Selective Loss of Cysteine Residues and Disulphide Bonds in a Potato Proteinase Inhibitor II Family

Disulphide bonds between cysteine residues in proteins play a key role in protein folding, stability, and function. Loss of a disulphide bond is often associated with functional differentiation of the protein. The evolution of disulphide bonds is still actively debated; analysis of naturally occurring variants can promote understanding of the protein evolutionary process. One of the disulphide bond-containing protein families is the potato proteinase inhibitor II (PI-II, or Pin2, for short) superfamily, which is found in most solanaceous plants and participates in plant development, stress response, and defence. Each PI-II domain contains eight cysteine residues (8C), and two similar PI-II domains form a functional protein that has eight disulphide bonds and two non-identical reaction centres. It is still unclear which patterns and processes affect cysteine residue loss in PI-II. Through cDNA sequencing and data mining, we found six natural variants missing cysteine residues involved in one or two disulphide bonds at the first reaction centre. We named these variants Pi7C and Pi6C for the proteins missing one or two pairs of cysteine residues, respectively. This PI-II-7C/6C family was found exclusively in potato. The missing cysteine residues were in bonding pairs but distant from one another at the nucleotide/protein sequence level. The non-synonymous/synonymous substitution (Ka/Ks) ratio analysis suggested a positive evolutionary gene selection for Pi6C and various Pi7C. The selective deletion of the first reaction centre cysteine residues that are structure-level-paired but sequence-level-distant in PI-II illustrates the flexibility of PI-II domains and suggests the functionality of their transient gene versions during evolution

Improving the prediction of disease-related variants using protein three-dimensional structure

Background: Single Nucleotide Polymorphisms (SNPs) are an important source of human genome variability. Non-synonymous SNPs occurring in coding regions result in single amino acid polymorphisms (SAPs) that may affect protein function and lead to pathology. Several methods attempt to estimate the impact of SAPs using different sources of information. Although sequence-based predictors have shown good performance, the quality of these predictions can be further improved by introducing new features derived from three-dimensional protein structures.Results: In this paper, we present a structure-based machine learning approach for predicting disease-related SAPs. We have trained a Support Vector Machine (SVM) on a set of 3,342 disease-related mutations and 1,644 neutral polymorphisms from 784 protein chains. We use SVM input features derived from the protein's sequence, structure, and function. After dataset balancing, the structure-based method (SVM-3D) reaches an overall accuracy of 85%, a correlation coefficient of 0.70, and an area under the receiving operating characteristic curve (AUC) of 0.92. When compared with a similar sequence-based predictor, SVM-3D results in an increase of the overall accuracy and AUC by 3%, and correlation coefficient by 0.06. The robustness of this improvement has been tested on different datasets and in all the cases SVM-3D performs better than previously developed methods even when compared with PolyPhen2, which explicitly considers in input protein structure information.Conclusion: This work demonstrates that structural information can increase the accuracy of disease-related SAPs identification. Our results also quantify the magnitude of improvement on a large dataset. This improvement is in agreement with previously observed results, where structure information enhanced the prediction of protein stability changes upon mutation. Although the structural information contained in the Protein Data Bank is limiting the application and the performance of our structure-based method, we expect that SVM-3D will result in higher accuracy when more structural date become available. \ua9 2011 Capriotti; licensee BioMed Central Ltd

Effects of Perfluorocarbons on surfactant exocytosis and membrane properties in isolated alveolar type II cells

