spectra modeling
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The cis-platin binding to the d(CCTGGTCC)*d(GGACCAGG) model DNA octamer was monitored with infrared absorption (IR) and vibrational circular dichroism (VCD) spectroscopies. The spectra were modeled with the aid of density functional computations and a Cartesian coordinate-based transfer of molecular property tensors from smaller DNA fragments. Because of the fragmentation, the tensors could be calculated with a higher precision. Environmental effects, such as the presence of the solvent or the cis-platin ligand, could be included in the modeling. The solvent was modeled by an explicit inclusion of hydrogen-bound water molecules, positions of which were estimated from a molecular dynamics simulation, or by the polarized continuum COSMO model. The B3LYP and BPW91 functionals used for the calculations of the spectral parameters were combined with the relativistic LANL2DZ platinum pseudo-potentials. The simulations reproduced the main IR and VCD DNA spectral features and explained most of the changes observed experimentally upon metal binding. The results confirmed that the influence of the ligand on DNA vibrational properties is quite complex; it originates in the geometry deformation and normal mode coupling pattern changes of the platinated octamer, as well as in local perturbations of the electronic structure and force field of the GC base pairs to which the platinum is bound. Many of the local effects could be accounted for by a point charge used in place of the metal in the GC complex.
- MeSH
- chemické modely MeSH
- cisplatina chemie MeSH
- DNA chemie MeSH
- farmaceutická chemie metody MeSH
- financování organizované MeSH
- fyzikální chemie metody MeSH
- guanidin chemie MeSH
- ionty MeSH
- ligandy MeSH
- magnetická rezonanční spektroskopie MeSH
- molekulární konformace MeSH
- molekulární struktura MeSH
- oligonukleotidy chemie MeSH
- protinádorové látky chemie MeSH
- spektrofotometrie infračervená metody MeSH
- spektrofotometrie metody MeSH
Interpretation of the Raman optical activity (ROA) of peptides is difficult because of molecular flexibility and interaction with the solvent. Typically, simulations and experiments are compared in terms of a qualitative agreement between the spectra. However, on a series of the Pro-Gly, Gly-Pro, Pro-Ala, and Ala-Pro dipeptides more precise conformer ratios could be obtained with the aid of the density functional computations and numerical decomposition of the spectral shapes. All observed transitions were assigned, and the computed transition frequencies were scaled accordingly. Then the populations predicted by the optical spectroscopy agreed within a few percent with an analysis of the spin-spin coupling constants based on the Karplus equations, which was confirmed also by a comparison of calculated and experimental NMR couplings. The results are supported by molecular dynamics simulations and related to the previous conformational studies of similar molecules.
- MeSH
- chemické modely MeSH
- dipeptidy chemie MeSH
- financování organizované MeSH
- kvantová teorie MeSH
- magnetická rezonanční spektroskopie metody normy MeSH
- molekulární konformace MeSH
- počítačová simulace MeSH
- Ramanova spektroskopie metody normy MeSH
- referenční standardy MeSH
- reprodukovatelnost výsledků MeSH
- vibrace MeSH
- Publikační typ
- srovnávací studie MeSH
The surface organic horizons in forest soils have been affected by air and soil pollutants, including potentially toxic elements (PTEs). Monitoring of PTEs requires a large number of samples and adequate analysis. Visible-near infrared (vis-NIR: 350-2500 nm) spectroscopy provides an alternative method to conventional laboratory measurements, which are time-consuming and expensive. However, vis-NIR spectroscopy relies on an empirical calibration of the target attribute to the spectra. This study examined the capability of vis-NIR spectra coupled with machine learning (ML) techniques (partial least squares regression (PLSR), support vector machine regression (SVMR), and random forest (RF)) and a deep learning (DL) approach called fully connected neural network (FNN) to assess selected PTEs (Cr, Cu, Pb, Zn, and Al) in forest organic horizons. The dataset consists of 2160 samples from 1080 sites in the forests over all the Czech Republic. At each site, we collected two samples from the fragmented (F) and humus (H) organic layers. The content of all PTEs was higher in horizon H compared to F horizon. Our results indicate that the reflectance of samples tended to decrease with increased PTEs concentration. Cr was the most accurately predicted element, regardless of the algorithm used. SVMR provided the best results for assessing the H horizon (R2 = 0.88 and RMSE = 3.01 mg/kg for Cr). FNN produced the best predictions of Cr in the combined F + H layers (R2 = 0.89 and RMSE = 2.95 mg/kg) possibly due to the larger number of samples. In the F horizon, the PTEs were not predicted adequately. The study shows that PTEs in forest soils of the Czech Republic can be accurately estimated with vis-NIR spectra and ML approaches. Results hint in availability of a large sample size, FNN provides better results.
