290 research outputs found

    Exploring the role of cyclodextrins as a cholesterol scavenger: a molecular dynamics investigation of conformational changes and thermodynamics

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    This study presents a comprehensive analysis of the cholesterol binding mechanism and conformational changes in cyclodextrin (CD) carriers, namely βCD, 2HPβCD, and MβCD. The results revealed that the binding of cholesterol to CDs was spontaneous and thermodynamically favorable, with van der Waals interactions playing a dominant role, while Coulombic interactions have a negligible contribution. The solubility of cholesterol/βCD and cholesterol/MβCD complexes was lower compared to cholesterol/2HPβCD complex due to stronger vdW and Coulombic repulsion between water and CDs. Hydrogen bonding was found to have a minor role in the binding process. The investigation of mechanisms and kinetics of binding demonstrated that cholesterol permeates into the CD cavities completely. Replicas consideration indicated that while the binding to 2HPβCD occurred perpendicularly and solely through positioning cholesterol's oxygen toward the primary hydroxyl rim (PHR), the mechanism of cholesterol binding to βCD and MβCD could take place with the orientation of oxygen towards both rims. Functionalization resulted in decreased cavity polarity, increased constriction tendency, and altered solubility and configuration of the carrier. Upon cholesterol binding, the CDs expanded, increasing the cavity volume in cholesterol-containing systems. The effects of cholesterol on the relative shape anisotropy (κ 2) and asphericity parameter (b) in cyclodextrins were investigated. βCD exhibited a spherical structure regardless of cholesterol presence, while 2HPβCD and MβCD displayed more pronounced non-sphericity in the absence of cholesterol. Loading cholesterol transformed 2HPβCD and MβCD into more spherical shapes, with increased probabilities of higher κ 2. MβCD showed a higher maximum peak of κ 2 compared to 2HPβCD after cholesterol loading, while 2HPβCD maintained a significant maximum peak at 0.2 for b

    Identification of DNA-binding protein target sequences by physical effective energy functions. Free energy analysis of lambda repressor-DNA complexes

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    Specific binding of proteins to DNA is one of the most common ways in which gene expression is controlled. Although general rules for the DNA-protein recognition can be derived, the ambiguous and complex nature of this mechanism precludes a simple recognition code, therefore the prediction of DNA target sequences is not straightforward. DNA-protein interactions can be studied using computational methods which can complement the current experimental methods and offer some advantages. In the present work we use physical effective potentials to evaluate the DNA-protein binding affinities for the lambda repressor-DNA complex for which structural and thermodynamic experimental data are available. The effect of conformational sampling by Molecular Dynamics simulations on the computed binding energy is assessed; results show that this effect is in general negative and the reproducibility of the experimental values decreases with the increase of simulation time considered. The free energy of binding for non-specific complexes agrees with earlier theoretical suggestions. Moreover, as a results of these analyses, we propose a protocol for the prediction of DNA-binding target sequences. The possibility of searching regulatory elements within the bacteriophage-lambda genome using this protocol is explored. Our analysis shows good prediction capabilities, even in the absence of any thermodynamic data and information on the naturally recognized sequence. This study supports the conclusion that physics-based methods can offer a completely complementary methodology to sequence-based methods for the identification of DNA-binding protein target sequences.Comment: 35 pages,8 figure

    The kth nearest neighbor method for estimation of entropy changes from molecular ensembles

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    All processes involving molecular systems entail a balance between associated enthalpic and entropic changes. Molecular dynamics simulations of the end-points of a process provide in a straightforward way the enthalpy as an ensemble average. Obtaining absolute entropies is still an open problem and most commonly pathway methods are used to obtain free energy changes and thereafter entropy changes. The kth nearest neighbor (kNN) method has been first proposed as a general method for entropy estimation in the mathematical community 20 years ago. Later, it has been applied to compute conformational, positional–orientational, and hydration entropies of molecules. Programs to compute entropies from molecular ensembles, for example, from molecular dynamics (MD) trajectories, based on the kNN method, are currently available. The kNN method has distinct advantages over traditional methods, namely that it is possible to address high-dimensional spaces, impossible to treat without loss of resolution or drastic approximations with, for example, histogram-based methods. Application of the method requires understanding the features of: the kth nearest neighbor method for entropy estimation; the variables relevant to biomolecular and in general molecular processes; the metrics associated with such variables; the practical implementation of the method, including requirements and limitations intrinsic to the method; and the applications for conformational, position/orientation and solvation entropy. Coupling the method with general approximations for the multivariable entropy based on mutual information, it is possible to address high dimensional problems like those involving the conformation of proteins, nucleic acids, binding of molecules and hydration. This article is categorized under: Molecular and Statistical Mechanics > Free Energy Methods Theoretical and Physical Chemistry > Statistical Mechanics Structure and Mechanism > Computational Biochemistry and Biophysics

