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55 results for “Cyclodextrines”
Dataset for "Exploring the Potential of Various Cyclodextrin-based Derivatives in Enzyme Supramolecular Engineering" research article
<p>The dataset for the paper titled "Exploring the Potential of Various Cyclodextrin-based Derivatives in Enzyme Supramolecular Engineering".<br>The dataset includes the following items:<br><br>1. "alpha-CD-TES_Characterization" xls file (1 file) including 5 datasheets;<br>These data sheets provide raw characterization data regarding the synthesis of the alpha-CD-TES molecule including 1H NMR, 13C NMR, FTIR, ESI-MS, and MALDI.</p> <p>2. "beta-CD-TES_Characterization" xls file (1 file) including 5 datasheets;<br>These data sheets provide raw characterization data regarding the synthesis of the beta-CD-TES molecule including 1H NMR, 13C NMR, FTIR, ESI-MS, and MALDI.</p> <p>3. "gamma-CD-TES_Characterization" xls file (1 file) including 5 datasheets;<br>These data sheets provide raw characterization data regarding the synthesis of the gamma-CD-TES molecule including 1H NMR, 13C NMR, FTIR, ESI-MS, and MALDI.<br><br>4. "Activities" xls file (1 file) including 6 datasheets;<br>These datasheets contain the raw data of the enzymatic activities measured for both LipMRD9 and A50 enzymes for each set of stability experiments reported in the manuscript or the supporting information documents.</p> <p>5. "Layer growth - A50" zip file including 5 files:<br>The unprocessed SEM micrographs of A50 enzyme shielding with alpha/beta/gamma-CD-TES building blocks (after 75 min reaction) and the corresponding size measurements in an xls file.</p> <p>6. "Layer growth - LipMRD9" zip file including 15 files:<br>The unprocessed SEM micrographs of the shielded LipMRD9 enzyme with α-, β-, and γ-CD-TES building blocks (after 30, 60, 90, and 120 min reaction) and the corresponding size measurements (using ImageJ software) saved in separate xls files.</p>
Stereoisomers are not Machine Learning's Best Friends: Experimental results of the prediction of the association constant between a cyclodextrin and a guest with Stereo2vec
<p>This study addresses the challenge of accurately identifying stereoisomers in cheminformatics which originates from our objective to apply machine learning to predict association constant between a cyclodextrin and a guest. Identifying stereoisomers is indeed crucial for machine learning applications. Current tools offer various molecular descriptors, including their textual representation as Isomeric SMILES which can distinguish stereoisomers. But such representation is text-based and does not have a fixed size, so a conversion is needed to make it usable to machine learning approaches. Word embedding techniques can be used to solve this problem. Mol2vec, a word embedding approach for molecules, offers such a conversion. Unfortunately, it cannot distinguish between stereoisomers due to its inability to capture the spatial configuration of molecular structures. This study proposes several approaches that use word embedding techniques to handle molecular discrimination using stereochemical information of molecules or considering Isomeric SMILES notation as a text in Natural Language Processing. Our aim is to generate a distinct vector for each unique molecule, correctly identifying stereoisomer information in cheminformatics. The proposed approaches are then compared on our original machine learning task: predicting the association constant between a cyclodextrin and a guest molecule.</p>
Data - Host-guest dynamic behavior of melatonin encapsulated in beta-cyclodextrin nanosponges
<p>Amber topologies, input coordinates and MD trajectories for the simulations of:</p> <ul> <li>free melatonin in solution (gaff2+TIP3P)</li> <li>free beta-cyclodextrin in solution (GLYCAM-06j+TIP3P, GLYCAM-06j+OPC, GLYCAM-06j+OPC3)</li> <li>melatonin:beta-cyclodextrin monomeric inclusion complex in solution from three starting geometries (linear, folded1, and folded2) in solution (GLYCAM-06j+TIP3P+gaff2).</li> <li>nanopsonge models with acyclic (ns3, ns4, and ns5) and cyclic (ns5c and ns7c) topologies resulting from beta-cyclodextrin crosslinking with citric acid, in solution (GLYCAM-06j+TIP3P+gaff2).</li> <li>the same nanosponge models (3MT-ns3, 4MT-ns4, 5MT-ns5, 5MT-ns5c, and 7MT-ns7c) loaded with melatonin with 1:1 melatonin:beta-cyclodextrin ratio, in solution (GLYCAM-06j+TIP3P+gaff2).</li> </ul> <p>All MD trajectories are saved with an even stride of 10 ns.</p>
Characterization of bakuchiol-β-cyclodextrin inclusion complexes and their pH-dependent formation
Open the record for dataset details and reuse information.