<p>Abstract</p> <p>Background</p> <p>Perfluorocarbons (PFC) are used to improve gas exchange in diseased lungs. PFC have been shown to affect various cell types. Thus, effects on alveolar type II (ATII) cells and surfactant metabolism can be expected, data, however, are controversial.</p> <p>Objective</p> <p>The study was performed to test two hypotheses: (I) the effects of PFC on surfactant exocytosis depend on their respective vapor pressures; (II) different pathways of surfactant exocytosis are affected differently by PFC.</p> <p>Methods</p> <p>Isolated ATII cells were exposed to two PFC with different vapor pressures and spontaneous surfactant exocytosis was measured. Furthermore, surfactant exocytosis was stimulated by either ATP, PMA or Ionomycin. The effects of PFC on cell morphology, cellular viability, endocytosis, membrane permeability and fluidity were determined.</p> <p>Results</p> <p>The spontaneous exocytosis was reduced by PFC, however, the ATP and PMA stimulated exocytosis was slightly increased by PFC with high vapor pressure. In contrast, Ionomycin-induced exocytosis was decreased by PFC with low vapor pressure. Cellular uptake of FM 1-43 - a marker of membrane integrity - was increased. However, membrane fluidity, endocytosis and viability were not affected by PFC incubation.</p> <p>Conclusions</p> <p>We conclude that PFC effects can be explained by modest, unspecific interactions with the plasma membrane rather than by specific interactions with intracellular targets.</p

Stabilisation of the Fc Fragment of Human IgG1 by Engineered Intradomain Disulfide Bonds

We report the stabilization of the human IgG1 Fc fragment by engineered intradomain disulfide bonds. One of these bonds, which connects the N-terminus of the CH3 domain with the F-strand, led to an increase of the melting temperature of this domain by 10°C as compared to the CH3 domain in the context of the wild-type Fc region. Another engineered disulfide bond, which connects the BC loop of the CH3 domain with the D-strand, resulted in an increase of Tm of 5°C. Combined in one molecule, both intradomain disulfide bonds led to an increase of the Tm of about 15°C. All of these mutations had no impact on the thermal stability of the CH2 domain. Importantly, the binding of neonatal Fc receptor was also not influenced by the mutations. Overall, the stabilized CH3 domains described in this report provide an excellent basic scaffold for the engineering of Fc fragments for antigen-binding or other desired additional or improved properties. Additionally, we have introduced the intradomain disulfide bonds into an IgG Fc fragment engineered in C-terminal loops of the CH3 domain for binding to Her2/neu, and observed an increase of the Tm of the CH3 domain for 7.5°C for CysP4, 15.5°C for CysP2 and 19°C for the CysP2 and CysP4 disulfide bonds combined in one molecule

In silico-designed lignin peroxidase from Phanerochaete chrysosporium shows enhanced acid stability for depolymerization of lignin

Background: The lignin peroxidase isozyme H8 from the white-rot fungus Phanerochaete chrysosporium (LiPH8) demonstrates a high redox potential and can efficiently catalyze the oxidation of veratryl alcohol, as well as the degradation of recalcitrant lignin. However, native LiPH8 is unstable under acidic pH conditions. This characteristic is a barrier to lignin depolymerization, as repolymerization of phenolic products occurs simultaneously at neutral pH. Because repolymerization of phenolics is repressed at acidic pH, a highly acid-stable LiPH8 could accelerate the selective depolymerization of recalcitrant lignin. Results: The engineered LiPH8 was in silico designed through the structural superimposition of surface-active site-harboring LiPH8 from Phanerochaete chrysosporium and acid-stable manganese peroxidase isozyme 6 (MnP6) from Ceriporiopsis subvermispora. Effective salt bridges were probed by molecular dynamics simulation and changes to Gibbs free energy following mutagenesis were predicted, suggesting promising variants with higher stability under extremely acidic conditions. The rationally designed variant, A55R/N156E-H239E, demonstrated a 12.5-fold increased half-life under extremely acidic conditions, 9.9-fold increased catalytic efficiency toward veratryl alcohol, and a 7.8-fold enhanced lignin model dimer conversion efficiency compared to those of native LiPH8. Furthermore, the two constructed salt bridges in the variant A55R/N156E-H239E were experimentally confirmed to be identical to the intentionally designed LiPH8 variant using X-ray crystallography (PDB ID: 6A6Q). Conclusion: Introduction of strong ionic salt bridges based on computational design resulted in a LiPH8 variant with markedly improved stability, as well as higher activity under acidic pH conditions. Thus, LiPH8, showing high acid stability, will be a crucial player in biomass valorization using selective depolymerization of lignin