    Insights into a Protein-Nanoparticle System by Paramagnetic Perturbation NMR Spectroscopy

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    BACKGROUND: The interaction between proteins and nanoparticles is a very relevant subject because of the potential applications in medicine and material science in general. Further interest derives from the amyloidogenic character of the considered protein, \u3b22-microglobulin (\u3b22m), which may be regarded as a paradigmatic system for possible therapeutic strategies. Previous evidence showed in fact that gold nanoparticles (AuNPs) are able to inhibit \u3b22m fibril formation in vitro. METHODS: NMR (Nuclear Magnetic Resonance) and ESR (Electron Spin Resonance) spectroscopy are employed to characterize the paramagnetic perturbation of the extrinsic nitroxide probe Tempol on \u3b22m in the absence and presence of AuNPs to determine the surface accessibility properties and the occurrence of chemical or conformational exchange, based on measurements conducted under magnetization equilibrium and non-equilibrium conditions. RESULTS: The nitroxide perturbation analysis successfully identifies the protein regions where protein-protein or protein-AuNPs interactions hinder accessibility or/and establish exchange contacts. These information give interesting clues to recognize the fibrillation interface of \u3b22m and hypothesize a mechanism for AuNPs fibrillogenesis inhibition. CONCLUSIONS: The presented approach can be advantageously applied to the characterization of the interface in protein-protein and protein-nanoparticles interactions

    A novel de novo HDAC8 missense mutation causing Cornelia de Lange syndrome

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    Background: Cornelia de Lange syndrome (CdLS) is a rare and clinically variable syndrome characterized by growth impairment, multi-organ anomalies, and a typical set of facial dysmorphisms. Here we describe a 2-year-old female child harboring a novel de novo missense variant in HDAC8, whose phenotypical score, according to the recent consensus on CdLS clinical diagnostic criteria, allowed the diagnosis of a non-classic CdLS. Methods: Clinical exome sequencing was performed on the trio, identifying a de novo heterozygous variant in HDAC8 (NM_018486; c. 356C>G p.Thr119Arg). Molecular modeling was performed to evaluate putative functional consequence of the HDAC8 protein. Results: The variant HDAC8 c.356C>G is classified as pathogenic following the ACMG (American College of Medical Genetics and Genomics)/AMP (Association for Molecular Pathology) guidelines. By molecular modeling, we confirmed the deleterious effect of this variant, since the amino acid change compromises the conformational flexibility of the HDAC8 loop required for optimal catalytic function. Conclusion: We described a novel Thr119Arg mutation in HDAC8 in a patient displaying the major phenotypic traits of the CdLS. Our results suggest that a modest change outside an active site is capable of triggering global structural changes that propagate through the protein scaffold to the catalytic site, creating de facto haploinsufficiency

    Topologically non-trivial metal-organic assemblies inhibit \u3b22-microglobulin amyloidogenesis

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    Inhibiting amyloid aggregation through high-turnover dynamic interactions could be an efficient strategy that is already used by small heat-shock proteins in different biological contexts. We report the interactions of three topologically non-trivial, zinc-templated metal-organic assemblies, a [2]catenane, a trefoil knot (TK), and Borromean rings, with two \u3b22-microglobulin (\u3b22m) variants responsible for amyloidotic pathologies. Fast exchange and similar patterns of preferred contact surface are observed by NMR, consistent with molecular dynamics simulations. In vitro fibrillation is inhibited by each complex, whereas the zinc-free TK induces protein aggregation and does not inhibit fibrillogenesis. The metal coordination imposes structural rigidity that determines the contact area on the \u3b22m surface depending on the complex dimensions, ensuring in vitro prevention of fibrillogenesis. Administration of TK, the best protein-contacting species, to a disease-model organism, namely a Caenorhabditis elegans mutant expressing the D76N \u3b22m variant, confirms the bioactivity potential of the knot topology and suggests new developments

    Adaptability and stability of wheat cultivars in the Northern region of Rio Grande do Sul

