Characterization of the structure of RAMP1 by mutagenesis and molecular modeling

Receptor activity modifying proteins (RAMPs) are a family of single-pass transmembrane proteins that dimerize with G-protein-coupled receptors. They may alter the ligand recognition properties of the receptors (particularly for the calcitonin receptor-like receptor, CLR). Very little structural information is available about RAMPs. Here, an ab initio model has been generated for the extracellular domain of RAMP1. The disulfide bond arrangement (Cys 27-Cys82, Cys40-Cys72, and Cys 57-Cys104) was determined by site-directed mutagenesis. The secondary structure (a-helices from residues 29-51, 60-80, and 87-100) was established from a consensus of predictive routines. Using these constraints, an assemblage of 25,000 structures was constructed and these were ranked using an all-atom statistical potential. The best 1000 conformations were energy minimized. The lowest scoring model was refined by molecular dynamics simulation. To validate our strategy, the same methods were applied to three proteins of known structure; PDB:1HP8, PDB:1V54 chain H (residues 21-85), and PDB:1T0P. When compared to the crystal structures, the models had root mean-square deviations of 3.8 Å, 4.1 Å, and 4.0 Å, respectively. The model of RAMP1 suggested that Phe93, Tyr 100, and Phe101 form a binding interface for CLR, whereas Trp74 and Phe92 may interact with ligands that bind to the CLR/RAMP1 heterodimer. © 2006 by the Biophysical Society.

Responsive hydrophobically associating polymers:a review of structure and properties

Responsive hydrophobically associating polymers can in many ways be considered to be analogous to proteins in their ability to form compact molecules with a defined secondary structure, and hence, functionality. These molecules are characterized by the presence of alternating charged and hydrophobic groups. The balance between charge repulsion and hydrophobic interactions is sensitive to environmental pH and therefore changes in pH produce controllable conformational changes. The change from a charged extended chain to a collapsed uncharged coil structure is sometimes referred to as hypercoiling behaviour and enables the polymer to act as a simple switch between an 'on' and 'off' state. The purpose of this review is to illustrate the structure and behaviour of polymers that exhibit hypercoiling behaviour and to highlight their potential pharmaceutical applications, which in terms of drug delivery is likely to be related to their surface behaviour and solubilizing activity. © 2001 Elsevier Science B.V. All rights reserved.

BPROMPT:a consensus server for membrane protein prediction

Protein structure prediction is a cornerstone of bioinformatics research. Membrane proteins require their own prediction methods due to their intrinsically different composition. A variety of tools exist for topology prediction of membrane proteins, many of them available on the Internet. The server described in this paper, BPROMPT (Bayesian PRediction Of Membrane Protein Topology), uses a Bayesian Belief Network to combine the results of other prediction methods, providing a more accurate consensus prediction. Topology predictions with accuracies of 70% for prokaryotes and 53% for eukaryotes were achieved. BPROMPT can be accessed at http://www.jenner.ac.uk/BPROMPT.

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.

DNA methylation at cytosine position 5

DNA methylation appears to be involved in the regulation of gene expression. Transcriptionally inactive (silenced) genes normally contain a high proportion of 5-methyl-2'-deoxycytosine residues whereas transcriptionally active genes show much reduced levels. There appears good reason to believe that chemical agents capable of methylating 2'-deoxycytosine might affect gene expression and as a result of hypermethylating promoter regions of cytosine-guanine rich oncogenic sequences, cancer related genes may be silenced. This thesis describes the synthesis of a number of `electrophilic' S-methylsulphonium compounds and assesses their ability to act as molecules capable of methylating cytosine at position 5 and also considers their potential as cytotoxic agents. DNA is methylated in vivo by DNA methyltransferase utilising S-adenoxylmethionine as the methyl donor. This thesis addresses the theory that S-adenoxylmethionine may be replaced as the methyl donor for DNA methytransferase by other sulphonium compounds. S-[3H-methyl]methionine sulphonium iodide was synthesised and experiments to assess the ability of this compounds to transfer methyl groups to cytosine in the presence of DNA methyltransferase were unsuccessful. A proline residue adjacent to a cysteine residue has been identified to a highly conserved feature of the active site region of a large number of prokaryotic DNA methyltransferases. The thesis examines the possibility that short peptides containing the Pro-Cys fragment may be able to facilitate the alkylation of cytosine position 5 by sulphonium compounds. Peptides were synthesised up to 9 amino acids in length but none were shown to exhibit significant activity. Molecular modelling techniques, including Chem-X, Quanta, BIPED and protein structure prediction programs were used to assess any structural similarities that may exist between short peptides containing a Pro-Cys fragment and similar sequences present in proteins. A number of similar structural features were observed.

