Find research datasets worth reusing

opencc-by-4.0Aug 2021View details →

Simulation systems of: "Free energies of membrane stalk formation from a lipidomics perspective"

Simulation systems of: Free energies of membrane stalk formation from a lipidomics perspective Chetan S. Poojari, Katharina C. Scherer, Jochen S. Hub Nature Communications, 12,  6594 (2021), <a href="https://doi.org/10.1038/s41467-021-26924-2">https://doi.org/10.1038/s41467-021-26924-2</a>   First published as  a preprint manuscript in BioRxiv as: Free energies of stalk formation in the lipidomics era Chetan S. Poojari, Katharina C. Scherer, Jochen S. Hub, BioRxiv, https://www.biorxiv.org/content/10.1101/2021.06.02.446700v1, 2021 The archive contains <ul> <li>starting conformations of double-membrane systems</li> <li>topologies</li> <li>MD parameter files</li> </ul> Running the simulations requires a modified version of GROMACS, which implements the chain coordinate available at GitLab: <a href="https://gitlab.com/cbjh/gromacs-chain-coordinate">https://gitlab.com/cbjh/gromacs-chain-coordinate</a>

opencc-by-4.0Nov 2022View details →

Free Energy Differences from Molecular Simulations: Exact Confidence Intervals from Transition Counts

Supporting data for Free Energy Differences from Molecular Simulations: Exact Confidence Intervals from Transition Counts Molecular simulations make it possible to predict equilibrium constants and corresponding free energy differences. For a system that exists in two states A and B, the equilibrium constant K can be predicted as K = t_B / t_A, where t_B and t_A are times spent in states B and A, respectively. The free energy can be calculated as Delta G = -kT log(K). Here we propose a new method for calculation of confidence intervals for K and Delta G. The ratio of the true value of K and estimated K follows the F-distribution with degrees of freedom df1 = number of B to A transitions and df2 = number of A to B transitions. This makes it possible to calculated the confidence interval of K solely from the number of transitions. The code in the directory errors was used to calculate Table 1 of the article. The code in the directory type1error was used to generate 10000 first time passage times for a transition from A to B and B to A as random numbers with exponential distribution. This was done for different combinations of number of transition and values of K. Number of confidence intervals not spanning the predefined value of K (type 1 errors) was expected to be 5 % for 95-% confidence intervals. This was in agreement with the result. The code in the directory type1errorodd was used to run similar experiment as type1error, but with number of A to B transitions higher than B to A by one. The code in the directory threestates was used to run similar experiment as type1error and  type1errorodd but for a system with three states A, B and C. The directory glycerol contains a trajectory, evolution of values of torsion angles and the code for analysis of the simulation of glycerol in water. The directory ffmp contains evolution of values of RMSD from the native structure, manual assignments of folded and unfolded states and the code for analysis of simulations of fast folding miniproteins (original data from Lindorf-Larsen et al. Science 2011, 334(6055) 517-520). The directory se contains the code for calculation of standard errors numerically and by the method presented in the article. The directory parallel presents the code for calculations supporting our method to calculate rate and equilibrium constants in parallel simulations. Codes written in R were executed using R version 3.4.4 by running: $ R –no-save < code.R > code.log File md5sums contains md5sum codes for all files.

opencc-by-4.0Jun 2023View details →

Extended ensemble molecular dynamics study of ammonia–cellulose I complex crystal models: free-energy landscape and atomistic pictures of ammonia diffusion in the crystalline phase.

The data deposited here accompany the manuscript "Extended ensemble molecular dynamics study of ammonia–cellulose I complex crystal models: free-energy landscape and atomistic pictures of ammonia diffusion in the crystalline phase" and include the molecular dynamics trajectories and the AMBER topology (parm) files. Detailed file contents are summarized in the README file.

opencc-by-4.0Feb 2023View details →

Supporting material of "A nonequilibrium alchemical method for drug-receptor absolute binding free energy calculations: the role of restraints"

Supporting material of the paper "A nonequilibrium alchemical method for drug-receptor absolute binding free energy calculations: the role of restraints". The directory is fully documented with README files. Differences of V2.0 with V1.0: <ul> <li>Due to a software bug we had to re-parametrize the ligands whose torsions were parametized with ANI-2.X (ligand 6 and 7).</li> <li>During the peer reviewing process we also parametrized with ANI-2.X and docked ligand 8.</li> </ul>

Input files for the MD simulations and free energy calculations for the article "Water Dissolved in a Variety of Polymers Studied by Molecular Dynamics Simulation and a Theory of Solutions"

Article: <a href="https://pubs.acs.org/doi/10.1021/acs.jpcb.1c04818">J. Phys. Chem. B. 125, 9357–9371 (2021) [DOI: 10.1021/acs.jpcb.1c04818]</a> The structures of the homopolymers and copolymers simulated are shown in Figures 1 and S1 and Tables 2 and 3. All-atom MD simulation was carried out using GROMACS, and this repository provides the input files with the GAFF/RESP force and initial coordinate files. The free energy of water dissolution was obtained with <a href="https://sourceforge.net/projects/ermod/">ERmod</a>, and the input files for the free-energy calculations are also contained. See the README files for details.

