AlphaFold2 models indicate that protein sequence determines both structure and dynamics

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 proteins with good multisequence alignment (MSA) depths, including large proteins and protein complexes, the AF2-scores are highly correlated with the root mean square fluctuations (RMSF) calculated from MD simulations. For proteins with little or no MSA hits (the IDP and randomized protein), the AF2-scores do not correlate with the RMSF from MD, especially for the intrinsically disordered proteins (IDPs). Our results indicate that the protein structures predicted by AF2 also convey information of the residue flexibility, i.e., protein dynamics.

Functionally annotating cysteine disulfides and metal binding sites in the plant kingdom using AlphaFold2 predicted structures

“…This is as also evidenced by the absence or presence of disulfides in different deposited PDB structures of the same protein (Dataset S2). It should be noted that the AlphaFold2 per-residue pLDDT confidence scores in predicted structures can hint towards flexible or disordered protein regions [78,79]. Moreover, such disulfide alterations, and oxidative modifications, are especially anticipated in conditions perturbing redox homeostasis, such as environmental stresses faced by plants.…”

AlphaFold Prediction of Structural Ensembles of Disordered Proteins

“…Support for this idea comes from the observation that AlphaFold performs as well as current state-of-the-art predictors of protein disorder 16,17 . It has also been reported that the predicted aligned error (PAE) maps from AlphaFold are correlated with the distance variation matrices from molecular dynamics simulations 7 , suggesting that AlphaFold provides information about the dynamics of proteins in addition to their structures.…”

“…Furthermore, the initial predictions of the native structures of proteins have been recently extended to protein complexes 4,5 . These advances have prompted the question of whether it is possible to use this type of approach for the prediction of the conformational fluctuations of the native states of folded proteins [6][7][8][9][10][11][12] , and more generally for the characterisation of the structural properties of the native states of disordered proteins [13][14][15] . Support for this idea comes from the observation that AlphaFold performs as well as current state-of-the-art predictors of protein disorder 16,17 .…”

Investigating the conformational landscape of AlphaFold2-predicted protein kinase structures

“…Hegedűs et. al and Guo et al have also shown a relationship between pLDDT and protein conformational dynamics(35; 36). Since AF2 can model several pharmacologically-relevant kinase conformational states (Fig.…”