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606 results for “Bioactivation”
Figure 3 in Partially purified Glycine max proteinase inhibitors: potential bioactive compounds against tobacco cutworm, Spodoptera litura (Fabricius, 1775) (Lepidoptera: Noctuidae)
Figure 3. Food assimilation (in mg) with respect to control when second-instar larvae of S. litura were given different concentrations of soybean PIs. Columns and bars represent the mean ± SE. Different letters above the columns representing each concentration indicate significant differences with Tukey's test at P ≤ 0.05.
Figure 2 in Partially purified Glycine max proteinase inhibitors: potential bioactive compounds against tobacco cutworm, Spodoptera litura (Fabricius, 1775) (Lepidoptera: Noctuidae)
Figure 2. Percentage survival of adults when second-instar larvae of S. litura were given different concentrations of soybean PIs. Columns and bars represent the mean ± SE. Different letters above the columns representing each concentration indicate significant differences with Tukey's test at P ≤ 0.05.
Figure 1 in Partially purified Glycine max proteinase inhibitors: potential bioactive compounds against tobacco cutworm, Spodoptera litura (Fabricius, 1775) (Lepidoptera: Noctuidae)
Figure 1. (A) Normal S. litura adult, (B–D) abnormality in adults observed at 100 µg/mL concentration of soybean PIs.
Figure 4 in Partially purified Glycine max proteinase inhibitors: potential bioactive compounds against tobacco cutworm, Spodoptera litura (Fabricius, 1775) (Lepidoptera: Noctuidae)
Figure 4. Trypsin activity in larvae of S. litura at different time intervals under the influence of partially purified soybean PIs.
Dataset - Papyrus - A large scale curated dataset aimed at bioactivity predictions
<p><strong>Fixed version of additional_files:</strong></p> <p><strong>- In the previous version of 05.6_additional_files</strong> the data type of some descriptors was assigned incorrectly</p> <p><strong>- In this fixed version </strong>data types are correct </p> <p>This repository contains version 05.6 of the Papyrus dataset, an aggregated dataset of small molecule bioactivities, as described in the article "Papyrus - A large scale curated dataset aimed at bioactivity predictions" doi.org/10.1186/s13321-022-00672-x.</p> <p>Changes compared to version 05.5</p> <p>- applied small molecule filter that filters out compounds with a MW < 200 or > 800, heavy metal containing compounds and mixtures</p> <p>- include TID column which contains information on the original protein identifier</p>
Fingerprint Matrix Files for "Machine Learning-based Bioactivity Classification of Natural Products Using LC-MS/MS Metabolomics"
<p>These files are the necessary dataset to reproduce the observed machine learning metrics in the paper "Machine Learning-based Bioactivity Classification of Natural Products Using LC-MS/MS Metabolomics" in review at the Journal of Natural Products. </p> <ul> <li>Multiclassifier_23_Drug_Class_Train-Test_Fingerprint_Matrix.tsv is the accumulated positive training set for the 23 different classes demonstrated in the training and testing sets.</li> <li>Negative_Train-Test_Fingerprint_Matrix.tsv is the negatives training and testing examples derived from the RIKEN NP Depo which represent a diverse set of natural product compounds that serve as the counter points to the positive examples.</li> <li>GNPS_23_Drug_Class_Fingerprints_Matrix.tsv is the dataset of fingerprints generated from the publically available GNPS MSMS dataset. These training examples serve to confirm the ability of the machine learning model to generalize to experimental data. </li> <li> Negative_Train-Test_Fingerprint_Matrix.tsv is the dataset of negative training examples derived from the publically available spectra from the GNPS dataset. It is composed of nearly 2,800 random MSMS spectra to compose a diverse negative evaluation set. </li> <li>Random_GNPS_Fingerprints.tsv is the dataset of fingeprints of 9,443 random spectra from GNPS used to evaluate the false positive rate of each model.</li> </ul>
Making sense of large-scale kinase inhibitor bioactivity data sets: a comparative and integrative analysis
<p>We carried out a systematic evaluation of target selectivity profiles across three recent large-scale biochemical assays of kinase inhibitors and further compared these standardized bioactivity assays with data reported in the widely used databases ChEMBL and STITCH. Our comparative evaluation revealed relative benefits and potential limitations among the bioactivity types, as well as pinpointed biases in the database curation processes. Ignoring such issues in data heterogeneity and representation may lead to biased modeling of drugs' polypharmacological effects as well as to unrealistic evaluation of computational strategies for the prediction of drug-target interaction networks. Toward making use of the complementary information captured by the various bioactivity types, including IC50, K(i), and K(d), we also introduce a model-based integration approach, termed KIBA, and demonstrate here how it can be used to classify kinase inhibitor targets and to pinpoint potential errors in database-reported drug-target interactions. An integrated drug-target bioactivity matrix across 52,498 chemical compounds and 467 kinase targets, including a total of 246,088 KIBA scores, has been made freely available.</p> <p>Please cite: </p> <p>https://pubmed.ncbi.nlm.nih.gov/24521231/ </p> <p>https://pubs.acs.org/doi/10.1021/ci400709d</p>
Data underlying the article: 3DDPDs: Describing protein dynamics for proteochemometric bioactivity prediction. A case for (mutant) G protein-coupled receptors
