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8 results for “conformational energy”
Free energy simulations of receptor-binding domain opening in the SARS-CoV-2 spike indicate a barrierless transition with slow conformational motions
<p>This online data set accompanies the manuscript entitled "Free energy<br> simulations of receptor-binding domain opening in the SARS-CoV-2 spike<br> indicate a barrierless transition with slow conformational motions."</p> <p>The dataset is composed of the following files:</p> <p>* pmf0-now.dcd -- pmf63-now.dcd : molecular dynamics trajectory frames in<br> each of the 64 umbrella sampling windows, from which water has been<br> removed to save space</p> <p>* s1am_0-now.pdb -- s1am_63-now.pdb : initial coordinates in each of the 64<br> umbrella sampling windows, from which water has been removed,<br> corresponding to the trajectory data above</p> <p>* view -- Visual Molecular Dynamics command script to load a trajectory, <br> e.g., in Linux, use "vmd -e view"</p> <p>* s1am_0-cg.dcd -- s1am_63-cg.dcd : molecular dynamics<br> trajectory frames in each of the 64 umbrella sampling windows, coarse-grained to<br> 1 bead per residue.</p> <p>* s1am_0-cg.pdb -- s1am_63-cg.pdb : initial coordinates in each of the 64<br> umbrella sampling windows, corresponding to the coarse-grained trajectory<br> data above.</p> <p>* viewcg -- Visual Molecular Dynamics command script to load a<br> coarse-grained trajectory, e.g., in Linux, use "vmd -e viewcg"</p> <p>* 0readme -- brief instructions on how to view the trajectories</p> <p>* colors.vmd -- utility script for VMD</p> <p>* covmacros.vmd -- VMD script to define coronavirus spike subdomains</p> <p>* fe.zip -- ZIP archive that contains data and Matlab analysis files to<br> reproduce the free energy profiles</p> <p>* diff.zip -- ZIP archive that contains data and Matlab analysis files to<br> reproduce the diffusion and mean first passage times calculations</p> <p>* pca-qha.zip -- ZIP archive that contains the data and Matlab analysis files<br> to compute the autocorrelation functions of trajectory displacements<br> along principal/quasiharmonic modes</p> <p>Each ZIP archive contains a "0readme" file with brief instructions, and also the <br> results of the calculations<br> </p>
Dataset: 800 QM/MM minimum energy pathway conformations for the acylation reactions of Toho-1/ampicillin and Toho-1/cefalexin
<p>This dataset consists of 800 coordinate files (in the CHARMM psf/cor format) for the QM/MM minimum energy pathways of the acylation reactions between a Class A beta-lactamases (Toho-1) and two beta-lactam antibiotic molecules (ampicillin and cefalexin).</p> <p>These files are:</p> <ul> <li>toho_amp.r1-ae.zip: The R1-AE acylation pathways for Toho-1/Ampicillin (200 pathways);</li> <li>toho_amp.r2-ae.zip: The R2-AE acylation pathways for Toho-1/Ampicillin (200 pathways);</li> <li>toho_cex.r1-ae.zip: The R1-AE acylation pathways for Toho-1/Cefalexin (200 pathways);</li> <li>toho_cex.r2-ae.zip: The R2-AE acylation pathways for Toho-1/Cefalexin (200 pathways);</li> <li>energies.zip: the replica energies at B3LYP-D3/6-31+G**/C36 level;</li> <li>chelpgs.zip: the ChElPG charges of all reactant replicas at B3LYP-D3/6-31+G**/C36 level;</li> <li>farrys.zip: the featurzied NumPy arrays for model training;</li> <li>peephole.zip: an example file for how the optimized MEPs look like; </li> <li>dftb3_benchmark.zip: the reference calculations to justify the use of DFTB3/3OB-F/C36 in MEP optimizations, the reference level of theory is B3LYP-D3/6-31G**/C36. </li> </ul> <p>The R1-AE pathways are the acylation uses Glu166 as the general base; the R2-AE pathways uses Lys73 and Glu166 as the concerted base. </p> <p>All QM/MM pathways are optimized at the DFTB3/3OB-f/CHARMM36 level of theory. </p> <p>Z. Song et al Mechanistic Insights into Enzyme Catalysis from Explaining Machine-Learned Quantum Mechanical and Molecular Mechanical Minimum Energy Pathways. <em>ACS Phys. Chem Au</em> 2022, <strong>2</strong>, 4, 316–330. DOI: <a href="https://doi.org/10.1021/acsphyschemau.2c00005">10.1021/acsphyschemau.2c00005</a></p>