Analysing the effects of 24/7 Carbon-free Energy procurement strategies on the electricity system

This dataset contains results of simulations performed as part of a master's thesis project at Kungliga Tekniska Högskolan (KTH) in Stockholm, Sweden. Title: Analysing the effects of 24/7 Carbon-free Energy procurement strategies on the electricity system. Case Study of commercial and industrial sector in the Netherlands Programme: Sustainable Energy Systems, spec. Combined Energy Systems. Part of EIT InnoEnergy double master's degree SELECT programme.

Why The Perfectly Symmetric Cobalt-Pentapyridyl Loses the H2 Production Challenge: Theoretical Insight into Reaction Mechanism and Reduction Free Energies

Abstract Researchers have extensively investigated photo-catalytic water reduction utilizing Cobalt-based catalysts with poly-pyridyl ligands. While catalysts exhibiting distorted poly-pyridyl ligand demonstrate higher H2 production yields, those with ideal octahedral coordination display poor performance. This outcome suggests the crucial role of ligand framework in catalytic activity, yet reasons behind the disparity in H2 production rates for catalysts with octahedral geometries remain unclear. We theoretically examined the water reduction mechanism of Co-based poly-pyridyl catalyst, CoPy5, having perfect octahedral coordination. We clarified the effect of octahedral coordination by utilizing each intermediate step of ECEC mechanism. We determined spin states, solvent response, electronic structures, and reduction free energies. CoPy5 with perfect octahedral coordination, alongside its distorted counterparts, exhibit similar spin states as the reaction progresses through each intermediate step. However, the first reduction free energy obtained for the CoPy5 is slightly higher than that of its distorted counterparts. Following the second protonation, resulting H2 molecule experiences limited diffusion from the Co center due to the compact structure of the CoPy5, which blocks the Co center for the next H2 production cycle. Catalysts having distorted octahedral geometries facilitate fast removal of H2 into the solvent. Thus, the reaction center becomes immediately available for subsequent H2 production. Computational Details AIMD simulations have been performed for modeling intermediate states of the ECEC mechanisms of H2 production through water splitting. Open source CP2K simulation package have been used in all simulations. PBE density functional in general gradient approximation (GGA) formalism was employed for the AIMD simulations. Goedecker-Teter-Hutter (GTH) potentials were applied for the estimation of core electron interactions with the valence shell and nucleus. Valence electrons were modeled explicitly and valence shells of Co, N, C, O and H contain 17, 5, 4, 6 and 1 electrons, respectively. DZVP-MOLOPT basis set was used for all atomic kinds. For auxiliary plane wave basis set, a cutoff of 400 Ry was utilized. Dispersion interactions were taken into consideration by applying Vydrov and Van Voorhis vdW density functional, in the revised form (rVV10). Periodic boundary conditions and spin polarization were always applied. For the CoPy5 complex, AIMD simulations were carried out in a box defined as cubic with explicit water environment. The CoPy5 catalyst was first solvated in 215 water molecules and the simulation volume was relaxed by performing AIMD simulations for approximately 20 ps in the isothermal-isobaric ensemble (NPT). Cubic simulation box volume was determined as 6163.28  ̊A3. Following the determination of the simulation box size, each intermediate step were modeled by applying AIMD simulations in the canonical ensemble (NVT) for approximately 20 ps. Time step was set to 0.5 fs. Canonical sampling through velocity rescaling (CSVR) thermostat with a time constant of 100 fs was applied in order to keep the simulation temperature at 300 K. Please see the corresponding article for more details.

opencc-by-4.0Jul 2023View details →

Data and code for "Revealing the free energy landscape of halide perovskites: Metastability and transition characters in CsPbBr3 and MAPbI3"

This record contains a neuroevolution potential (NEP) model (<code>nep-MAPI-SCAN.txt</code> ) for MAPbI3 used in the linked publication. The model can be used in conjunction with the <a href="https://gpumd.org">GPUMD package</a>. The <a href="https://calorine.materialsmodeling.org">calorine package</a> provides a Python interface to GPUMD. Several primitive structures in extended xyz format can be found in the <code>*.xyz</code> files. These structures have been relaxed using the NEP model included here. The <code>demo-for-using-structures-and-model.py</code> script illustrates how to access the structures and model.

