We demonstrated how the wazy package (Yang et al. 2022, developed by members of the White lab at U. Rochester) can be trained on protein sequence-property prediction tasks. For training we ran coarse-grained simulations using HOOMD-blue 2.9.7 extended with azplugins. The simulations were run on the MOGON II computing cluster of JGU Mainz.
Here, we provide the code used for training and the results of the simulations (extracted quantities, e.g.
The code presented here was used in the study by Changiarath, Arya, Xenidis, Padeken, Stelzl 2024, under review for Faraday Discussions.
Our code builds on wazy, which performs the featurization using UniRep, and has its own construction for doing bayesian optimization using MLPs as a surrogate model. We use localCIDER for computing descriptors.
Apparently metapredict
has a lot of dependencies and it'll download large libraries while installing.
pip install cython metapredict wazy localcider