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Predicting Relative Populations of Protein Conformations without a Physics Engine Using AlphaFold 2
Gabriel Monteiro da Silva1, Jennifer Y Cui1, David C Dalgarno2
1Brown University Department of Molecular Biology, Cell Biology, and Biochemistry, Providence, RI, USA.
Biorxiv : the Preprint Server for Biology
|August 7, 2023
Summary
Researchers can now predict protein conformation populations using AlphaFold 2 by subsampling alignments. This AI method accurately forecasts changes in protein states due to mutations or evolution.
Area of Science:
- Computational Biology
- Structural Biology
- Biophysics
Background:
- AlphaFold 2 accurately predicts protein structures but is limited to ground-state conformations.
- Predicting protein conformational landscapes and relative state populations remains a challenge.
Conclusions:
- The subsampling approach enables direct prediction of relative protein conformation populations using AlphaFold 2.
- This method provides a fast, cost-effective tool for analyzing conformational changes at single-point mutation resolution.
- Applications include pharmacology, NMR analysis, and evolutionary studies of protein dynamics.
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