Basic usage

Using AQME in Jupyter Notebooks

There are multiple ready-to-use workflows presented as jupyter notebooks in the in the aqme repository in Example_Workflows folder. Some examples are:

CSEARCH_CMIN_conformer_generation folder --> CSEARCH/CMIN conformational sampling from SMILES and creation of QM input files

QCORR_processing_QM_outputs --> QCORR analysis of Gaussian output files, generation of JSON files with all the information and creation of new QM input files

QPREP_generating_input_files --> QPREP preparation of input files for Gaussian, ORCA and PySCF from LOG/OUT, SDF and JSON files

Note

For a more examples please see the 'Examples/Examples Python' section in our ReadtheDocs page.

Using AQME through the command line

CSEARCH examples

Conformer generation with one SMILES and name using RDKit or CREST (use rdkit or crest in --program):

python -m aqme --csearch --program rdkit --smi "CCC" --name proprane

Conformer generation with multiple SMILES and names (i.e. from a database in CSV format):

python -m aqme --csearch --program rdkit --input FILENAME.csv

Note

The csv file must contain the list of SMILES in a column called "SMILES" and the corresponding names in a column called "code_name" (see Example_workflows for more information)

CMIN examples

Geometry optimization with xTB or ANI (use xtb or ani in --program; use sdf, xyz, com/gjf or pdb in --files):

python -m aqme --cmin --program xtb --files "*.sdf"

QPREP examples

Input file generation from SDF, JSON and LOG/OUT files (replace "*.sdf" for the corresponding format):

python -m aqme --qprep --program gaussian --qm_input "M062x def2tzvp opt freq" --files "*.sdf"

QCORR examples

Analysis of Gaussian output files and JSON file generation:

python -m aqme --qcorr --program gaussian --freq_conv "opt=(calcfc,maxstep=5)" --files "*.log"