Generate beautiful ensembles of molecular geometries "Bayesian Optimization Using QUantum Energy Tool"
This repo contains code for optimizing conformers using Bayesian optimization for active learning and quantum chemistry computations.
Background
Conformers define the different geometries with the same molecular bonding graph but different coordinates. Finding the lowest-energy conformation is a common task in molecular modeling, and one that often requires significant time to solve. We implement optimal experimental design techniques to solve this problem following recent work that uses Bayesian optimization find optimize dihedral angles.
Build the environment using anaconda:
conda env create --file environment.yml --forcerun.py provides a simple interface to the code. To optimize cysteine with default arguments.
python run.py "C([C@@H](C(=O)O)N)S"This will produce a folder in the solutions directory containing the optimized geometry
(final.xyz) and many other files for debugging.
Call python run.py --help for available options.