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82 results for “Predictive Simulations”
Figure 4 from: Ha T-K-Q, Pham-Khanh N-H, Nguyen T-K (2024) Molecular docking screening, dynamics simulations, ADMET, and semi-synthesis prediction of flavones and flavonols from the COCONUT database as potent bifunctional neuraminidase inhibitors. Pharmacia 71: 1-10. https://doi.org/10.3897/pharmacia.71.e114967
Figure 4 Number of HBs and RMSD between N1-H274Y-oseltamivir protein (PDB ID: 3CL0) with three flavones 428, 581, and 864 (Fig. A–C, respectively) during dynamic simulation time 500 ns.
Figure 5 from: Ha T-K-Q, Pham-Khanh N-H, Nguyen T-K (2024) Molecular docking screening, dynamics simulations, ADMET, and semi-synthesis prediction of flavones and flavonols from the COCONUT database as potent bifunctional neuraminidase inhibitors. Pharmacia 71: 1-10. https://doi.org/10.3897/pharmacia.71.e114967
Figure 5 The proposed semi-synthesis of compound 864. (i) Column chromatography (70% EtOH: 18.64 mg.g−1) (ii) ClCH2COCl, K2CO3, DCM, rt, 8–24h; (iii) K2CO3/KI, acetone, reflux, 25–30 h.
Figure 2 from: Ha T-K-Q, Pham-Khanh N-H, Nguyen T-K (2024) Molecular docking screening, dynamics simulations, ADMET, and semi-synthesis prediction of flavones and flavonols from the COCONUT database as potent bifunctional neuraminidase inhibitors. Pharmacia 71: 1-10. https://doi.org/10.3897/pharmacia.71.e114967
Figure 2 2D interaction diagrams and 3D molecular docking of N1-H274Y-oseltamivir protein (PDB ID: 3CL0) with four flavones 428, 581, 864, and 948 (A–D, respectively) and two flavonols 162 and 218, (E, F, respectively).
Figure 3 from: Ha T-K-Q, Pham-Khanh N-H, Nguyen T-K (2024) Molecular docking screening, dynamics simulations, ADMET, and semi-synthesis prediction of flavones and flavonols from the COCONUT database as potent bifunctional neuraminidase inhibitors. Pharmacia 71: 1-10. https://doi.org/10.3897/pharmacia.71.e114967
Figure 3 3D molecular docking of bifunctional N inhibitor (compound 864) binding into the sialic acid binding cavity and the 430-cavity through the unique arginine triad Arg118-Arg292-Arg371 of N1-H274Y-oseltamivir protein (PDB ID: 3CL0).
Figure 1 from: Ha T-K-Q, Pham-Khanh N-H, Nguyen T-K (2024) Molecular docking screening, dynamics simulations, ADMET, and semi-synthesis prediction of flavones and flavonols from the COCONUT database as potent bifunctional neuraminidase inhibitors. Pharmacia 71: 1-10. https://doi.org/10.3897/pharmacia.71.e114967
Figure 1 Procedure of molecular docking screening and molecular dynamics of flavones and flavonols from COCONUT database.
Supplementary material 1 from: Ha T-K-Q, Pham-Khanh N-H, Nguyen T-K (2024) Molecular docking screening, dynamics simulations, ADMET, and semi-synthesis prediction of flavones and flavonols from the COCONUT database as potent bifunctional neuraminidase inhibitors. Pharmacia 71: 1-10. https://doi.org/10.3897/pharmacia.71.e114967
Supporting data
Simulation files for Highly accurate carbohydrate-binding site prediction with DeepGlycanSite
<p>Simulation files for Highly accurate carbohydrate-binding site prediction with DeepGlycanSite</p>
Data from: Analysis and prediction of effects of the Manchester Triage System on patient waiting times in an emergency department by means of agent-based simulation
A simulation of complex clinical processes is a challenging task and suitable methods need to be found which can capture the influence of relevant factors and their relationships. The Manchester triage system (MTS) is widely used in German emergency departments (ED), however the impact on patient waiting times remain difficult to predict. The purpose of this work is the assessment of MTS particularly with regard to the waiting times of different degrees of severity. The methodology of agent based simulation was found suitable for the ED domain and the agent based simulation tool SeSAm was chosen due to its intuitive user interface and easy adaption of the simulation models. Altogether four agent classes could be implemented based on the information derived from a process model. The model permits a dynamic simulation of the ED processes and a reliable assessment of patient waiting times. In addition, the implementation of a triage nurse allowed the simulation of the triage process and a direct comparison to the current state without a standardized triage procedure. Essential influencing factors (e.g. number of patients, manning level) were implemented and their effects on the ED processes and patient waiting times assessed. The simulation runs delivered correct results based on the underlying process model and the collected statistical data. The process flow and the waiting times of an ED could be mapped exactly. In all simulation runs the waiting times of high triage levels (MTS-levels 1 and 2) could be reduced. Especially patients of MTS-level 2 in the waiting area of the ED benefit significantly from the implementation of a standardized triage procedure and the associated permanent monitoring.