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    Abstract: The experiment evaluated the performance of 12 wheat cultivars indicated to be grown in the northern of Rio Grande do Sul. According to Scott-Knott?s mean comparison test, they obtained higher grain yields of Ametista, Marfím, ORS Vintecinco, TBIO Mestre, TBIO Sintonia and TBIO Sinuelo, and regarding grain quality, Ametista, Jadeíte 11, ORS Vintecinco and Topázio. According to the method by Eberhart and Russell, Ametista, BRS Marcante, TBIO Iguaçu and TBIO Sinuelo were stable in relation to productivity and hectolitre weight. Using the Lin and Binns analysis, the Ametista showed higher average yield and greater stability in the evaluated cultivation conditions, and the TBIO Sintonia is indicated for favorable environments. In reference to the AMMI method, Ametista and TBIO Sinuelo were the most stable regarding productivity, and the 2014 and 2016 harvests were stable. In relation to hectolitre weight, Jadeíte 11 and TBIO Mestre and the year 2016 showed more stability. Resumo: O experimento avaliou o desempenho de 12 cultivares de trigo indicadas para cultivo no norte do estado do Rio Grande do Sul. De acordo com o teste de comparação da média de Scott-Knott, obtiveram maiores rendimentos de grãos as cultivares Ametista, Marfím, ORS Vintecinco, TBIO Mestre, TBIO Sintonia e TBIO Sinuelo, e em relação à qualidade dos grãos, Ametista, Jadeíte 11, ORS Vintecinco e Topázio. De acordo com o método de Eberhart e Russell, Ametista, BRS Marcante, TBIO Iguaçu e TBIO Sinuelo foram cultivares mais estáveis em relação à produtividade e peso do hectolitro. Utilizando a análise de Lin e Binns, a cultivar Ametista mostrou maior rendimento médio e maior estabilidade nas condições de cultivo avaliadas, e o TBIO Sintonia é o mais indicado para ambientes favoráveis. Em referência ao método AMMI, Ametista e TBIO Sinuelo foram as cultivares mais estáveis em relação à produtividade, e os cultivos de 2014 e 2016 foram estáveis. Em relação ao peso hectolitro, Jadeíte 11 e TBIO Mestre e o ano de 2016 demostraram mais estabilidade

    Bioinformatics in Italy: BITS2011, the Eighth Annual Meeting of the Italian Society of Bioinformatics

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    The BITS2011 meeting, held in Pisa on June 20-22, 2011, brought together more than 120 Italian researchers working in the field of Bioinformatics, as well as students in Bioinformatics, Computational Biology, Biology, Computer Sciences, and Engineering, representing a landscape of Italian bioinformatics research

    The osmotic pressure of charged colloidal suspensions: A unified approach to linearized Poisson-Boltzmann theory

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    We study theoretically the osmotic pressure of a suspension of charged objects (e.g., colloids, polyelectrolytes, clay platelets, etc.) dialyzed against an electrolyte solution using the cell model and linear Poisson-Boltzmann (PB) theory. From the volume derivative of the grand potential functional of linear theory we obtain two novel expressions for the osmotic pressure in terms of the potential- or ion-profiles, neither of which coincides with the expression known from nonlinear PB theory, namely, the density of microions at the cell boundary. We show that the range of validity of linearization depends strongly on the linearization point and proof that expansion about the selfconsistently determined average potential is optimal in several respects. For instance, screening inside the suspension is automatically described by the actual ionic strength, resulting in the correct asymptotics at high colloid concentration. Together with the analytical solution of the linear PB equation for cell models of arbitrary dimension and electrolyte composition explicit and very general formulas for the osmotic pressure ensue. A comparison with nonlinear PB theory is provided. Our analysis also shows that whether or not linear theory predicts a phase separation depends crucially on the precise definition of the pressure, showing that an improper choice could predict an artificial phase separation in systems as important as DNA in physiological salt solution.Comment: 16 pages, 5 figures, REVTeX4 styl

    A specific nanobody prevents amyloidogenesis of D76N β2-microglobulin in vitro and modifies its tissue distribution in vivo

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    Systemic amyloidosis is caused by misfolding and aggregation of globular proteins in vivo for which effective treatments are urgently needed. Inhibition of protein self-aggregation represents an attractive therapeutic strategy. Studies on the amyloidogenic variant of β2-microglobulin, D76N, causing hereditary systemic amyloidosis, have become particularly relevant since fibrils are formed in vitro in physiologically relevant conditions. Here we compare the potency of two previously described inhibitors of wild type β2-microglobulin fibrillogenesis, doxycycline and single domain antibodies (nanobodies). The β2-microglobulin -binding nanobody, Nb24, more potently inhibits D76N β2-microglobulin fibrillogenesis than doxycycline with complete abrogation of fibril formation. In β2-microglobulin knock out mice, the D76N β2-microglobulin/ Nb24 pre-formed complex, is cleared from the circulation at the same rate as the uncomplexed protein; however, the analysis of tissue distribution reveals that the interaction with the antibody reduces the concentration of the variant protein in the heart but does not modify the tissue distribution of wild type β2-microglobulin. These findings strongly support the potential therapeutic use of this antibody in the treatment of systemic amyloidosis
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