CH3CH2OCH3 conformer molecule 200 ps MD trajectory with energies and forces
<p>Forces and Energies for 200 ps MD trajectory of OCH2C2H6 molecule by xTB/GFN-2, NVE ensemble</p> <p>--------------------------------------------------</p> <p>MD params:</p> <p>temp = 300.0 K / 500.0 K<br> time = 200.0 ps<br> dump time = 10.0 fs<br> step = 0.4 fs</p> <p> </p> <p>SOAP params:</p> <p>species=["H", "C", "O"],</p> <p>periodic=False,</p> <p>rcut=5.0,</p> <p>sigma=0.5,</p> <p>nmax=5,</p> <p>lmax=5,</p> <p>average="outer" / "inner",</p> <p>crossover=True,</p> <p>dtype="float64",</p> <p>------------------------------------------------</p> <p>SOAP invariants were calculated with DScribe library (https://pypi.org/project/dscribe/1.2.1/)</p> <p> </p> <p>Energies and forces are in eV and eV/Angstrom</p> <p>Filenames are intended to be self-explanatory</p> <p>Dataset is intended to be used for machine learning algorithms tests.</p>
Dataset for "ConfSolv: Prediction of solute conformer free energies across a range of solvents"
<p>This dataset contains three archives. The first archive, full_dataset.zip, contains geometries and free energies for nearly 44,000 solute molecules with almost 9 million conformers, in 42 different solvents. The geometries and gas phase free energies are computed using density functional theory (DFT). The solvation free energy for each conformer is computed using COSMO-RS and the solution free energies are computed using the sum of the gas phase free energies and the solvation free energies. The geometries for each solute conformer are provided as ASE_atoms_objects within a pandas DataFrame, found in the compressed file dft coords.pkl.gz within full_dataset.zip. The gas-phase energies, solvation free energies, and solution free energies are also provided as a pandas DataFrame in the compressed file free_energy.pkl.gz within full_dataset.zip. Ten example data splits for both random and scaffold split types are also provided in the ZIP archive for training models. Scaffold split index 0 is used to generate results in the corresponding publication. </p><p>The second archive, refined_conf_search.zip, contains geometries and free energies for a representative sample of 28 solute molecules from the full dataset that were subject to a refined conformer search and thus had more conformers located. The format of the data is identical to full_dataset.zip.</p><p>The third archive contains one folder for each solvent for which we have provided free energies in full_dataset.zip. Each folder contains the .cosmo file for every solvent conformer used in the COSMOtherm calculations, a dummy input file for the COSMOtherm calculations, and a CSV file that contains the electronic energy of each solvent conformer that needs to be substituted for "EH_Line" in the dummy input file.</p>
Dataset: 1,000 QM/MM minimum energy pathway conformations for the deacylation reactions of GES-5/imipenem
<p>This dataset consists of 1,000 coordinate files (in the CHARMM psf/cor format) for the QM/MM minimum energy pathways of the deacylation reactions between a Class A beta-lactamases (GES-5) and the imipenem antibiotic molecules.</p> <p>All pathway conformations were optimized at DFTB3/3OB-f/CHARMM36 level with 36 replicas.</p> <p>All single point calculations and charge population analysis were done at B3LYP-D3/6-31+G(d,p)/CHARMM36 level.</p> <ul> <li>0.paths_ges_imi_d1.tar.gz: 500 pathway conformations for GES-5/IPM-Delta1 deacylation reactions.</li> <li>0.paths_ges_imi_d2.tar.gz: 500 pathway conformations for GES-5/IPM-Delta1 deacylation reactions.