Dynamics and Conformational Studies of TOAC Spin Labeled Analogues of Ctx(Ile21)-Ha Peptide from Hypsiboas albopunctatus

Antimicrobial peptides (AMPs) isolated from several organisms have been receiving much attention due to some specific features that allow them to interact with, bind to, and disrupt cell membranes. The aim of this paper was to study the interactions between a membrane mimetic and the cationic AMP Ctx(Ile21)-Ha as well as analogues containing the paramagnetic amino acid 2,2,6,6-tetramethylpiperidine-1-oxyl-4-amino-4-carboxylic acid (TOAC) incorporated at residue positions n = 0, 2, and 13. Circular dichroism studies showed that the peptides, except for [TOAC13]Ctx(Ile21)-Ha, are unstructured in aqueous solution but acquire different amounts of α-helical secondary structure in the presence of trifluorethanol and lysophosphocholine micelles. Fluorescence experiments indicated that all peptides were able to interact with LPC micelles. In addition, Ctx(Ile21)-Ha and [TOAC13]Ctx(Ile21)-Ha peptides presented similar water accessibility for the Trp residue located near the N-terminal sequence. Electron spin resonance experiments showed two spectral components for [TOAC0]Ctx(Ile21)-Ha, which are most likely due to two membrane-bound peptide conformations. In contrast, TOAC2 and TOAC13 derivatives presented a single spectral component corresponding to a strong immobilization of the probe. Thus, our findings allowed the description of the peptide topology in the membrane mimetic, where the N-terminal region is in dynamic equilibrium between an ordered, membrane-bound conformation and a disordered, mobile conformation; position 2 is most likely situated in the lipid polar head group region, and residue 13 is fully inserted into the hydrophobic core of the membrane. © 2013 Vicente et al.

The characterization of a thermostable and cambialistic superoxide dismutase from thermus filiformis

The superoxide dismutase (TfSOD) gene from the extremely thermophilic bacterium Thermus filiformis was cloned and expressed at high levels in mesophilic host. The purified enzyme displayed approximately 25 kDa band in the SDS-PAGE, which was further confirmed as TfSOD by mass spectrometry. The TfSOD was characterized as a cambialistic enzyme once it had enzymatic activity with either manganese or iron as cofactor. TfSOD showed thermostability at 65, 70 and 80°C. The amount of enzyme required to inhibit 50% of pyrogallol autoxidation was 0·41, 0·56 and 13·73 mg at 65, 70 and 80°C, respectively. According to the circular dichroism (CD) spectra data, the secondary structure was progressively lost after increasing the temperature above 70°C. The 3-dimensional model of TfSOD with the predicted cofactor binding corroborated with functional and CD analysis. © 2013 The Society for Applied Microbiology.

Modelagem molecular da interação entre a proteína de fusão do vírus sincicial respiratório humano e inibidores da ação viral. -

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Isolation and biochemical characterization of a gamma-type phospholipase A2 inhibitor from Crotalus durissus collilineatus snake serum

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Investigation of DMSO-Induced Conformational Transitions in Human Serum Albumin Using Two-Dimensional Raman Optical Activity Spectroscopy

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Conformational stability of recombinant manganese superoxide dismutase from the filamentous fungus Trichoderma reesei

Superoxide dismutases (SODS; EC 1.15.1.1) are part of the antioxidant system of aerobic organisms and are used as a defense against oxidative injury caused by reactive oxygen species (ROS). The cloning and sequencing of the 788-bp genomic DNA from Trichoderma reesei strain QM9414 (anamorph of Hypocrea jecorina) revealed an open reading frame encoding a protein of 212 amino acid residues, with 65-90% similarity to manganese superoxide dismutase from other filamentous fungi. The TrMnSOD was purified and shown to be stable from 20 to 90 degrees C for 1 h at pH from 8 to 11.5, while maintaining its biological activity. (C) 2011 Elsevier B.V. All rights reserved.

