Solvent Accessibility Of Residues Research Articles

Cross-species comparison of site-specific evolutionary-rate variation in influenza haemagglutinin

We investigate the causes of site-specific evolutionary-rate variation in influenza haemagglutinin (HA) between human and avian influenza, for subtypes H1, H3, and H5. By calculating the evolutionary-rate ratio, ω = dN/dS as a function of a residue's solvent accessibility in the three-dimensional protein structure, we show that solvent accessibility has a significant but relatively modest effect on site-specific rate variation. By comparing rates within HA subtypes among host species, we derive an upper limit to the amount of variation that can be explained by structural constraints of any kind. Protein structure explains only 20-40% of the variation in ω. Finally, by comparing ω at sites near the sialic-acid-binding region to ω at other sites, we show that ω near the sialic-acid-binding region is significantly elevated in both human and avian influenza, with the exception of avian H5. We conclude that protein structure, HA subtype, and host biology all impose distinct selection pressures on sites in influenza HA.

Fast photochemical oxidation of proteins for comparing solvent-accessibility changes accompanying protein folding: Data processing and application to barstar

Mass spectrometry-based protein footprinting reveals regional and even amino-acid structural changes and fills the gap for many proteins and protein interactions that cannot be studied by X-ray crystallography or NMR spectroscopy. Hydroxyl radical-mediated labeling has proven to be particularly informative in this pursuit because many solvent-accessible residues can be labeled by OH in a protein or protein complex, thus providing more coverage than does specific amino-acid modifications. Finding all the OH-labeling sites requires LC/MS/MS analysis of a proteolyzed sample, but data processing is daunting without the help of automated software. We describe here a systematic means for achieving a comprehensive residue-resolved analysis of footprinting data in an efficient manner, utilizing software common to proteomics core laboratories. To demonstrate the method and the utility of OH-mediated labeling, we show that FPOP easily distinguishes the buried and exposed residues of barstar in its folded and unfolded states. This article is part of a Special Issue entitled: Mass spectrometry in structural biology.

S-linked protein homocysteinylation: identifying targets based on structural, physicochemical and protein–protein interactions of homocysteinylated proteins

An elevated level of homocysteine, a thiol-containing amino acid is associated with a wide spectrum of disease conditions. A majority (>80%) of the circulating homocysteine exist in protein-bound form. Homocysteine can bind to free cysteine residues in the protein or could cleave accessible cysteine disulfide bonds via thiol disulfide exchange reaction. Binding of homocysteine to proteins could potentially alter the structure and/or function of the protein. To date only 21 proteins have been experimentally shown to bind homocysteine. In this study we attempted to identify other proteins that could potentially bind to homocysteine based on the criteria that such proteins will have significant 3D structural homology with the proteins that have been experimentally validated and have solvent accessible cysteine residues either with high dihedral strain energy (for cysteine-cysteine disulfide bonds) or low pKa (for free cysteine residues). This analysis led us to the identification of 78 such proteins of which 68 proteins had 154 solvent accessible disulfide cysteine pairs with high dihedral strain energy and 10 proteins had free cysteine residues with low pKa that could potentially bind to homocysteine. Further, protein-protein interaction network was built to identify the interacting partners of these putative homocysteine binding proteins. We found that the 21 experimentally validated proteins had 174 interacting partners while the 78 proteins identified in our analysis had 445 first interacting partners. These proteins are mainly involved in biological activities such as complement and coagulation pathway, focal adhesion, ECM-receptor, ErbB signalling and cancer pathways, etc. paralleling the disease-specific attributes associated with hyperhomocysteinemia.