<p>This repository contains the datasets and results supporting the conclusions of the manuscript "<strong>3DDPDs: Describing protein dynamics for proteochemometric bioactivity prediction. A case for (mutant) G protein-coupled receptors</strong>". </p> <p>Publicly available data is not included in this repository. The source code to generate the results gathered here can be found on GitHub (https://github.com/CDDLeiden/3ddpd). </p>
Bioactive compound classes from ChEMBL20 for molecular hierarchy
<p>Compound structure, scaffold, and CSK of 78,150 (all) and 54,042 (only compounds with a scaffold shared by at least one another compound) compounds, respectively, are provided herein. In addition, each compound is annotated with target and potency information.</p>
Bioactive compounds from Crataegus Oxycantha Protects myocardium against important proteins of atherosclerosis. An in-depth analysis using molecular simulation studies
<p>We are submitting this data as a raw file for the submission of our manuscript to the peer reviwed journals. </p>
Extraction, Chemical Characterization and Antioxidant Activity of Bioactive Plant Extracts
<p>Recording of the talk “Extraction, chemical characterization and antioxidant activity of bioactive plant extracts”, presented by Beatriz Nunes Silva at the 1st International Electronic Conference on Food Science and Functional Foods; MDPI Foods. Online virtual meeting (10-25 Nov 2020).</p>
Umbrella review data of colour-associated bioactive pigments found in fruit and vegetables, compared to placebo or low intakes, on human health outcomes relevant to public health
<p>This dataset comprises data extracted from 86 publications included in an umbrella review which compared the effect of colour-associated bioactive pigments found in fruit and vegetables (carotenoids, flavonoids, betalains and chlorophyll) on human health outcomes relevant to public health. Meta-analysed data from 83 systematic literature reviews were available for 17 different bioactive pigments spanning all colours of fruit and vegetables except green, with additional data from two randomised controlled trials and one cohort study for chlorophyll. This dataset represents 2,847 original research studies and data from over 37 million participants. There were 449 meta-analysed health outcomes extracted from the 83 systematic literature reviews. Extracted health outcomes were categorised according to pigment, comparator type, broad health outcome, study design, age group, source of pigment, risk of bias, and confidence in the estimated effect. Data extracted were dose, intervention duration, sample size, number of original studies, effect estimate, 95% confidence intervals, I2 statistics, publication bias and p-value. Rigorous analysis, including estimations of a common effect size, stratification of the evidence, study level sensitivity analyses and reporting on heterogeneity and potential biases, may be carried out using these data, to further evaluate the effect of colour-associated bioactive pigments in fruit and vegetables on human health.</p>
Data underlying the article: "Excuse me, there is a mutant in my bioactivity soup! A comprehensive analysis of the genetic variability landscape of bioactivity databases and its effect on activity modelling"
<p>This repository contains the data underlying the article: “Excuse me, there is a mutant in my bioactivity soup! A comprehensive analysis of the genetic variability landscape of bioactivity databases and its effect on activity modelling” available as a preprint on ChemRxiv.</p> <p>Main authors: Marina Gorostiola González & Olivier J.M. Béquignon (Leiden University)</p> <p>Senior author: Gerard J.P. van Westen (Leiden University)</p> <p>This analysis was performed using the code available at <a href="https://github.com/CDDLeiden/chembl_variants" target="_blank" rel="noopener">https://github.com/CDDLeiden/chembl_variants</a></p>
Bioprospecting for bioactive peptide production by lactic acid bacteria isolated from fermented dairy food
<p>Table S1 of the review article "Bioprospecting for bioactive peptide production by lactic acid bacteria isolated from fermented dairy food"</p> <p>by Davide Tagliazucchi, Serena Martini and Lisa Solieri</p>
A bioactive compound isolated from Duku (Lansium domesticum Corr) fruit peels exhibits cytotoxicity against T47D cell line
<p><strong>Background: </strong>Breast cancer is a major health problem for women globally. Many attempts have been promoted to cure cancer by finding new anticancer medicines from natural resources. Despite the richness of biodiversity discovered, there are some natural resources that remain unexplored. Fruit peels of Duku (<em>Lansium domesticum</em> Corr.) are rich with compounds that may have the potential to be developed as anticancer drugs. This study aimed to isolate cytotoxic compounds from the fruit peels of <em>L. domesticum</em> and assess their cytotoxic nature against T47D cells.</p> <p><strong>Methods: </strong>Powdered peels were macerated with ethyl acetate and the filtrate was evaporated to give EtOAc extract A. Dried extract A was triturated with n-hexane to give n-hexane soluble fraction B and insoluble fraction C. The cytotoxic nature of these three samples were assessed using MTT assay using T47D cells and doxorubicin as a control</p> <p><strong>Results: </strong>Fraction C that showed the smallest IC<sub>50</sub> (25.56 + 0.64µg/mL) value compared to extract A and fraction BFraction C was further fractionated by vacuum liquid chromatography to give 6 subfractions. Subfraction 2 showed a single compound based on thin layer chromatography, and this compound was identified as Lamesticumin A on the basis of its spectroscopic data. Lamesticumin A demonstrated cytotoxic activity against T47D cell lines with an IC<sub>50</sub> value of 15.68 + 0.30µg/mL.</p>
Fig. 1 in Chemical composition and bioactivity of the essential oil from Artemisia lavandulaefolia (Asteraceae) on Plutella xylostella (Lepidoptera: Plutellidae)
Fig. 1. Repellent activity of Artemisia lavandulaefolia essential oil to Plutella xylostella.