Mechanism of Protein Kinetic Stabilization by Engineered Disulfide Crosslinks

The impact of disulfide bonds on protein stability goes beyond simple equilibrium thermodynamics effects associated with the conformational entropy of the unfolded state. Indeed, disulfide crosslinks may play a role in the prevention of dysfunctional association and strongly affect the rates of irreversible enzyme inactivation, highly relevant in biotechnological applications. While these kinetic-stability effects remain poorly understood, by analogy with proposed mechanisms for processes of protein aggregation and fibrillogenesis, we propose that they may be determined by the properties of sparsely-populated, partially-unfolded intermediates. Here we report the successful design, on the basis of high temperature molecular-dynamics simulations, of six thermodynamically and kinetically stabilized variants of phytase from Citrobacter braakii (a biotechnologically important enzyme) with one, two or three engineered disulfides. Activity measurements and 3D crystal structure determination demonstrate that the engineered crosslinks do not cause dramatic alterations in the native structure. The inactivation kinetics for all the variants displays a strongly non-Arrhenius temperature dependence, with the time-scale for the irreversible denaturation process reaching a minimum at a given temperature within the range of the denaturation transition. We show this striking feature to be a signature of a key role played by a partially unfolded, intermediate state/ensemble. Energetic and mutational analyses confirm that the intermediate is highly unfolded (akin to a proposed critical intermediate in the misfolding of the prion protein), a result that explains the observed kinetic stabilization. Our results provide a rationale for the kinetic-stability consequences of disulfide-crosslink engineering and an experimental methodology to arrive at energetic/structural descriptions of the sparsely populated and elusive intermediates that play key roles in irreversible protein denaturation.This work was supported by grants BIO2009-09562, CSD2009-00088 from the Spanish Ministry of Science and Innovation, and FEDER Funds (JMS-R)

Deciphering the Preference and Predicting the Viability of Circular Permutations in Proteins

Circular permutation (CP) refers to situations in which the termini of a protein are relocated to other positions in the structure. CP occurs naturally and has been artificially created to study protein function, stability and folding. Recently CP is increasingly applied to engineer enzyme structure and function, and to create bifunctional fusion proteins unachievable by tandem fusion. CP is a complicated and expensive technique. An intrinsic difficulty in its application lies in the fact that not every position in a protein is amenable for creating a viable permutant. To examine the preferences of CP and develop CP viability prediction methods, we carried out comprehensive analyses of the sequence, structural, and dynamical properties of known CP sites using a variety of statistics and simulation methods, such as the bootstrap aggregating, permutation test and molecular dynamics simulations. CP particularly favors Gly, Pro, Asp and Asn. Positions preferred by CP lie within coils, loops, turns, and at residues that are exposed to solvent, weakly hydrogen-bonded, environmentally unpacked, or flexible. Disfavored positions include Cys, bulky hydrophobic residues, and residues located within helices or near the protein's core. These results fostered the development of an effective viable CP site prediction system, which combined four machine learning methods, e.g., artificial neural networks, the support vector machine, a random forest, and a hierarchical feature integration procedure developed in this work. As assessed by using the hydrofolate reductase dataset as the independent evaluation dataset, this prediction system achieved an AUC of 0.9. Large-scale predictions have been performed for nine thousand representative protein structures; several new potential applications of CP were thus identified. Many unreported preferences of CP are revealed in this study. The developed system is the best CP viability prediction method currently available. This work will facilitate the application of CP in research and biotechnology

The role of tenascin-C in tissue injury and tumorigenesis

The extracellular matrix molecule tenascin-C is highly expressed during embryonic development, tissue repair and in pathological situations such as chronic inflammation and cancer. Tenascin-C interacts with several other extracellular matrix molecules and cell-surface receptors, thus affecting tissue architecture, tissue resilience and cell responses. Tenascin-C modulates cell migration, proliferation and cellular signaling through induction of pro-inflammatory cytokines and oncogenic signaling molecules amongst other mechanisms. Given the causal role of inflammation in cancer progression, common mechanisms might be controlled by tenascin-C during both events. Drugs targeting the expression or function of tenascin-C or the tenascin-C protein itself are currently being developed and some drugs have already reached advanced clinical trials. This generates hope that increased knowledge about tenascin-C will further improve management of diseases with high tenascin-C expression such as chronic inflammation, heart failure, artheriosclerosis and cancer