Datasets from "Electrostatic Embedding of Machine Learning Potentials"
Data required to reproduce results in "Electrostatic Embedding of Machine Learning Potentials" article. See https://github.com/emedio/embedding for details. QM7_B3LYP_cc-pVTZ.tgz - outputs of single point B3LYP/cc-pVTZ calculations of structures in QM7 dataset with ORCA 5. Include molecula...
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| Format: | Dataset |
| Language: | unknown |
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2022
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| Subjects: | |
| Online Access: | https://zenodo.org/record/7051785 https://doi.org/10.5281/zenodo.7051785 |
| Summary: | Data required to reproduce results in "Electrostatic Embedding of Machine Learning Potentials" article. See https://github.com/emedio/embedding for details. QM7_B3LYP_cc-pVTZ.tgz - outputs of single point B3LYP/cc-pVTZ calculations of structures in QM7 dataset with ORCA 5. Include molecular dipolar polarizabilities. QM7_B3LYP_cc-pVTZ_horton.tgz - MBIS partitioning of the B3LYP/cc-pVTZ densities with Horton 2.1.0. mpro_xyz.tgz - coordinates of the ligand and surrounding point charges from 100 snapshots of SARS-CoV-2 Mpro complex with PF-00835231. mpro_*.tgz - DFT and semiempirical single point calculations with ORCA 5 for the coordinates from mpro_xyz.tgz, in vacuo and in presence of point charges. mlmm.mat - learned parameters and SOAP feature vectors of reference atomic environments |
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