Predicting protein β-sheet contacts using a maximum entropy-based correlated mutation measure

The problem of ab initio protein folding is one of the most difficult in modern computational biology. The prediction of residue contacts within a protein provides a more tractable immediate step. Recently introduced maximum entropy-based correlated mutation measures (CMMs), such as direct information, have been successful in predicting residue contacts. However, most correlated mutation studies focus on proteins that have large good-quality multiple sequence alignments (MSA) because the power of correlated mutation analysis falls as the size of the MSA decreases. However, even with small autogenerated MSAs, maximum entropy-based CMMs contain information. To make use of this information, in this article, we focus not on general residue contacts but contacts between residues in β-sheets. The strong constraints and prior knowledge associated with β-contacts are ideally suited for prediction using a method that incorporates an often noisy CMM. Using contrastive divergence, a statistical machine learning technique, we have calculated a maximum entropy-based CMM. We have integrated this measure with a new probabilistic model for β-contact prediction, which is used to predict both residue- and strand-level contacts. Using our model on a standard non-redundant dataset, we significantly outperform a 2D recurrent neural network architecture, achieving a 5% improvement in true positives at the 5% false-positive rate at the residue level. At the strand level, our approach is competitive with the state-of-the-art single methods achieving precision of 61.0% and recall of 55.4%, while not requiring residue solvent accessibility as an input. http://www2.warwick.ac.uk/fac/sci/systemsbiology/research/software/

Independent Effects of Protein Core Size and Expression on Residue-Level Structure-Evolution Relationships

Recently, we demonstrated that yeast protein evolutionary rate at the level of individual amino acid residues scales linearly with degree of solvent accessibility. This residue-level structure-evolution relationship is sensitive to protein core size: surface residues from large-core proteins evolve much faster than those from small-core proteins, while buried residues are equally constrained independent of protein core size. In this work, we investigate the joint effects of protein core size and expression on the residue-level structure-evolution relationship. At the whole-protein level, protein expression is a much more dominant determinant of protein evolutionary rate than protein core size. In contrast, at the residue level, protein core size and expression both have major impacts on protein structure-evolution relationships. In addition, protein core size and expression influence residue-level structure-evolution relationships in qualitatively different ways. Protein core size preferentially affects the non-synonymous substitution rates of surface residues compared to buried residues, and has little influence on synonymous substitution rates. In comparison, protein expression uniformly affects all residues independent of degree of solvent accessibility, and affects both non-synonymous and synonymous substitution rates. Protein core size and expression exert largely independent effects on protein evolution at the residue level, and can combine to produce dramatic changes in the slope of the linear relationship between residue evolutionary rate and solvent accessibility. Our residue-level findings demonstrate that protein core size and expression are both important, yet qualitatively different, determinants of protein evolution. These results underscore the complementary nature of residue-level and whole-protein analysis of protein evolution.

Modeling coding-sequence evolution within the context of residue solvent accessibility

BackgroundProtein structure mediates site-specific patterns of sequence divergence. In particular, residues in the core of a protein (solvent-inaccessible residues) tend to be more evolutionarily conserved than residues on the surface (solvent-accessible residues).ResultsHere, we present a model of sequence evolution that explicitly accounts for the relative solvent accessibility of each residue in a protein. Our model is a variant of the Goldman-Yang 1994 (GY94) model in which all model parameters can be functions of the relative solvent accessibility (RSA) of a residue. We apply this model to a data set comprised of nearly 600 yeast genes, and find that an evolutionary-rate ratio ω that varies linearly with RSA provides a better model fit than an RSA-independent ω or an ω that is estimated separately in individual RSA bins. We further show that the branch length t and the transition-transverion ratio κ also vary with RSA. The RSA-dependent GY94 model performs better than an RSA-dependent Muse-Gaut 1994 (MG94) model in which the synonymous and non-synonymous rates individually are linear functions of RSA. Finally, protein core size affects the slope of the linear relationship between ω and RSA, and gene expression level affects both the intercept and the slope.ConclusionsStructure-aware models of sequence evolution provide a significantly better fit than traditional models that neglect structure. The linear relationship between ω and RSA implies that genes are better characterized by their ω slope and intercept than by just their mean ω.

