bioRxivMolecular BiologyPreprint
Experiment-guided AlphaFold3 resolves accurate protein ensembles
Advaith MaddipatlaiD, Nadav Bojan SellamiD, Meital BojaniD, Volodymyr MasalitiniD, Sanketh VedulaiD, Paul SchandaiD, Ailie MarxiD, Alex M. BronsteiniD
Abstract
AlphaFold3 predicts highly accurate protein structures from sequence, but tends to collapse to a single dominant conformation, even when the underlying structure is inherently heterogeneous. Moreover, its predictions are oblivious to experimental conditions that can alter local sequence conformation. In this work we show that AlphaFold3 can be guided to match data obtained by NMR spectroscopy, X-ray crystallography and cryo-EM experiments, and combinations thereof. Our approach can also incorporate data that explicitly report on dynamics, such as site-resolved order parameters. We demonstrate that this methodology can generate ensembles of conformations having less distance restraint violations than traditionally resolved NMR structures and uncover unmodelled alternate conformations detectable in electron density. This methodology paves the way for the development of experimentally aware predictive models that capture the ensemble nature of protein structures.
- assay: protein structure
- research focus: protein structure prediction
- approach: deep learning
- approach: experimental assay
- Citations
- 2
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