Tools
CASCADE
CASCADE stands for ChemicAl Shift CAlculation with DEep learning. It is a stereochemically-aware graph network for the prediction of NMR chemical shifts. Model training was performed against 8,000 DFT structures followed by transfer learning with experimental spectra. A web-server has been created to access CASCADE predictions from SMILES or by drawing structures in the graphical interface. An automated workflow executes 3D structure embedding and MMFF conformer searching. The full ensemble of optimized conformations are passed to a trained graph neural network to predict the NMR chemical shifts (in ppm) for C and H atoms. The underlying datasets used for training and the Python code to run CASCADE from the command line have been made available.
[GitHub]
DBSTEP
DBSTEP is a python package for obtaining DFT-Based Steric Parameters from 3-dimensional chemical structures. It can parse the outputs from most computational chemistry programs and other common molecular structure file formats. Steric properties can either be obtained exactly or by using a Cartesian grid, the latter approach being amenable to the featurization of a molecular isodensity surface (DBSTEP can process wavefunction files) rather than using classical atomic radii. Currently, traditional Sterimol parameters (L, Bmin, Bmax) and percent buried volume parameters are implemented, as well as our novel steric parameter vectors Sterimol2vec and vol2vec. This package is designed for use on the command line or alternatively implemented in a Python script for use in a computational workflow to collect steric parameters.
[GitHub]
Goodvibes
A Python program to compute quasi-harmonic thermochemical data and potential energy surface diagrams from frequency calculations at a given temperature/concentration, corrected for the effects of vibrational scaling-factors. All (electronic, translational, rotational and vibrational) partition functions are recomputed and can be correct to any temperature or concentration. The first public version of GoodVibes was released in 2016 and it has undergone several revisions since, during which time it has been used by many groups around the world. The program is described in the publication: GoodVibes: automated thermochemistry for heterogeneous computational chemistry data
[GitHub]
wSterimol
A program to generate Boltzmann-weighted Sterimol Steric Parameters for conformationally-flexible substituents that integrates with PyMol. The program contains an automated computational workflow which computes multidimensional Sterimol parameters. For flexible molecules or substituents, the program will generate & optimize a conformational ensemble, and produce Boltzmann-weighted Sterimol parameters. It has been developed as a PyMol plugin and can be run from within the graphical user interface. The wSterimol code is described in more detail in Conformational Effects on Physical-Organic Descriptors – the Case of Sterimol Steric Parameters
[GitHub]
pyQRC
QRC is an abbreviation of Quick Reaction Coordinate. This provides a quick alternative to IRC (intrinsic reaction coordinate) calculations. The program will read a Gaussian frequency calculation and will create a new input file which has been projcted from the final coordinates along the Hessian eigenvector with a negative force constant. The magnitude of displacement can be adjusted on the command line. By default the projection will be in a positive sense (in relation to the imaginary normal mode) and the level of theory in the new input file will match that of the frequency calculation. A common application for pyQRC is in distorting ground state structures to remove annoying imaginary frequencies after reoptimization. This code has, in some form or other, been in use since around 2010.
[GitHub]
Kinisot
A Python program to compute kinetic isotope effects from two Gaussian output files, one of which is a ground state and the other a transition state. The level of theory and basis set are detected from in the output files and the program will attempt to assign the appropriate scaling factor based on data from the Truhlar group. The program diagonalizes the mass-weighted Hessian matrices to obtain harmonic vibrational frequencies and Bigeleisen-Mayer Reduced Isotopic Partition Function Ratios. Kinisot is freely available (CC-BY license) from GitHub; alternatively, it can be installed from the command line with pipy: pip install kinisot.
[GitHub]
pyDFTD3
A standalone Python version of Grimme’s DFT-D3 dispersion correction with zero and Becke-Johnson damping. This python version will give D3 energies identical to other implementations in electronic structure codes, but these can also be decomposed into interatomic or intermolecular terms. If separate molecules are recognized, based on interatomic connectivity, then the intramolecular terms can also be ignored. The pyDFTD3 code was largely written for Gaussian formatted input and output files, and should be able to parse the functional from these and apply the appropriate damping parameters automatically. Otherwise they can be specified manually from the command line.
[GitHub]Datasets
bde-db2
bde-db2 dataset contains bond dissociation energies (including enthalpies and free energies) for 65,540 molecules which represent a set of 531,244 unique BDEs. This dataset is broken down into molecule, bond index, fragments and BDEs. This was used to build the ALFABET2 GNN model hosted at https://bde.ml.nrel.gov.
[GitHub]