Integrating Sequence Variation and Protein Structure to Identify Sites under Selection

We present a novel method to identify sites under selection in protein-coding genes. Our method combines the traditional Goldman-Yang model of coding-sequence evolution with the information obtained from the 3D structure of the evolving protein, specifically the relative solvent accessibility (RSA) of individual residues. We develop a random-effects likelihood sites model in which rate classes are RSA dependent. The RSA dependence is modeled with linear functions. We demonstrate that our RSA-dependent model provides a significantly better fit to molecular sequence data than does a traditional, RSA-independent model. We further show that our model provides a natural, RSA-dependent neutral baseline for the evolutionary rate ratio ω = dN/dS Sites that deviate from this neutral baseline likely experience selection pressure for function. We apply our method to the influenza proteins hemagglutinin and neuraminidase. For hemagglutinin, our method recovers positively selected sites near the sialic acid-binding site and negatively selected sites that may be important for trimerization. For neuraminidase, our method recovers the oseltamivir resistance site and otherwise suggests that few sites deviate from the neutral baseline. Our method is broadly applicable to any protein sequences for which structural data are available or can be obtained via homology modeling or threading.

USING RIGIDITY ANALYSIS TO PROBE MUTATION-INDUCED STRUCTURAL CHANGES IN PROTEINS

Predicting the effect of a single amino acid substitution on the stability of a protein structure is a fundamental task in macromolecular modeling. It has relevance to drug design and understanding of disease-causing protein variants. We present KINARI-Mutagen, a web server for performing in silico mutation experiments on protein structures from the Protein Data Bank. Our rigidity-theoretical approach permits fast evaluation of the effects of mutations that may not be easy to perform in vitro, because it is not always possible to express a protein with a specific amino acid substitution. We use KINARI-Mutagen to identify critical residues, and we show that our predictions correlate with destabilizing mutations to glycine. In two in-depth case studies we show that the mutated residues identified by KINARI-Mutagen as critical correlate with experimental data, and would not have been identified by other methods such as Solvent Accessible Surface Area measurements or residue ranking by contributions to stabilizing interactions. We also generate 48 mutants for 14 proteins, and compare our rigidity-based results against experimental mutation stability data. KINARI-Mutagen is available at http://kinari.cs.umass.edu.

DR_bind: a web server for predicting DNA-binding residues from the protein structure based on electrostatics, evolution and geometry

DR_bind is a web server that automatically predicts DNA-binding residues, given the respective protein structure based on (i) electrostatics, (ii) evolution and (iii) geometry. In contrast to machine-learning methods, DR_bind does not require a training data set or any parameters. It predicts DNA-binding residues by detecting a cluster of conserved, solvent-accessible residues that are electrostatically stabilized upon mutation to Asp−/Glu−. The server requires as input the DNA-binding protein structure in PDB format and outputs a downloadable text file of the predicted DNA-binding residues, a 3D visualization of the predicted residues highlighted in the given protein structure, and a downloadable PyMol script for visualization of the results. Calibration on 83 and 55 non-redundant DNA-bound and DNA-free protein structures yielded a DNA-binding residue prediction accuracy/precision of 90/47% and 88/42%, respectively. Since DR_bind does not require any training using protein–DNA complex structures, it may predict DNA-binding residues in novel structures of DNA-binding proteins resulting from structural genomics projects with no conservation data. The DR_bind server is freely available with no login requirement at http://dnasite.limlab.ibms.sinica.edu.tw.

Sequence, Structure, and Dynamic Determinants of Hsp27 (HspB1) Equilibrium Dissociation Are Encoded by the N-Terminal Domain

Human small heat shock protein 27 (Hsp27) undergoes concentration-dependent equilibrium dissociation from an ensemble of large oligomers to a dimer. This phenomenon plays a critical role in Hsp27 chaperone activity in vitro enabling high affinity binding to destabilized proteins. In vivo dissociation, which is regulated by phosphorylation, controls Hsp27 role in signaling pathways. In this study, we explore the sequence determinants of Hsp27 dissociation and define the structural basis underlying the increased affinity of Hsp27 dimers to client proteins. A systematic cysteine mutagenesis is carried out to identify residues in the N-terminal domain important for the equilibrium between Hsp27 oligomers and dimers. In addition, spin-labels were attached to the cysteine mutants to enable electron paramagnetic resonance (EPR) analysis of residue environment and solvent accessibility in the context of the large oligomers, upon dissociation to the dimer, and following complex formation with the model substrate T4 Lysozyme (T4L). The mutagenic analysis identifies residues that modulate the equilibrium dissociation in favor of the dimer. EPR analysis reveals that oligomer dissociation disrupts subunit contacts leading to the exposure of Hsp27 N-terminal domain to the aqueous solvent. Moreover, regions of this domain are highly dynamic with no evidence of a packed core. Interaction between T4L and sequences in this domain is inferred from transition of spin-labels to a buried environment in the substrate/Hsp27 complex. Together, the data provide the first structural analysis of sHSP dissociation and support a model of chaperone activity wherein unstructured and highly flexible regions in the N-terminal domain are critical for substrate binding.

