SPICE (Small-Molecule/Protein Interaction Chemical Energies) is a collection of quantum mechanical data for training potential functions. The emphasis is particularly on simulating drug-like small molecules interacting with proteins. It is described in this publication: Peter Eastman, Pavan Kumar Behara, David L. Dotson, Raimondas Galvelis, John E. Herr, Josh T. Horton, Yuezhi Mao, John D. Chodera, Benjamin P. Pritchard, Yuanqing Wang, Gianni De Fabritiis, and Thomas E. Markland. "SPICE, A Dataset of Drug-like Molecules and Peptides for Training Machine Learning Potentials." https://doi.org/10.48550/arXiv.2209.10702 (2022). The HDF5 file is structured as follows. There is one top level group for each unique molecule or cluster. The nam...
Molecular modelling and simulations are nowadays an integral part of research in areas ranging from ...
Accurate representation of the molecular electrostatic potential, which is often expanded in distrib...
Machine learning has been used for estimation of potential energy surfaces to speed up molecular dyn...
SPICE (Small-Molecule/Protein Interaction Chemical Energies) is a collection of quantum mechanical d...
SPICE (Small-Molecule/Protein Interaction Chemical Energies) is a collection of quantum mechanical d...
SPICE (Small-Molecule/Protein Interaction Chemical Energies) is a collection of quantum mechanical d...
Machine learning potentials are an important tool for molecular simulation, but their development is...
This is a collection of QM datasets deposited in the QCArchive to train espaloma-0.3.0. Extensive ch...
Quantum mechanical predictive modelling in chemistry and biology is often hindered by the long time ...
Data used in the paper "Transferring Chemical and Energetic Knowledge Between Molecular Systems With...
We introduce machine learning models of quantum mechanical observables of atoms in molecules. Instan...
Accurate modelling of chemical and physical interactions is crucial for obtaining thermodynamic and ...
We introduce a fingerprint representation of molecules based on a Fourier series of atomic radial di...
Molecular modelling and simulations are nowadays an integral part of research in areas ranging from ...
Computational chemistry is a branch of chemistry that uses principles of computer science to assist ...
Molecular modelling and simulations are nowadays an integral part of research in areas ranging from ...
Accurate representation of the molecular electrostatic potential, which is often expanded in distrib...
Machine learning has been used for estimation of potential energy surfaces to speed up molecular dyn...
SPICE (Small-Molecule/Protein Interaction Chemical Energies) is a collection of quantum mechanical d...
SPICE (Small-Molecule/Protein Interaction Chemical Energies) is a collection of quantum mechanical d...
SPICE (Small-Molecule/Protein Interaction Chemical Energies) is a collection of quantum mechanical d...
Machine learning potentials are an important tool for molecular simulation, but their development is...
This is a collection of QM datasets deposited in the QCArchive to train espaloma-0.3.0. Extensive ch...
Quantum mechanical predictive modelling in chemistry and biology is often hindered by the long time ...
Data used in the paper "Transferring Chemical and Energetic Knowledge Between Molecular Systems With...
We introduce machine learning models of quantum mechanical observables of atoms in molecules. Instan...
Accurate modelling of chemical and physical interactions is crucial for obtaining thermodynamic and ...
We introduce a fingerprint representation of molecules based on a Fourier series of atomic radial di...
Molecular modelling and simulations are nowadays an integral part of research in areas ranging from ...
Computational chemistry is a branch of chemistry that uses principles of computer science to assist ...
Molecular modelling and simulations are nowadays an integral part of research in areas ranging from ...
Accurate representation of the molecular electrostatic potential, which is often expanded in distrib...
Machine learning has been used for estimation of potential energy surfaces to speed up molecular dyn...