Label-free quantification of Tacrolimus in biological samples by atomic force microscopy

In the present paper we describe an atomic force microscopy (AFM)-based method for the quantitative analysis of FK506 (Tacrolimus) in whole blood (WB) samples. Current reference methods used to quantify this immunosuppressive drug are based on mass spectrometry. In addition, an immunoenzymatic assay (ELISA) has been developed and is widely used in clinic, even though it shows a small but consistent overestimation of the actual drug concentration when compared with the mass spectrometry method. The AFM biosensor presented herein utilises the endogen drug receptor, FKBP12, to quantify Tacrolimus levels. The biosensor was first assayed to detect the free drug in solution, and subsequently used for the detection of Tacrolimus in blood samples. The sensor was suitable to generate a dose–response curve in the full range of clinical drug monitoring. A comparison with the clinically tested ELISA assay is also reported.     

Development of models for prediction of the antioxidant activity of derivatives of natural compounds

Antioxidants are important for maintaining the appropriate balance between oxidizing and reducing species in the body and thus preventing oxidative stress. Many natural compounds are being screened for their possible antioxidant activity. It was found that a mushroom pigment Norbadione A, which is a pulvinic acid derivative, shows an antioxidant activity; the same was found for other pulvinic acid derivatives and structurally related coumarines. Based on the results of in vitro studies performed on these compounds as a part of this study quantitative structure–activity relationship (QSAR) predictive models were constructed using multiple linear regression, counter-propagation artificial neural networks and support vector regression (SVR). The models have been developed in accordance with current QSAR guidelines, including the assessment of the models applicability domains. A new approach for the graphical evaluation of the applicability domain for SVR models is suggested. The developed models show sufficient predictive abilities for the screening of virtual libraries for new potential antioxidants.     

The PyPES library of high quality semi‐global potential energy surfaces

In this article, we present a Python‐based library of high quality semi‐global potential energy surfaces for 50 polyatomic molecules with up to six atoms. We anticipate that these surfaces will find widespread application in the testing of new potential energy surface construction algorithms and nuclear ro‐vibrational structure theories. To this end, we provide the ability to generate the energy derivatives required for Taylor series expansions to sixth order about any point on the potential energy surface in a range of common coordinate systems, including curvilinear internal, Cartesian, and normal mode coordinates. The PyPES package, along with FORTRAN, C, MATLAB and Mathematica wrappers, is available at http://sourceforge.net/projects/pypes-lib . © 2015 Wiley Periodicals, Inc.     

Nucleic acid reactivity: Challenges for next‐generation semiempirical quantum models

Semiempirical quantum models are routinely used to study mechanisms of RNA catalysis and phosphoryl transfer reactions using combined quantum mechanical (QM)/molecular mechanical methods. Herein, we provide a broad assessment of the performance of existing semiempirical quantum models to describe nucleic acid structure and reactivity to quantify their limitations and guide the development of next‐generation quantum models with improved accuracy. Neglect of diatomic differential overlap and self‐consistent density‐functional tight‐binding semiempirical models are evaluated against high‐level QM benchmark calculations for seven biologically important datasets. The datasets include: proton affinities, polarizabilities, nucleobase dimer interactions, dimethyl phosphate anion, nucleoside sugar and glycosidic torsion conformations, and RNA phosphoryl transfer model reactions. As an additional baseline, comparisons are made with several commonly used density‐functional models, including M062X and B3LYP (in some cases with dispersion corrections). The results show that, among the semiempirical models examined, the AM1/d‐PhoT model is the most robust at predicting proton affinities. AM1/d‐PhoT and DFTB3‐3ob/OPhyd reproduce the MP2 potential energy surfaces of 6 associative RNA phosphoryl transfer model reactions reasonably well. Further, a recently developed linear‐scaling “modified divide‐and‐conquer” model exhibits the most accurate results for binding energies of both hydrogen bonded and stacked nucleobase dimers. The semiempirical models considered here are shown to underestimate the isotropic polarizabilities of neutral molecules by approximately 30%. The semiempirical models also fail to adequately describe torsion profiles for the dimethyl phosphate anion, the nucleoside sugar ring puckers, and the rotations about the nucleoside glycosidic bond. The modeling of pentavalent phosphorus, particularly with thio substitutions often used experimentally as mechanistic probes, was problematic for all of the models considered. Analysis of the strengths and weakness of the models suggests that the creation of robust next‐generation models should emphasize the improvement of relative conformational energies and barriers, and nonbonded interactions. © 2015 Wiley Periodicals, Inc.     