Increased Protein Structural Resolution from Diethylpyrocarbonate-based Covalent Labeling and Mass Spectrometric Detection

Covalent labeling and mass spectrometry are seeing increased use together as a way to obtain insight into the 3-dimensional structure of proteins and protein complexes. Several amino acid specific (e.g., diethylpyrocarbonate) and non-specific (e.g., hydroxyl radicals) labeling reagents are available for this purpose. Diethylpyrocarbonate (DEPC) is a promising labeling reagent because it can potentially probe up to 30% of the residues in the average protein and gives only one reaction product, thereby facilitating mass spectrometric analysis. It was recently reported, though, that DEPC modifications are labile for some amino acids. Here, we show that label loss is more significant and widespread than previously thought, especially for Ser, Thr, Tyr, and His residues, when relatively long protein digestion times are used. Such label loss ultimately decreases the amount of protein structural information that is obtainable with this reagent. We find, however, that the number of DEPC modified residues and, thus, protein structural information, can be significantly increased by decreasing the time between the covalent labeling reaction and the mass spectrometric analysis. This is most effectively accomplished using short (e.g., 2 h) proteolytic digestions with enzymes such as immobilized chymotrypsin or Glu-C rather than using methods (e.g., microwave or ultrasonic irradiation) that accelerate proteolysis in other ways. Using short digestion times, we show that the percentage of solvent accessible residues that can be modified by DEPC increases from 44% to 67% for cytochrome c, 35% to 81% for myoglobin, and 76% to 95% for β-2-microglobulin. In effect, these increased numbers of modified residues improve the protein structural resolution available from this covalent labeling method. Compared with typical overnight digestion conditions, the short digestion times decrease the average distance between modified residues from 11 to 7 Å for myoglobin, 13 to 10 Å for cytochrome c, and 9 to 8 Å for β-2-microglobulin.

Identification of residues involved in homodimer formation located within a β-strand region of the N-terminus of a Yeast G protein-coupled receptor

G protein-coupled receptors (GPCRs) are members of a superfamily of cell surface signaling proteins that play critical roles in many physiological functions; malfunction of these proteins is associated with multiple diseases. Understanding the structure–function relationships of these proteins is important, therefore, for GPCR-based drug discovery. The yeast Saccharomyces cerevisiae tridecapeptide pheromone α-factor receptor Ste2p has been studied as a model to explore the structure–function relationships of this important class of cell surface receptors. Although transmembrane domains of GPCRs have been examined extensively, the extracellular N-terminus and loop regions have received less attention. We have used substituted cysteine accessibility method to probe the solvent accessibility of single cysteine residues engineered to replace residues Gly20 through Gly33 of the N-terminus of Ste2p. Unexpectedly, our analyses revealed that the residues Ser22, Ile24, Tyr26, and Ser28 in the N-terminus were solvent inaccessible, whereas all other residues of the targeted region were solvent accessible. The periodicity of accessibility from residues Ser22–Ser28 is indicative of an underlying structure consistent with a β-strand that was predicted computationally in this region. Moreover, a number of these Cys-substituted Ste2p receptors (G20C, S22C, I24C, Y26C, S28C and Y30C) were found to form increased dimers compared to the Cys-less Ste2p. Based on these data, we propose that part of the N-terminus of Ste2p is structured and that this structure forms a dimer interface for Ste2p molecules. Dimerization mediated by the N-terminus was affected by ligand binding, indicating an unanticipated conformational change in the N-terminus upon receptor activation.

