Conformer Optimization

This repo contains code for optimizing conformers using active learning and quantum chemistry computations.

Background Conformers define the different structures with the same 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 emerged that uses Bayesian optimization find optimize dihedral angles.

Installation

Build the environment using anaconda:

conda env create --file environment.yml --force

Use

run.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.