Molecular Dynamics Simulations of HADDOCK-predicted Complex Structures of apoE2 and Factor H
<p>Input and output data for the molecular dynamics simulations of the FH5–7/ApoE2 complex. Initial structures generated with the HADDOCK v2.4 web server with 3 nm distance restraints for lysine pairs that were experimentally found to be cross-linked with DSS. </p> <p>Five clusters and the four representative structures provided by HADDOCK were then used for atomistic molecular dynamics simulations. These structures were solvated and simulated with both CHARMM36m and Amber FF14SB force fields for 250 ns each using GROMACS 2021. The recommended simulation parameters were used for both force fields, and they are available in the mdp files. </p> <p>For each of these 5 (clusters) x 4 (structures per cluster) x 2 (force fields) = 40 simulations, the outputs and inputs are provided; the trajectory (xtc), energy file (edr), final structure (gro), run parameter file (tpr), and continue point (cpt) are system-specific, whereas a single topology (top) and index file (ndx) is shared among all simulations with the same force field. The molecule definitions (itp) referred to in the topology are provided in the compressed files.</p>
Data from: Analysis and prediction of effects of the Manchester Triage System on patient waiting times in an emergency department by means of agent-based simulation
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Data from: Phylodynamic model adequacy using posterior predictive simulations
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Data from: Simulated hatching failure predicts female plasticity in extra-pair behavior over successive broods
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Data from: Assessing the performance of DNA barcoding using posterior predictive simulations
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Data from: Robust regression and posterior predictive simulation increase power to detect early bursts of trait evolution
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The Observing-system Research and predictability experiment ER2 MODIS Airborne Simulator
THORPEX_ER2_MAS data are THe Observing-system Research and Predictability EXperiment (THORPEX) ER_2 MODIS Airborne Simulator (MAS) Data in HDF covering Hawaii and the Pacific Ocean.THe Observing-system Research and predictability experiment (THORpex) is a ten-year international research program where the primary objective is to accelerate improvements in short range weather predictions and warnings over the Northern Hemisphere. The fifth in an ongoing series of ER-2 field experiments, THORpex is the primary over-water validation experiment for the GIFTS (Geosynchronous Imaging Fourier Transform Spectrometer) satellite. The MODIS Airborne Simulator (MAS) is an airborne scanning spectrometer that acquires high spatial resolution imagery of cloud and surface features from its vantage point on-board a NASA ER-2 high-altitude research aircraft. The MAS spectrometer acquires high spatial resolution imagery in the range of 0.55 to 14.3 microns. A total of 50 spectral bands are available in this range. A 50-channel digitizer which records all 50 spectral bands at 12 bit resolution became operational in January 1995. The MAS spectrometer is mated to a scanner sub-assembly which collects image data with an IFOV of 2.5 mrad, giving a ground resolution of 50 meters from 20000 meters altitude, and a cross track scan width of 85.92 degrees.
Database of "Dynamic Design and Performance Prediction of Tuned Particle Damper Based on Co-simulation"
<p>These data are obtained based on the co-simulation of ADAMS and EDEM. The first 7 columns are inputs and the last column is output.</p>
Clinical Exploratory Study on Predicting Drug Sensitivity for Breast Cancer Treatment Using Simulated Organoid Models.
ClinicalTrials.gov study NCT06702800. IPD Sharing: NO. Countries: 1. Publications: 0.
Validation of Numerical Simulation to Predict Proximal Deployment of Standard Stents
ClinicalTrials.gov study NCT05944835. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Data from: The contribution of dominance to phenotype prediction in a pine breeding and simulated population
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Data related to the article "Molecular dynamics simulations for the prediction of thermophysical properties of plutonium-based molten salts"
<p>Contains input files and data used to generate the figures of the article:</p> <p>Molecular dynamics simulations for the prediction of thermophysical properties of plutonium-based molten salts<br>(Giovanni Pireddu*, Mirella Simoes Santos*, David Lambertin, Timothée Kooyman)<br><br>*:Equal contribution</p> <p>Journal of Nuclear Materials<br>DOI: https://doi.org/10.1016/j.jnucmat.2024.155124</p> <p>The folder EXAMPLE_INPUT_FILES contains typical MetalWalls(https://doi.org/10.21105/joss.02373) (repository(https://gitlab.com/ampere2/metalwalls)) input files used to perform the molecular simulations.</p> <p>The folder DATA_FIGURES contains the processed data used to plot the figures of the paper (see below).</p> <p><br>Figure 2:<br>- 'Fig2_Density.dat' : density as a function of temperature (binary system, calculated from MD simulations)</p> <p>Figure 3:<br>- 'Fig3_HCap.dat' : heat capacity as a function of temperature (binary system, calculated from MD simulations)</p> <p>Figure 4:<br>- 'Fig4_Density.dat' : density as a function of temperature (ternary system, calculated from MD simulations)</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.