RSARF: Prediction of Residue Solvent Accessibility from Protein Sequence Using Random Forest Method

Prediction of protein structure from its amino acid sequence is still a challenging problem. The complete physicochemical understanding of protein folding is essential for the accurate structure prediction. Knowledge of residue solvent accessibility gives useful insights into protein structure prediction and function prediction. In this work, we propose a random forest method, RSARF, to predict residue accessible surface area from protein sequence information. The training and testing was performed using 120 proteins containing 22006 residues. For each residue, buried and exposed state was computed using five thresholds (0%, 5%, 10%, 25%, and 50%). The prediction accuracy for 0%, 5%, 10%, 25%, and 50% thresholds are 72.9%, 78.25%, 78.12%, 77.57% and 72.07% respectively. Further, comparison of RSARF with other methods using a benchmark dataset containing 20 proteins shows that our approach is useful for prediction of residue solvent accessibility from protein sequence without using structural information. The RSARF program, datasets and supplementary data are available at http://caps.ncbs.res.in/download/pugal/RSARF/.

Oxidative Modification of Native Protein Residues Using Cerium(IV) Ammonium Nitrate

A new protein modification strategy has been developed that is based on an oxidative coupling reaction that targets electron-rich amino acids. This strategy relies on cerium(IV) ammonium nitrate (CAN) as an oxidation reagent and results in the coupling of tyrosine and tryptophan residues to phenylene diamine and anisidine derivatives. The methodology was first identified and characterized on peptides and small molecules, and was subsequently adapted for protein modification by determining appropriate buffer conditions. Using the optimized procedure, native and introduced solvent-accessible residues on proteins were selectively modified with polyethylene glycol (PEG) and small peptides. This unprecedented bioconjugation strategy targets these under-utilized amino acids with excellent chemoselectivity and affords good-to-high yields using low concentrations of the oxidant and coupling partners, short reaction times, and mild conditions.

CLICK--topology-independent comparison of biomolecular 3D structures.

Our server, CLICK: http://mspc.bii.a-star.edu.sg/click, is capable of superimposing the 3D structures of any pair of biomolecules (proteins, DNA, RNA, etc.). The server makes use of the Cartesian coordinates of the molecules with the option of using other structural features such as secondary structure, solvent accessible surface area and residue depth to guide the alignment. CLICK first looks for cliques of points (3–7 residues) that are structurally similar in the pair of structures to be aligned. Using these local similarities, a one-to-one equivalence is charted between the residues of the two structures. A least square fit then superimposes the two structures. Our method is especially powerful in establishing protein relationships by detecting similarities in structural subdomains, domains and topological variants. CLICK has been extensively benchmarked and compared with other popular methods for protein and RNA structural alignments. In most cases, CLICK alignments were statistically significantly better in terms of structure overlap. The method also recognizes conformational changes that may have occurred in structural domains or subdomains in one structure with respect to the other. For this purpose, the server produces complementary alignments to maximize the extent of detectable similarity. Various examples showcase the utility of our web server.

Abstract 2118: Phenotypic diversity of disease-associated transforming growth factor-β (TGF-β) type I receptor gene (TGFBR1) mutants