Comparison of the phytochemical composition and bioactivity of the latex of Hura crepitans L. from Peru and Africa by metabolomic approaches
<p><em><span>Hura crepitans</span></em><span> <span> </span>(Euphorbiaceae), is widespread in the Amazon rainforest and on plantations in sub-Saharan Africa. This tree produces an irritating milky latex rich in secondary metabolites, notably daphnane-type diterpenes and cerebrosides. Previous studies have shown that huratoxin, the main daphnane in the latex, significantly and selectively inhibited the growth of colorectal cancer cells through a unique mechanism involving the activation of PKCζ. One major challenge in isolating active molecules from natural products is the accessibility of the resource. This study explores the phytochemical composition and cytotoxic activities of latexes collected in Peru, Benin, and Togo using UHPLC-MS and metabolomics tools to identify a renewable source of bioactive compounds. Significant inter- and intra-continental differences in chemical composition have been highlighted, with daphnanes being concentrated in the Peruvian samples. Extracts form latexes collected in Peru showed cytostatic activity on Caco-2 cells, correlated with the presence of daphnanes, while some African samples exhibited cytotoxic activity on Jurkat and Hela cancer cell lines, leading to the identification of potential other new bioactive compounds such as sterol and cerebrosides.</span></p> <p><span> </span></p>
Data described in the article "Three-step enzymatic remodeling of chitin into bioactive chitooligomers"
<p>The Supporting Information file contains the following data: <span>PCR primers and reaction conditions for the generation of <em>Tf</em>Chit mutants; HPLC chromatogram of chitin hydrolysate; detailed sequence alignment; computational data; additional figures for modeling of <em>Tf</em>Chit;</span><span> <span>MALDI-TOF MS analysis of a mixture of insoluble chitooligomers prepared by Y445N <em>Ao</em>Hex, and <em>m/z</em> values monitored by HPLC-MS of the deacetylation reactions.</span></span></p>
Primary data for Manuscript provisionally titled Stereoselective access to bioactive cyclopropanes (+)-PPCC and (1R,2S)-2-aminomethyl-1-arylcyclopropane-1-carboxamides from (−)-levoglucosenone
<p><span>Contains HRMS and FID data for compounds described in the manuscript titled, "<span>Stereoselective access to bioactive cyclopropanes (+)-PPCC and (1<em><span>R</span></em>,2<em><span>S</span></em>)-2-aminomethyl-1-arylcyclopropane-1-carboxamides from (−)-levoglucosenone"</span></span></p> <p><span>FIDs can be opened using SpinWorks or Topspin programs.</span></p> <p> </p>
Novel Insights into the Bioactive Metabolites of Macrocybe gigantea (Massee) Pegler & Lodge, a Wild Edible Macrofungi Using Gas Chromatography Mass Spectrometry (GC-MS) Combined with Chemoinformatics Approaches
<p><em>Macrocybe gigantea </em>(MG) is an edible mushroom and has multiple pharmacological activities such as antibacterial, antioxidant, and antitumor activities. However, only a few reports were available on the bioactive compounds and bioactivity of this mushroom. In this concern, the present study was aimed to explore the unique chemical diversity from the fruiting body of MG<em>. </em>The species identification was done accurately with morphological and molecular methods followed by mycochemical extraction in different solvent systems. The ethanolic extract of the fruiting body gave maximum yield and its Gas Chromatography-Mass Spectrometry (GC-MS) analysis was performed along with antibacterial activity and cell viability by MTT assay. The GC-MS analysis revealed 50 metabolites and further chemoinformatics analysis of these metabolites revealed their possible biological activities. In addition, the mushrooms' physico-chemical and mineral element analysis revealed the quality and authenticity of the species. Altogether, the current investigation gives a comprehensive overview of the bioactive metabolites of MG.</p>
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International Brain Laboratory public data
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OpenNeuro
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