Scientific Reports (Jun 2022)

AlphaFold2 models indicate that protein sequence determines both structure and dynamics

  • Hao-Bo Guo,
  • Alexander Perminov,
  • Selemon Bekele,
  • Gary Kedziora,
  • Sanaz Farajollahi,
  • Vanessa Varaljay,
  • Kevin Hinkle,
  • Valeria Molinero,
  • Konrad Meister,
  • Chia Hung,
  • Patrick Dennis,
  • Nancy Kelley-Loughnane,
  • Rajiv Berry

DOI
https://doi.org/10.1038/s41598-022-14382-9
Journal volume & issue
Vol. 12, no. 1
pp. 1 – 15

Abstract

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Abstract AlphaFold 2 (AF2) has placed Molecular Biology in a new era where we can visualize, analyze and interpret the structures and functions of all proteins solely from their primary sequences. We performed AF2 structure predictions for various protein systems, including globular proteins, a multi-domain protein, an intrinsically disordered protein (IDP), a randomized protein, two larger proteins (> 1000 AA), a heterodimer and a homodimer protein complex. Our results show that along with the three dimensional (3D) structures, AF2 also decodes protein sequences into residue flexibilities via both the predicted local distance difference test (pLDDT) scores of the models, and the predicted aligned error (PAE) maps. We show that PAE maps from AF2 are correlated with the distance variation (DV) matrices from molecular dynamics (MD) simulations, which reveals that the PAE maps can predict the dynamical nature of protein residues. Here, we introduce the AF2-scores, which are simply derived from pLDDT scores and are in the range of [0, 1]. We found that for most protein models, including large proteins and protein complexes, the AF2-scores are highly correlated with the root mean square fluctuations (RMSF) calculated from MD simulations. However, for an IDP and a randomized protein, the AF2-scores do not correlate with the RMSF from MD, especially for the IDP. Our results indicate that the protein structures predicted by AF2 also convey information of the residue flexibility, i.e., protein dynamics.