Interaction potential models for bulk Zns,Zns nanoparticle,and Zns nanoparticle‐PMMA from first‐principles

An ab initio derived transferable polarizable force‐field has been developed for Zinc sulphide (ZnS) nanoparticle (NP) and ZnS NP‐PMMA nanocomposite. The structure and elastic constants of bulk ZnS using the new force‐field are within a few percent of experimental observables. The new force‐field show remarkable ability to reproduce structures and nucleation energies of nanoclusters (Zn₁S₁‐Zn₁₂S₁₂) as validated with that of the density functional theory calculations. A qualitative agreement of the radial distribution functions of Zn? O, in a ZnS nanocluster‐PMMA system, obtained using molecular mechanics molecular dynamics (MD) and ab initio MD (AIMD) simulations indicates that the ZnS–PMMA interaction through Zn? O bonding is explained satisfactorily by our force‐field. © 2015 Wiley Periodicals, Inc.     

QuickFF: A program for a quick and easy derivation of force fields for metal‐organic frameworks from ab initio input

QuickFF is a software package to derive accurate force fields for isolated and complex molecular systems in a quick and easy manner. Apart from its general applicability, the program has been designed to generate force fields for metal‐organic frameworks in an automated fashion. The force field parameters for the covalent interaction are derived from ab initio data. The mathematical expression of the covalent energy is kept simple to ensure robustness and to avoid fitting deficiencies as much as possible. The user needs to produce an equilibrium structure and a Hessian matrix for one or more building units. Afterward, a force field is generated for the system using a three‐step method implemented in QuickFF. The first two steps of the methodology are designed to minimize correlations among the force field parameters. In the last step, the parameters are refined by imposing the force field parameters to reproduce the ab initio Hessian matrix in Cartesian coordinate space as accurate as possible. The method is applied on a set of 1000 organic molecules to show the easiness of the software protocol. To illustrate its application to metal‐organic frameworks (MOFs), QuickFF is used to determine force fields for MIL‐53(Al) and MOF‐5. For both materials, accurate force fields were already generated in literature but they requested a lot of manual interventions. QuickFF is a tool that can easily be used by anyone with a basic knowledge of performing ab initio calculations. As a result, accurate force fields are generated with minimal effort. © 2015 Wiley Periodicals, Inc.     

Classification of nasopharyngeal cell lines (C666-1, CNE2, NP69) via Raman spectroscopy and decision tree

Researchers have demonstrated that Raman spectroscopy can be used for characterization of tumor cells with excellent spatial resolution. However, performance evaluation of different algorithms in classifying multiclass of Raman spectra has not been reported yet. In this work, we present Raman spectra of nasopharyngeal carcinoma and nasopharyngeal normal cell lines. Combined with student’s t-test and several multivariate approaches, including decision tree, support vector classification, and linear discriminant analysis, our work shows that the relative content of two histological abnormality sensitive bands at 1449 and 1658 cm⁻¹ in tumor cells is significantly different from that of normal cells (p = 0.0132), and can be a biomarker to classify these cells. This difference is confirmed by importance analyses in the decision tree model. Furthermore, performances of statistical methods are compared with one another to explore the ability in classification. Results show that the decision tree can be more capable for classification between tumorous and normal cell lines with sensitivity and specificity of 99.0% and 96.9%, respectively. Findings of this work further support our previous work and indicate that the decision tree performs more robustly in cell classification. Our work will prove helpful to the early diagnosis of nasopharyngeal carcinoma, and will indicate the decision tree to be the primary algorithm in tumor-cell classification.     

Substituting CF2 for O4′ in Components of Nucleic Acids: Towards Systems with Reduced Propensity to Form Abasic Lesions

Intrinsic structural features and energetics of nucleotides containing variously fluorinated sugars as potential building blocks of DNA duplexes and quadruplexes are explored systematically using the modern methods of density functional theory (DFT) and quantum chemical topology (QCT). Our results suggest that fluorination at the 2′‐β or 2′‐α,β positions somewhat stabilizes in vacuo the AI relative to the BI conformations. In contrast, substitution of the CF₂ group for the O4′ atom (O4′‐CF₂ modification) leads to a preference of the BI relative to AI DNA‐like conformers. All the studied modifications result in a noticeable increase in the stability of the glycosidic bond [estimated by the relaxed force constants (RFC) approach], with particularly encouraging results for the O4′‐CF₂ derivative. Consequently, the O4′‐CF₂ modified systems are suggested and explored as promising scaffolds for the development of duplex and quadruplex structures with reduced propensity to form abasic lesions and to undergo DNA damage.