- MeSH
- algoritmy MeSH
- látky znečišťující půdu * MeSH
- neuronové sítě MeSH
- půda * MeSH
- Publikační typ
- časopisecké články MeSH
- Geografické názvy
- Česká republika MeSH
Acta dermato-venereologica, ISSN 0365-8341 vol. 57, suppl. 77
33 s. : tab. ; 26 cm
Proton MR spectra of the brain, especially those measured at short and intermediate echo times, contain signals from mobile macromolecules (MM). A description of the main MM is provided in this consensus paper. These broad peaks of MM underlie the narrower peaks of metabolites and often complicate their quantification but they also may have potential importance as biomarkers in specific diseases. Thus, separation of broad MM signals from low molecular weight metabolites enables accurate determination of metabolite concentrations and is of primary interest in many studies. Other studies attempt to understand the origin of the MM spectrum, to decompose it into individual spectral regions or peaks and to use the components of the MM spectrum as markers of various physiological or pathological conditions in biomedical research or clinical practice. The aim of this consensus paper is to provide an overview and some recommendations on how to handle the MM signals in different types of studies together with a list of open issues in the field, which are all summarized at the end of the paper.
- MeSH
- dospělí MeSH
- konsensus * MeSH
- lidé středního věku MeSH
- lidé MeSH
- lipidy chemie MeSH
- magnetická rezonanční tomografie MeSH
- makromolekulární látky metabolismus MeSH
- metabolom MeSH
- mladý dospělý MeSH
- mozek diagnostické zobrazování MeSH
- počítačové zpracování signálu MeSH
- protonová magnetická rezonanční spektroskopie * MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- teoretické modely MeSH
- znalecký posudek * MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mladý dospělý MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Research Support, N.I.H., Extramural MeSH
Automated methods for NMR structure determination of proteins are continuously becoming more robust. However, current methods addressing larger, more complex targets rely on analyzing 6-10 complementary spectra, suggesting the need for alternative approaches. Here, we describe 4D-CHAINS/autoNOE-Rosetta, a complete pipeline for NOE-driven structure determination of medium- to larger-sized proteins. The 4D-CHAINS algorithm analyzes two 4D spectra recorded using a single, fully protonated protein sample in an iterative ansatz where common NOEs between different spin systems supplement conventional through-bond connectivities to establish assignments of sidechain and backbone resonances at high levels of completeness and with a minimum error rate. The 4D-CHAINS assignments are then used to guide automated assignment of long-range NOEs and structure refinement in autoNOE-Rosetta. Our results on four targets ranging in size from 15.5 to 27.3 kDa illustrate that the structures of proteins can be determined accurately and in an unsupervised manner in a matter of days.
- MeSH
- algoritmy * MeSH
- bakteriální proteiny chemie MeSH
- konformace proteinů, alfa-helix MeSH
- konformace proteinů, beta-řetězec MeSH
- molekulární modely MeSH
- nukleární magnetická rezonance biomolekulární metody MeSH
- Thermoanaerobacter chemie MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Research Support, N.I.H., Extramural MeSH
Binary and ternary amorphous transition metal (TM) nitrides and oxides are of great interest because of their suitability for diverse applications ranging from high-temperature machining to the production of optical filters or electrochromic devices. However, understanding of bonding in, and electronic structure of, these materials represents a challenge mainly due to the d electrons in their valence band. In the present work, we report ab initio calculations of the structure and electronic structure of ZrSiN materials. We focus on the methodology needed for the interpretation and automatic analysis of the bonding structure, on the effect of the length of the calculation on the convergence of individual quantities of interest and on the electronic structure of materials. We show that the traditional form of the Wannier function center-based algorithm fails due to the presence of d electrons in the valence band. We propose a modified algorithm, which allows one to analyze bonding structure in TM-based systems. We observe an appearance of valence p states of TM atoms in the electronic spectra of such systems (not only ZrSiN but also NbO(x) and WAuO), and examine the importance of the p states for the character of the bonding as well as for facilitating the bonding analysis. The results show both the physical phenomena and the computational methodology valid for a wide range of TM-based ceramics.
A general relationship is derived for the abundance of an imperfect dendrimer with a given number of missing constitutional repeating units in the two outmost layers. The relationship is used in the interpretation of the MALDI TOF mass spectrum of the second-generation carbosilane dendrimer prepared by the iterative divergent method. The model quantitatively describes the spectrum of the dendrimer and correctly predicts the MALDI TOF mass spectrum of its first-generation precursor. Thus, the use of well-resolved MALDI TOF mass spectra for assessing the purity of low-generation dendrimers with uniform end groups is substantiated for carbosilane dendrimers and to lesser extent for dendrimers in general.