On the impact of disproportional samples in credit scoring models: An application to a Brazilian bank data

Statistical methods have been widely employed to assess the capabilities of credit scoring classification models in order to reduce the risk of wrong decisions when granting credit facilities to clients. The predictive quality of a classification model can be evaluated based on measures such as sensitivity, specificity, predictive values, accuracy, correlation coefficients and information theoretical measures, such as relative entropy and mutual information. In this paper we analyze the performance of a naive logistic regression model (Hosmer & Lemeshow, 1989) and a logistic regression with state-dependent sample selection model (Cramer, 2004) applied to simulated data. Also, as a case study, the methodology is illustrated on a data set extracted from a Brazilian bank portfolio. Our simulation results so far revealed that there is no statistically significant difference in terms of predictive capacity between the naive logistic regression models and the logistic regression with state-dependent sample selection models. However, there is strong difference between the distributions of the estimated default probabilities from these two statistical modeling techniques, with the naive logistic regression models always underestimating such probabilities, particularly in the presence of balanced samples. (C) 2012 Elsevier Ltd. All rights reserved.

A statistical mechanical model for β-hairpin kinetics

Understanding the mechanism of protein secondary structure formation is an essential part of the protein-folding puzzle. Here, we describe a simple statistical mechanical model for the formation of a β-hairpin, the minimal structural element of the antiparallel β-pleated sheet. The model accurately describes the thermodynamic and kinetic behavior of a 16-residue, β-hairpin-forming peptide, successfully explaining its two-state behavior and apparent negative activation energy for folding. The model classifies structures according to their backbone conformation, defined by 15 pairs of dihedral angles, and is further simplified by considering only the 120 structures with contiguous stretches of native pairs of backbone dihedral angles. This single sequence approximation is tested by comparison with a more complete model that includes the 215 possible conformations and 15 × 215 possible kinetic transitions. Finally, we use the model to predict the equilibrium unfolding curves and kinetics for several variants of the β-hairpin peptide.

Metal Clips Induce Folding of a Short Unstructured Peptide into an a-Helix via Turn Conformations in Water. Kinetic versus Thermodynamic Products

Short peptides corresponding to two to four a-helical turns of proteins are not thermodynamically stable helices in water. Unstructured octapeptide Ac-His1*-Ala2-Ala3-His4*-His5*-Glu6-Leu7-His8*-NH2 (1) reacts with two [Pd ((NH2)-N-15(CH2)(2) (NH2)-N-15)(NO3)(2)] in water to form a kinetically stable intermediate, [{Pden}(2)-{(1,4)(5,8)-peptide}](2), in which two 19-membered metallocyclic rings stabilize two peptide turns. Slow subsequent folding to a thermodynamically more stable two-turn a-helix drives the equilibrium to [{Pden}(2)-{(1,5)(4,8)-peptide}] (3), featuring two 22-membered rings. This transformation from unstructured peptide via turns to an a-helix suggests that metal clips might be useful probes for investigating peptide folding.

Single turn peptide alpha helices with exceptional stability in water

Cyclic pentapepticles are not known to exist in a-helical conformations. CD and NMR spectra show that specific 20-membered cyclic pentapepticles, Ac-(cyclo-1,5) [KxxxD]-NH2 and Ac-(cyclo-2,6)R[KxxxD]-NH2, are highly a-helical structures in water and independent of concentration, TFE, denaturants, and proteases. These are the smallest a-helical peptides in water.

Prediction of subcellular localization using sequence-biased recurrent networks

Motivation: Targeting peptides direct nascent proteins to their specific subcellular compartment. Knowledge of targeting signals enables informed drug design and reliable annotation of gene products. However, due to the low similarity of such sequences and the dynamical nature of the sorting process, the computational prediction of subcellular localization of proteins is challenging. Results: We contrast the use of feed forward models as employed by the popular TargetP/SignalP predictors with a sequence-biased recurrent network model. The models are evaluated in terms of performance at the residue level and at the sequence level, and demonstrate that recurrent networks improve the overall prediction performance. Compared to the original results reported for TargetP, an ensemble of the tested models increases the accuracy by 6 and 5% on non-plant and plant data, respectively.

The applicability of recurrent neural networks for biological sequence analysis

Selection of machine learning techniques requires a certain sensitivity to the requirements of the problem. In particular, the problem can be made more tractable by deliberately using algorithms that are biased toward solutions of the requisite kind. In this paper, we argue that recurrent neural networks have a natural bias toward a problem domain of which biological sequence analysis tasks are a subset. We use experiments with synthetic data to illustrate this bias. We then demonstrate that this bias can be exploitable using a data set of protein sequences containing several classes of subcellular localization targeting peptides. The results show that, compared with feed forward, recurrent neural networks will generally perform better on sequence analysis tasks. Furthermore, as the patterns within the sequence become more ambiguous, the choice of specific recurrent architecture becomes more critical.

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.

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.