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"