</li> <li>1.eners.zip: The single point replica energies along all GES-5/IPM pathways.</li> <li>1.chrgs.zip: The NBO charges of the QM region of all replica conformations along all GES-5/IPM pathways.</li> <li>2.datasets.zip: The Python codes to postprocess the molecular data and the featurized the NumPy arrays.</li> <li>3.gnn.zip: The Python codes that implements the edge-conditioned graph convolutional NN to predict the deacylation barriers.</li> <li>5.representative_conf.zip: The pathway conformations of all cluster centroids and an energetic representative (pathway id 22) pathway. Note: This file also serves as a peephole of how the pathway conformations from Reaction Path with Holonomic Constrains calculations looks like.</li> <li>6.benchmark.zip: The benchmark calculations that validates the DFTB3/3OB-f/CHARMM36 against DFTB3/3OB/CHARMM36 and B3LYP/6-31G(d,p)/CHARMM36 level of theory on the energetic representative (pathway id 22) pathway conformations. </li> <li>p.figures.zip: A series of Jupyter Notebooks that produces the visualizations in the work.</li> <li>README.md: A markdown file that contains additional descriptions.</li> <li>environment.yml: The Conda environment used for the graph-learning. </li> </ul> <p>Z. Song and P. Tao, Graph-Learning Guided Mechanistic Insights into Imipenem Hydrolysis in GES Carbapenemases. <strong><em>Electron. Struct.</em></strong> 2022, <strong>4</strong>, 034001. DOI: <a href="https://doi.org/10.1088/2516-1075/ac7993">10.1088/2516-1075/ac7993</a></p>
Benchmarking the ability of GFB1-xTB to determine relative energies of conformers in small organic molecules
Open the record for dataset details and reuse information.
Energy Landscape of the Sugar Conformation Controls the Sol-to- Gel Transition in Self-Assembled Bola Glycolipid Hydrogels
<p>Self-assembled fibrillar network (SAFIN) hydrogels and organogels are commonly obtained by a crystallization process into fibers induced by external stimuli like temperature or pH. The gel-to-sol-to-gel transition is generally readily reversible and the change rate of the stimulus determines the fiber homogeneity and eventual elastic properties of the gels. However, recent work shows that in some specific cases, fibrillation occurs for a given molecular conformation and the sol-to-gel transition depends on the relative energetic stability of one conformation over the other, and not on the rate of change of the stimuli. We observe such a phenomenon on a class of bolaform glycolipids, sophorosides, similar to the well-known sophorolipid biosurfactants, but composed of two symmetric sophorose units. A combination of oscillatory rheology, small-angle X-ray scattering (SAXS) cryogenic transmission electron microscopy (cryo-TEM) and <em>in situ</em> rheo-SAXS using synchrotron radiation shows that below 14°C, twisted nanofibers are the thermodynamic phase. Between 14°C and about 33°C, nanofibers coexist with micelles and a strong hydrogel forms, the sol-to-gel transition being readily reversible in this temperature range. However, above the annealing temperature of about 40°C, the micelle morphology becomes kinetically-trapped over hours, even upon cooling, whichever the rate, to 4°C. A combination of solution and solid-state nuclear magnetic resonance (NMR) suggests two different conformations of the 1ˈˈ, 1ˈ and 2ˈ carbon stereocenters of sophorose, precisely at the β(1,2) glycosidic bond, for which several combinations of the dihedral angles are known to provide at least three energetic minima of comparable magnitude and each corresponding to a given sophorose conformation.</p>
Using Metadynamics to Reveal Extractant Conformational Free Energy Landscapes
<p>Input scripts for the simulations</p>
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