dryad40/100

Data from: Free energy analysis of peptide-induced pore formation in lipid membranes by bridging atomistic and coarse-grained simulations

Open the record for dataset details and reuse information.

publicOct 2024View details →

opencc-by-4.0Dec 2015View details →

Underlying data for "Evaluating parameterization protocols for hydration free energy calculations with the AMOEBA polarizable force field"

This dataset includes underlying data for the publication "Evaluating parameterization protocols for hydration free energy calculations with the AMOEBA polarizable force field" Contents: Modified valence parameters for the Poltype software (valence.py). This can be substituted for the existing valence.py module packaged with Poltype to make the parameter assignment changes detailed in the article supplementary information.  Results files for each parameter set (*.txt). Each consists of a 4 x 47 array of numbers. Rows correspond to entries for each sequential ligand. The first column in each row is the experimental hydration free energy. The following three rows are computational hydration free energy predictions from three independent repeat simulations. Script for analysis of results files (analyse_hfe.py). Short script to produce descriptive statistics for packaged datasets. Expects input files in the syntax of *.txt (i.e. 4 x 47 arrays)

opencc-by-4.0Dec 2016View details →

Aerodynamics code used in Wind Energy Science paper "Comparison of a coupled near- and far-wake model with a free-wake vortex code"

This research code has been developed from the start of my PhD as a first step before the HAWC2 implementation of the near wake model. It can be used to make aerodynamic computations of a stiff wind turbine rotor, and it includes <ul> <li>A BEM and far wake model implementation based on the one in HAWC2</li> <li>An attached flow unsteady airfoil aerodynamics model including the modifications described in the WES article</li> <li>Most importantly a near wake model implementation including all major modifications except the recent stand still extension presented at TORQUE 2016</li> </ul> All the data files need to be in a subfolder 'NREL_5MW' located in the same folder as the compiled source code. With the present (hardcoded) settings, the program will simulate the NREL 5 MW reference turbine for 650 seconds, with blade vibrations according to different prescribed mode shapes after steady state is reached. The aerodynamics model is a coupled near and far wake model. The integrated aerodynamic work during 1 period of the different prescribed vibrations will be output in the file 'aerowork.out' . The NREL 5 MW turbine is described in: Jonkman, J., Butterfield, S., Musial,W., and Scott, G.: Definition of a 5-MW Reference Wind Turbine for Offshore System Development, National Renewable Energy Laboratory, 2009.

opencc-by-4.0Jun 2017View details →

Research data accompanying the paper 'Exploiting Sparsity in Free Energy Basin-Hopping'

Input and output files for the results presented in Tables 1-5 of the paper 'Exploiting Sparsity in Free Energy Basin-Hopping'. Further information on these files can be found in the README files within the tar file.

Dataset for "ConfSolv: Prediction of solute conformer free energies across a range of solvents"

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. 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.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.

opencc-by-4.0Nov 2024View details →

Data for: Alchemical free-energy calculations at quantum-chemical precision

In the last decade, machine-learned potentials (MLP) have demonstrated the capability to predict various QM properties learned from a set of reference QM calculations. Accordingly, hybrid QM/MM simulations can be accelerated by replacement of expensive QM calculations with efficient MLP energy predictions. At the same time, alchemical free energy perturbations (FEP) remain unachievable at the QM level of theory. In this work, we extend the capabilities of the Buffer Region Neural Network (BuRNN) QM/MM scheme towards FEP. BuRNN introduces a buffer region that experiences full electronic polarization by the QM region to minimize artifacts at the QM/MM interface. A MLP is used to predict the energies for the QM region and its interactions with the buffer region. Furthermore, BuRNN allows us to implement FEP directly into the MLP Hamiltonian. Here, we describe the alchemical change from methanol to methane in water at the MLP/MM level as a proof of concept.

opencc-by-4.0Dec 2021View details →

Alchemical Free Energy Estimators and Molecular Dynamics Engines: Accuracy, Precision and Reproducibility

This zip contains all input structures for paper the: Alchemical Free Energy Estimators and Molecular Dynamics Engines: Accuracy, Precision and Reproducibility Authors: Alexander D. Wade, Agastya P. Bhati, Shunzhou Wan, Peter V.Coveney The structures of the folders are protein/ligand_transformation/alchemical_leg/input/files The ligand transformation are derived from previous work by wang et al. (https://pubs.acs.org/doi/10.1021/ja512751q) There are two files for the solvent alchemical leg: complex.pdb and complex.prmtop complex.pdb is  structure file that also denotes the alchemical atoms in the pdb beta column. complex.prmtop is an AMBER parameter/topology file For the complex alchemical leg there is an additional file constraints.pdb that contains the constraint information in the pdb beta column. These files can be used with TIES_MD (https://ucl-ccs.github.io/TIES_MD/) or other molecular dynamics engiens that take AMBER input.