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.

A predictor of membrane class:discriminating α-helical and β-barrel membrane proteins from non-membranous proteins

Accurate protein structure prediction remains an active objective of research in bioinformatics. Membrane proteins comprise approximately 20% of most genomes. They are, however, poorly tractable targets of experimental structure determination. Their analysis using bioinformatics thus makes an important contribution to their on-going study. Using a method based on Bayesian Networks, which provides a flexible and powerful framework for statistical inference, we have addressed the alignment-free discrimination of membrane from non-membrane proteins. The method successfully identifies prokaryotic and eukaryotic α-helical membrane proteins at 94.4% accuracy, β-barrel proteins at 72.4% accuracy, and distinguishes assorted non-membranous proteins with 85.9% accuracy. The method here is an important potential advance in the computational analysis of membrane protein structure. It represents a useful tool for the characterisation of membrane proteins with a wide variety of potential applications.

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.

Toward the prediction of class I and II mouse major histocompatibility complex-peptide-binding affinity:in silico bioinformatic step-by-step guide using quantitative structure-activity relationships

Quantitative structure-activity relationship (QSAR) analysis is a cornerstone of modern informatics. Predictive computational models of peptide-major histocompatibility complex (MHC)-binding affinity based on QSAR technology have now become important components of modern computational immunovaccinology. Historically, such approaches have been built around semiqualitative, classification methods, but these are now giving way to quantitative regression methods. We review three methods--a 2D-QSAR additive-partial least squares (PLS) and a 3D-QSAR comparative molecular similarity index analysis (CoMSIA) method--which can identify the sequence dependence of peptide-binding specificity for various class I MHC alleles from the reported binding affinities (IC50) of peptide sets. The third method is an iterative self-consistent (ISC) PLS-based additive method, which is a recently developed extension to the additive method for the affinity prediction of class II peptides. The QSAR methods presented here have established themselves as immunoinformatic techniques complementary to existing methodology, useful in the quantitative prediction of binding affinity: current methods for the in silico identification of T-cell epitopes (which form the basis of many vaccines, diagnostics, and reagents) rely on the accurate computational prediction of peptide-MHC affinity. We have reviewed various human and mouse class I and class II allele models. Studied alleles comprise HLA-A*0101, HLA-A*0201, HLA-A*0202, HLA-A*0203, HLA-A*0206, HLA-A*0301, HLA-A*1101, HLA-A*3101, HLA-A*6801, HLA-A*6802, HLA-B*3501, H2-K(k), H2-K(b), H2-D(b) HLA-DRB1*0101, HLA-DRB1*0401, HLA-DRB1*0701, I-A(b), I-A(d), I-A(k), I-A(S), I-E(d), and I-E(k). In this chapter we show a step-by-step guide into predicting the reliability and the resulting models to represent an advance on existing methods. The peptides used in this study are available from the AntiJen database (http://www.jenner.ac.uk/AntiJen). The PLS method is available commercially in the SYBYL molecular modeling software package. The resulting models, which can be used for accurate T-cell epitope prediction, will be made are freely available online at the URL http://www.jenner.ac.uk/MHCPred.

Quantitative structure-activity relationships and the prediction of MHC supermotifs

The underlying assumption in quantitative structure–activity relationship (QSAR) methodology is that related chemical structures exhibit related biological activities. We review here two QSAR methods in terms of their applicability for human MHC supermotif definition. Supermotifs are motifs that characterise binding to more than one allele. Supermotif definition is the initial in silico step of epitope-based vaccine design. The first QSAR method we review here—the additive method—is based on the assumption that the binding affinity of a peptide depends on contributions from both amino acids and the interactions between them. The second method is a 3D-QSAR method: comparative molecular similarity indices analysis (CoMSIA). Both methods were applied to 771 peptides binding to 9 HLA alleles. Five of the alleles (A*0201, A* 0202, A*0203, A*0206 and A*6802) belong to the HLA-A2 superfamily and the other four (A*0301, A*1101, A*3101 and A*6801) to the HLA-A3 superfamily. For each superfamily, supermotifs defined by the two QSAR methods agree closely and are supported by many experimental data.