Dosage de la beta-cyclodextrine par complexation du bleu de méthylène - jeu de données
<p>Data set of absorption and fluorescence of complexes of methylene blue and beta-cyclodextrines</p>
Curated Dataset of Association Constants Between a Cyclodextrin and a Guest for Machine Learning: Raw Data and Generation Script
<p>Determining the association constant between a cyclodextrin and a guest molecule is an important task for various applications in various industrial and academical fields. However, such a task is time consuming, tedious and requires samples of both molecules. A significant number of association constants and relevant data is available from the literature. The availability of data makes the use of machine learning techniques to predict association constants possible. However, such data is mainly available from tables in articles or appendices. It is necessary to make them available in a computer friendly format and to curate them. Furthermore, the raw data need to be enriched with physicochemical information about each molecule and when such information does not allow to discriminate molecules, some additional data is needed. We present a dataset built from data gathered from the literature. The dataset contains both the original raw data from the articles and the enriched ones. We also provide the scripts used to curate and enrich the raw data.</p>
Evaluation of Oral Alpha-Cyclodextrin for Decreasing Serum Cholesterol
ClinicalTrials.gov study NCT01131299. IPD Sharing: UNDECIDED. Countries: 1. Publications: 4.
Atomically resolved imaging of the conformations and adsorption geometries of individual β-cyclodextrins with non-contact AFM
<p>Raw data for publication titled <em>Atomically resolved imaging of the conformations and adsorption geometries of individual β-cyclodextrins with non-contact AFM.</em></p>
Étude thermodynamique de la captation de la phénolphtaléine par les beta-cyclodextrines (spectres d'absorbance)
<p>Spectres d'absorbances avec et sans la cyclodextrine, en fonction de la température.</p>
Fig. 5 in Magnetic Ti C MXene functionalized with β-cyclodextrin as magnetic solid-phase extraction and in situ derivatization for determining 12 phytohormones in oilseeds by ultra-performance liquid chromatography-tandem mass spectrometry
Fig. 5. Spatio-temporal distribution of target phytohormones in different tissue of rapeseed germination.
Fig. 2 in Magnetic Ti C MXene functionalized with β-cyclodextrin as magnetic solid-phase extraction and in situ derivatization for determining 12 phytohormones in oilseeds by ultra-performance liquid chromatography-tandem mass spectrometry
Fig. 2. XRD spectrum (a), FI-TR pattern (b), Raman spectrum (c) of the composite material, and magnetization hysteresis loop of Fe3O4@Ti3C2@β-CD (d).
Fig. 1 in Magnetic Ti C MXene functionalized with β-cyclodextrin as magnetic solid-phase extraction and in situ derivatization for determining 12 phytohormones in oilseeds by ultra-performance liquid chromatography-tandem mass spectrometry
Fig. 1. Schematic of the synthetic route for Fe3O4@Ti3C2@β-CD and the sample pre-treatment procedure.
Fig. 4 in Magnetic Ti C MXene functionalized with β-cyclodextrin as magnetic solid-phase extraction and in situ derivatization for determining 12 phytohormones in oilseeds by ultra-performance liquid chromatography-tandem mass spectrometry
Fig. 4. Effects of different cleanup sorbents (a), effects of the amount of magnetic solid-phase extraction sorbents (b), effects of the simultaneous derivatization and magnetic solid phase extraction time (c), effects of the desorption time (d). 5 mg rapeseed spiked with 10 ng/g of each analyte.
Fig. 3 in Magnetic Ti C MXene functionalized with β-cyclodextrin as magnetic solid-phase extraction and in situ derivatization for determining 12 phytohormones in oilseeds by ultra-performance liquid chromatography-tandem mass spectrometry
Fig. 3. SEM image of Ti3C2 (a) and Fe3O4@Ti3C2@β-CD (b), TEM image of Ti3C2(c) and Fe3O4@Ti3C2@β-CD (d), elemental mapping and chemical composition of Fe3O4@Ti3C2@β-CD (e).
Hydroxypropyl Beta Cyclodextrin for Niemann-Pick Type C1 Disease
ClinicalTrials.gov study NCT01747135. IPD Sharing: NO. Countries: 1. Publications: 6.
Effect of Gamma-cyclodextrin on the Bioavailability of Ginsenosides
ClinicalTrials.gov study NCT04932265. IPD Sharing: Not stated. Countries: 2. Publications: 9.
The Effect of Oral Alpha-Cyclodextrin on Fecal Fat Excretion
ClinicalTrials.gov study NCT01910558. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Effect of Gamma-cyclodextrin on the Bioavailability of Berberine
ClinicalTrials.gov study NCT04918667. IPD Sharing: NO. Countries: 2. Publications: 7.
Insulin Complexation With Hydroxypropyl-beta-cyclodextrin: Use of the Complex in Gel for Healing of Pressure Ulcers
ClinicalTrials.gov study NCT02418676. IPD Sharing: Not stated. Countries: 0. Publications: 3.
Determining Lipid Content in Stool After Alpha-cyclodextrin
ClinicalTrials.gov study NCT03002168. IPD Sharing: YES. Countries: 1. Publications: 1.
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