JAMUN: Transferable Molecular Conformational Ensemble Generation with Walk-Jump Sampling
transferable;conformation;ensembles;3D structure;equivariance;sampling;proteins
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We present JAMUN, a new model for generating conformational ensembles for small proteins at rapid rates.
@misc{
daigavane2024jamun,
title={{JAMUN}: Transferable Molecular Conformational Ensemble Generation with Walk-Jump Sampling},
author={Ameya Daigavane and Bodhi P. Vani and Joseph Kleinhenz and Joshua A Rackers},
year={2024},
url={https://openreview.net/forum?id=3VxEGpamLT}
}
Conformational ensembles of protein structures are immensely important to understanding protein function. Current techniques for sampling ensembles are computationally inefficient, or do not transfer to systems outside their training data. We present walk-Jump Accelerated Molecular ensembles with Universal Noise (JAMUN), a step towards the goal of efficiently sampling the Boltzmann distribution of arbitrary proteins. By extending Walk-Jump Sampling to point clouds, JAMUN enables ensemble generation at orders of magnitude faster rates than traditional molecular dynamics or state-of-the-art generators. Further, JAMUN is able to predict the stable basins of small peptides that were not seen during training.
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~Ameya_Daigavane1 ~Bodhi_P._Vani1 ~Joseph_Kleinhenz1 ~Joshua_A_Rackers1
Ameya Daigavane Bodhi P. Vani Joseph Kleinhenz Joshua A Rackers
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transferable conformation ensembles 3D structure equivariance sampling proteins
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daigavane|jamun_transferable_molecular_conformational_ensemble_generation_with_walkjump_sampling
/pdf/0bd60461563017f1420e9ea607ff69b87ef6c122.pdf
applications to physical sciences (physics, chemistry, biology, etc.)
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JAMUN: Transferable Molecular Conformational Ensemble Generation with Walk-Jump Sampling
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