Abstract Transforming Growth Factor-β (TGF-β) inhibits cell growth and drives of epithelial-to-mesenchymal transition, invasion and migration. Somatic mutations in the TGFBR1 and -2 genes have been found in cancer (n=9), while germline mutations are the proximal cause of the Loeys-Dietz aortic aneurysm syndrome (LDS)(n=42). Each of the 40 missense mutations associated with disease affect the protein kinase domain. The majority of mutations affect buried residues, where biochemically non-conservative substitutions may disrupt protein folding. This is in sharp contrast with disease-associated mutations in TGFBR2, all of which affect solvent accessible residues and likely alter protein-protein interactions. We performed an in silico analysis of TGFBR1 mutants using SNAP (Screening for Non-Acceptable Polymorphisms), a sequence-based method to predict the functional effects of single amino acid substitutions. First, the means of SNAP scores for all possible non-conservative substitutions at each residue were used to predict functionally important domains of the wild type protein. All of the disease-associated TGFBR1 mutants was located within such domain. Secondly, 35 (92%) of the 38 disease-associated TGFBR1 missense mutations were correctly classified as non-neutral. In order to validate these predictions experimentally, we have constructed a library of HA-tagged mutants in a pcDNA3 backbone. Thus far, six of these (T200I, K223E, A230T, K232E, N267H, and S387Y) have been characterized in detail. The known kinase inactive K232R mutant was included as negative control. To determine the effect of these mutations on TGF-β-regulated gene transcription, we carried out transient transfection assays using the Smad-responsive SBE4-Luc reporter in both wild type (Mv1Lu) and TGFBR1- deficient (R1B) mink lung epithelial cells. In R1B cells, the T200I, K232E, and K232R mutants were inactive, while A230T, K223E, N267H, and S387Y restored TGF-β-induced SBE4-Luc responses. Interestingly, the K223E mutation constitutively activates SBE4-Luc signaling in the absence of TGF-β, while the response of the S387Y mutant to TGF-β is attenuated. As expected, T200I, K232E and K232R were unable to phosphorylate Smads 2 and -3, while S387Y, K223E, and A230T had retained their kinase activity. Interestingly, the ability of the N267H mutant to activate pSmad2 is attenuated compared to wild type TGFBR1. Additionally, A230T is able to induce pSmad2 in the presence of the kinase inhibitor, SD-093, indicating that this mutant kinase is constitutively active. In conclusion, disease-associated TGFBR1 gene mutants display considerable phenotypic diversity, ranging from complete loss of function to constitutive activation. These findings have important implications for the selection of patients with cancer or LDS for treatment with TGFBR1 selective kinase inhibitors. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 2118. doi:10.1158/1538-7445.AM2011-2118

Identification of Potential Sites for Tryptophan Oxidation in Recombinant Antibodies Using tert-Butylhydroperoxide and Quantitative LC-MS

Amino acid oxidation is known to affect the structure, activity, and rate of degradation of proteins. Methionine oxidation is one of the several chemical degradation pathways for recombinant antibodies. In this study, we have identified for the first time a solvent accessible tryptophan residue (Trp-32) in the complementary-determining region (CDR) of a recombinant IgG1 antibody susceptible to oxidation under real-time storage and elevated temperature conditions. The degree of light chain Trp-32 oxidation was found to be higher than the oxidation level of the conserved heavy chain Met-429 and the heavy chain Met-107 of the recombinant IgG1 antibody HER2, which have already been identified as being solvent accessible and sensitive to chemical oxidation. In order to reduce the time for simultaneous identification and functional evaluation of potential methionine and tryptophan oxidation sites, a test system employing tert-butylhydroperoxide (TBHP) and quantitative LC-MS was developed. The optimized oxidizing conditions allowed us to specifically oxidize the solvent accessible methionine and tryptophan residues that displayed significant oxidation in the real-time stability and elevated temperature study. The achieved degree of tryptophan oxidation was adequate to identify the functional consequence of the tryptophan oxidation by binding studies. In summary, the here presented approach of employing TBHP as oxidizing reagent combined with quantitative LC-MS and binding studies greatly facilitates the efficient identification and functional evaluation of methionine and tryptophan oxidation sites in the CDR of recombinant antibodies.

Mechanism of acetaldehyde-induced deactivation of microbial lipases

BackgroundMicrobial lipases represent the most important class of biocatalysts used for a wealth of applications in organic synthesis. An often applied reaction is the lipase-catalyzed transesterification of vinyl esters and alcohols resulting in the formation of acetaldehyde which is known to deactivate microbial lipases, presumably by structural changes caused by initial Schiff-base formation at solvent accessible lysine residues. Previous studies showed that several lipases were sensitive toward acetaldehyde deactivation whereas others were insensitive; however, a general explanation of the acetaldehyde-induced inactivation mechanism is missing.ResultsBased on five microbial lipases from Candida rugosa, Rhizopus oryzae, Pseudomonas fluorescens and Bacillus subtilis we demonstrate that the protonation state of lysine ε-amino groups is decisive for their sensitivity toward acetaldehyde. Analysis of the diverse modification products of Bacillus subtilis lipases in the presence of acetaldehyde revealed several stable products such as α,β-unsaturated polyenals, which result from base and/or amino acid catalyzed aldol condensation of acetaldehyde. Our studies indicate that these products induce the formation of stable Michael-adducts at solvent-accessible amino acids and thus lead to enzyme deactivation. Further, our results indicate Schiff-base formation with acetaldehyde to be involved in crosslinking of lipase molecules.ConclusionsDifferences in stability observed with various commercially available microbial lipases most probably result from different purification procedures carried out by the respective manufacturers. We observed that the pH of the buffer used prior to lyophilization of the enzyme sample is of utmost importance. The mechanism of acetaldehyde-induced deactivation of microbial lipases involves the generation of α,β-unsaturated polyenals from acetaldehyde which subsequently form stable Michael-adducts with the enzymes. Lyophilization of the enzymes from buffer at pH 6.0 can provide an easy and effective way to stabilize lipases toward inactivation by acetaldehyde.

