JAMUN: Transferable Molecular Conformational Ensemble Generation with Walk-Jump Sampling

Conformational ensembles of protein structures are immensely important both to understanding protein function, and for drug discovery in novel modalities such as cryptic pockets. Current techniques for sampling ensembles are computationally inefficient, or do not transfer to systems outside their tr...

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Bibliographic Details
Published in:arXiv.org 2024-10
Main Authors: Daigavane, Ameya, Vani, Bodhi P, Saremi, Saeed, Kleinhenz, Joseph, Rackers, Joshua
Format: Article
Language:English
Subjects:
Boltzmann distribution
Molecular dynamics
Peptides
Proteins
Sampling
Online Access:Get full text
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Summary:Conformational ensembles of protein structures are immensely important both to understanding protein function, and for drug discovery in novel modalities such as cryptic pockets. 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 ML methods. Further, JAMUN is able to predict the stable basins of small peptides that were not seen during training.
ISSN:2331-8422