Protein phosphorylation plays key roles in many signal transduction processes, preferentially targeting intrinsically disordered protein domains (IDPs). IDPs remain largely unstructured under native conditions, resembling random-coil polymers akin to the unfolded states of proteins. Present in more than 50% of eukaryotic proteins, IDPs perform a plethora of biological functions and are commonly associated with a variety of human diseases.
Technical limitations hamper intrinsically disordered protein characterization
The mechanism by which phosphorylation modulates disordered domains remains unknown. This stems from the extraordinary structural heterogeneity of IDPs, which poses a challenge for their characterization using common structural determination experimental techniques. For instance, the study of IDPs is inviable with X-ray crystallography because of the fast mobility of the domains, and NMR does not allow singling out the structural details of the multiple, underlying conformational states.
Can intrinsically disordered proteins be characterized using molecular dynamics simulations?
Recent advances in computer simulation technology offer a unique opportunity to study IDPs with atomic resolution on the millisecond timescale, the regime necessary to study these systems. The introduction of accelerator processors, and their application to MD, as well as the development of HTMD, and adaptive sampling methods, have allowed an increase of sampling efficiency of several orders of magnitude. Indeed, a single workstation can now obtain microsecond long simulations with atomic resolution in one day, and milliseconds can be obtained rapidly on a supercomputer, or through distributed computing projects. Nevertheless, this bourgeoning field is still limited in its ability to analyse millions of protein conformers, and compute their population and kinetics.
All-atom MD for intrinsically disordered protein characterization
In this work (Nat. Comm. 2014, DOI: 10.1038/ncomms6272), we successfully reconstructed the conformational ensemble of an IDP domain involved in gene transcription. A new analysis tool capable of resolving the disordered state of disordered domains was used in combination with large scale all-atom, unbiased, molecular simulations. 1.7 milliseconds of aggregated time were sampled. This methodology was used to study a well-characterized disordered fragment of the protein kinase-inducible domain (KID) in the cellular transcription factor of the cAMP response element-binding protein (CREB).
Identification of slow molecular order parameters for Markov model construction
The kinetic characterization of macromolecular systems requires the description of slow relaxation processes. This depends on the identification of the structural changes involved in these processes (selection of structural descriptors), the discretization of the high-dimensional coordinate space (clustering of conformers according to the descriptors) and estimation of the rates or timescales at which these slow processes occur. Approaches to this end include Markov models, master-equation models, and kinetic network models.
In this work we analyzed the simulated data by constructing a Markov state model of the entire ensemble of trajectories using inter-residue Cα-Cα distances and φ/ψ backbone dihedral angles as general metrics to build the kinetic model. The conformational space was discretized into one thousand clusters and then projected on a 5-dimensional space using time-lagged independent component analysis (TICA), which identifies the slow coordinates in the dynamics without relying on subjective guesses.
Phosphorylation reduces the conformational kinetics of intrinsically disordered proteins
The results presented in Figure 1 show the first microscopic view of the equilibrium states and conformational kinetics of a disordered protein domain at atomic resolution. The conformational exchange between state D (disordered) and state O (ordered) is shown together with forward (τ1) and backward (τ-1) transition times. Conformations were aligned using residues with the lowest Cα-Cα distance variance. N- to C-terminal is color coded red and blue.
We find that phosphorylation induces a 60-fold slowdown in conformational kinetics, compared to a non-phosphorylated domain, which involves a low populated and partially structured excited state known to participate in an early binding intermediate (Fig. 2). Figure 2a shows residue specific relaxation times of helix folding/unfolding process (filled bars) derived from autocorrelation function. Empty bars show chemical shifts changes in pKID that map residues participating in an early binding intermediate as detected by NMR. Figure 2b is an example of a kinetically locked conformation in phosphorylated KID. The peptide backbone is shown in cartoon representation, and the heavy atoms of phosphorylated serine 133 and several charged residues are shown as sticks.
Direct comparison against NMR data supports the validity of these findings and show that, contrary to what is typically assumed and in line with experiments, mutation of the phosphoserine to glutamate cannot recover the slowdown in conformational exchange (Fig. 1c).
Is the regulation of phosphorylation via the kinetic modulation of intrinsically disordered proteins conserved?
We propose a new mechanism of phosphorylation regulation by kinetic modulation which could be general for disordered domains which lack a well-defined equilibrium structure. This mechanism emerges from a theoretically derived kinetic model that shows that it is possible to modulate the binding affinity of protein-protein complexes by inducing a slowdown in conformational kinetics affecting both on- and off-conformational transition times by the same amount and simultaneously. This model agrees with kinetic and affinity values obtained through experiment (See paper).
With disordered domains taking part in more than 50% of proteins responsible for signaling in the cell, this kinetic mechanism of modulation highlights a further way by which post-translation modifications may affect disordered domains and their interactions with binding partners.
This work was performed in the De Fabritiis lab. Gianni De Fabritiis is the founder of Acellera. Should you be interested in performing similar studies in-house let Acellera know. We will be happy to inform you.