Structure of Apolipoprotein A-I N Terminus on Nascent High Density Lipoproteins

Apolipoprotein A-I (apoA-I) is the major protein component of high density lipoproteins (HDL) and a critical element of cholesterol metabolism. To better elucidate the role of the apoA-I structure-function in cholesterol metabolism, the conformation of the apoA-I N terminus (residues 6-98) on nascent HDL was examined by electron paramagnetic resonance (EPR) spectroscopic analysis. A series of 93 apoA-I variants bearing single nitroxide spin label at positions 6-98 was reconstituted onto 9.6-nm HDL particles (rHDL). These particles were subjected to EPR spectral analysis, measuring regional flexibility and side chain solvent accessibility. Secondary structure was elucidated from side-chain mobility and molecular accessibility, wherein two major α-helical domains were localized to residues 6-34 and 50-98. We identified an unstructured segment (residues 35-39) and a β-strand (residues 40-49) between the two helices. Residues 14, 19, 34, 37, 41, and 58 were examined by EPR on 7.8, 8.4, and 9.6 nm rHDL to assess the effect of particle size on the N-terminal structure. Residues 14, 19, and 58 showed no significant rHDL size-dependent spectral or accessibility differences, whereas residues 34, 37, and 41 displayed moderate spectral changes along with substantial rHDL size-dependent differences in molecular accessibility. We have elucidated the secondary structure of the N-terminal domain of apoA-I on 9.6 nm rHDL (residues 6-98) and identified residues in this region that are affected by particle size. We conclude that the inter-helical segment (residues 35-49) plays a role in the adaptation of apoA-I to the particle size of HDL.

Interactions of Apurinic/Apyrimidinic Endonuclease with a Redox Inhibitor: Evidence for an Alternate Conformation of the Enzyme

Apurinic/apyrimidinic endonuclease (APE1) is an essential base excision repair protein that also functions as a reduction and oxidation (redox) factor in mammals. Through a thiol-based mechanism, APE1 reduces a number of important transcription factors, including AP-1, p53, NF-κB, and HIF-1α. What is known about the mechanism to date is that the buried residues Cys 65 and Cys 93 are critical for APE1's redox activity. To further detail the redox mechanism, we developed a chemical footprinting-mass spectrometric assay using N-ethylmaleimide (NEM), an irreversible Cys modifier, to characterize the interaction of the redox inhibitor, E3330, with APE1. When APE1 was incubated with E3330, two NEM-modified products were observed, one with two and a second with seven added NEMs; this latter product corresponds to a fully modified APE1. In a similar control reaction without E3330, only the +2NEM product was observed in which the two solvent-accessible Cys residues, C99 and C138, were modified by NEM. Through hydrogen-deuterium amide exchange with analysis by mass spectrometry, we found that the +7NEM-modified species incorporates approximately 40 more deuterium atoms than the native protein, which exchanges nearly identically as the +2NEM product, suggesting that APE1 can be trapped in a partially unfolded state. E3330 was also found to increase the extent of disulfide bond formation involving redox critical Cys residues in APE1 as assessed by liquid chromatography and tandem mass spectrometry, suggesting a basis for its inhibitory effects on APE1's redox activity. Collectively, our results suggest that APE1 adopts a partially unfolded state, which we propose is the redox active form of the enzyme.