure, specific subsequences or low-energy folds are required. A population perturbed by bottlenecks behaves similarly to an adapting population, struggling to return to the optimized state. Whether it can survive in the long run or whether it goes extinct depends critically on the length of the time interval between bottlenecks. © 2010 Stich et al; licensee BioMed Central Ltd.

G-protein-coupled receptor solubilization and purification for biophysical analysis and functional studies, in the total absence of detergent

G-protein coupled receptors (GPCRs) constitute the largest class of membrane proteins and are a major drug target. A serious obstacle to studying GPCR structure/function characteristics is the requirement to extract the receptors from their native environment in the plasma membrane, coupled with the inherent instability of GPCRs in the detergents required for their solubilization. In the present study, we report the first solubilization and purification of a functional GPCR [human adenosine A2A receptor (A2AR)], in the total absence of detergent at any stage, by exploiting spontaneous encapsulation by styrene maleic acid (SMA) co-polymer direct from the membrane into a nanoscale SMA lipid particle (SMALP). Furthermore, the A2AR-SMALP, generated from yeast (Pichia pastoris) or mammalian cells, exhibited increased thermostability (∼5°C) compared with detergent [DDM (n-dodecyl-β-D-maltopyranoside)]-solubilized A2AR controls. The A2AR-SMALP was also stable when stored for prolonged periods at 4°C and was resistant to multiple freeze-thaw cycles, in marked contrast with the detergent-solubilized receptor. These properties establish the potential for using GPCR-SMALP in receptor-based drug discovery assays. Moreover, in contrast with nanodiscs stabilized by scaffold proteins, the non-proteinaceous nature of the SMA polymer allowed unobscured biophysical characterization of the embedded receptor. Consequently, CD spectroscopy was used to relate changes in secondary structure to loss of ligand binding ([³H]ZM241385) capability. SMALP-solubilization of GPCRs, retaining the annular lipid environment, will enable a wide range of therapeutic targets to be prepared in native-like state to aid drug discovery and understanding of GPCR molecular mechanisms.