openother-openJan 2022View details →

Benchmark set inputs for absolute binding free energy calculations of fragment optimisations

Supplementary Information: "Evaluating the use of absolute binding free energy in the fragment optimization process" Provided here are the various scripts, input files, and results necessary to reproduce the outcomes of the above mentioned publication. Please see the provided README.md files for further information on the contents of this dataset.

opencc-by-4.0Feb 2022View details →

Relative binding free energy between chemically distant compounds using a bidirectional non-equilibrium approach

Data from "Relative binding free energy between chemically distant compounds using a bidirectional nonequilibrium approach" Submitted to J Chem Theory Comput, February  2022. This archive contains the following directories: traj -> This directory contains trajectory files for SAMPL9:         g??_w.pdb.gz file contains ~ 160 snapshots from the 48 ns HREM sampling         of the target bound state of G1-G13 including water solvent.         g??_1.pdb.gz file contains ~ 3500 snapshots (no solvent included) of the     target bound state of G1-G13 work -> This trajectory contains the work data (in kJ/mol) obtained in         the NE trajectories for SAMPL9:     gxx-gyy_b_TIME.wrk is the work sample obtained for the xx->yy transmutation         in the bound state with a duration time of TIME.     gxx-gyy_u_TIME.wrk is the work sample obtained for the xx->yy transmutation         in the unbound state with a duration time of TIME. pdb -> This directory contains the pdb initial structures of the G1-G18 guests and the WP6 host ff ->  This directory contains the force field specification for SAMPL9:     the PrimaDORAC generated (http://www1.chim.unifi.it/orac/primadorac/)         tpg and prm files for the guests and the host in orac format.  (see         http://ftp.chim.unifi.it/orac/MAN/orac-manual.html) bin -> This directory contains the script files to compute all bidirectional and unidirectional RBFE estimates as reported in Table 2 of the paper.        In order to compute an RBFE using the work data in the work dir, do the following:        1) cd into the bin directory        2) issue the command              source source_this_file.bash       (N.B.: gfortran must be installed)        3) cd ../        4) from the main dir, issue the command:              RBFE.bash -b 720 -u 360 B A           where  B and A are the ghost and physical compound, respectively        Results for DG(A->B) are printed to the standard output        Example:                     RBFE.bash -b 720 -u 360 g01 g03 > g03g01       In the g03g01 file, estimates and properties of the work data are       printed in the format      "g05->g02   DG_bar=   -5.13   0.37  DG_ff_G=   -4.2   0.8  DG_ff_J=   -3.0   0.4  sig_AB_u=  0.90 sig_AB_b=  2.16 ADT_AB_u=  0.26 ADT_AB_b=  0.23 DG_rr_G=  130.5  33.5  DG_rr_J=   -7.2   0.8  sig_BA_u=  1.10 sig_BA_b= 13.61 ADT_BA_u=  0.48 ADT_BA_b=  3.40  DG_fr_G=  -4.27  1.04  DG_fr_J=  -3.23  0.58 bias_fr=  0.2  DG_rf_G= 127.88 30.30  DG_rf_J=  -7.16  0.66 bias_rf=  0.0 DG_BAR=  -5.26 0.0 tb=  720 tu=  360"      To compute all DDG estimates of Table 2 launch the script      "do_all.bash" from the main dir         shift-pot -> This directory contains two gnuplot scripts showing the evolution of the       Beutler LJ and elec soft-core potentials (soft.gplt)  and of the shifted LJ and       elec soft-core potentials used in this work  (shift.gplt)

opencc-by-4.0Jun 2022View details →

Does Hamiltonian Replica Exchange via lambda-hopping enhance the sampling in alchemical binding free energy calculations?

t-REM HREM lamba-hopping/FEP+ tests on the APA molecule with ORAC (www.chim.unifi.it/orac)  The untarred archive contains the following directories:  t-rem -> contains input for gas-phase tests st-hrem ->  contains input for solvated APA with solute tempering lam-hop ->  contains input for solvated APA with lambda-hopping bin -> scripts for REM analysis  lib -> APA starting conf and potential parameters for the runs  see also README files inside each dir for further details

opencc-by-4.0Dec 2023View details →

Machine Learning Guided AQFEP: A Fast & Efficient Absolute Free Energy Perturbation Solution for Virtual Screening

Data to reproduce primary figures in the manuscript titled: Machine Learning Guided AQFEP: A Fast & Efficient Absolute Free Energy Perturbation Solution for Virtual Screening. URL: https://chemrxiv.org/engage/chemrxiv/article-details/6583785e66c1381729ac86f5