The Effect of Multisite Phosphorylation on the Conformational Properties of Intrinsically Disordered Proteins

Streamlining NMR Chemical Shift Predictions for Intrinsically Disordered Proteins: Design of Ensembles with Dimensionality Reduction and Clustering

By merging advanced dimensionality reduction (DR) and clustering algorithm (CA) techniques, our study advances the sampling procedure for predicting NMR chemical shifts (CS) in intrinsically disordered proteins (IDPs), making a significant leap forward in the field of protein analysis/modeling. We enhance NMR CS sampling by generating clustered ensembles that accurately reflect the different properties and phenomena encapsulated by the IDP trajectories. This investigation critically assessed different rapid CS predictors, both neural network (e.g., Sparta+ and ShiftX2) and database-driven (ProCS-15), and highlighted the need for more advanced quantum calculations and the subsequent need for more tractable-sized conformational ensembles. Although neural network CS predictors outperformed ProCS-15 for all atoms, all tools showed poor agreement with HN CSs, and the neural network CS predictors were unable to capture the influence of phosphorylated residues, highly relevant for IDPs. This study also addressed the limitations of using direct clustering with collective variables, such as the widespread implementation of the GROMOS algorithm. Clustered ensembles (CEs) produced by this algorithm showed poor performance with chemical shifts compared to sequential ensembles (SEs) of similar size. Instead, we implement a multiscale DR and CA approach and explore the challenges and limitations of applying these algorithms to obtain more robust and tractable CEs. The novel feature of this investigation is the use of solvent-accessible surface area (SASA) as one of the fingerprints for DR alongside previously investigated α carbon distance/angles or ϕ/ψ dihedral angles. The ensembles produced with SASA tSNE DR produced CEs better aligned with the experimental CS of between 0.17 and 0.36 r2 (0.18-0.26 ppm) depending on the system and replicate. Furthermore, this technique produced CEs with better agreement than traditional SEs in 85.7% of all ensemble sizes. This study investigates the quality of ensembles produced based on different input features, comparing latent spaces produced by linear vs nonlinear DR techniques and a novel integrated silhouette score scanning protocol for tSNE DR.

Exploring the Functional Landscape of the p53 Regulatory Domain: The Stabilizing Role of Post-Translational Modifications

This study focuses on the intrinsically disordered regulatory domain of p53 and the impact of post-translational modifications. Through fully atomistic explicit water molecular dynamics simulations, we show the wealth of information and detailed understanding that can be obtained by varying the number of phosphorylated amino acids and implementing a restriction in the conformational entropy of the N-termini of that intrinsically disordered region. The take-home message for the reader is to achieve a detailed understanding of the impact of phosphorylation with respect to (1) the conformational dynamics and flexibility, (2) structural effects, (3) protein interactivity, and (4) energy landscapes and conformational ensembles. Although our model system is the regulatory domain p53 of the tumor suppressor protein p53, this study contributes to understanding the general effects of intrinsically disordered phosphorylated proteins and the impact of phosphorylated groups, more specifically, how minor changes in the primary sequence can affect the properties mentioned above.

Effects of Phosphorylation on Protein Backbone Dynamics and Conformational Preferences

Phosphorylations are the most common and extensively studied post-translational modification (PTM) of proteins in eukaryotes. They constitute a major regulatory mechanism, modulating protein function, protein-protein interactions, as well as subcellular localization. Phosphorylation sites are preferably located in intrinsically disordered regions and have been shown to trigger structural rearrangements and order-to-disorder transitions. They can therefore have a significant effect on protein backbone dynamics or conformation, but only sparse experimental data are available. To obtain a more general description of how and when phosphorylations have a significant effect on protein behavior, molecular dynamics (MD) currently provides the only suitable framework to study these effects at a large scale in atomistic detail. This study develops a systematic MD simulation framework to explore the influence of phosphorylations on the local backbone dynamics and conformational propensities of proteins. Through a series of glycine-backbone peptides, we studied the effects of amino acid residues including the three most common phosphorylations (Ser, Thr, and Tyr), on local backbone dynamics and conformational propensities. We further extended our study to investigate the interactions of all such residues between position i to positions i + 1, i + 2, i + 3, and i + 4 in such peptides. The final data set comprises structural ensembles for 3393 sequences with more than 1 μs of sampling for each ensemble. To validate the relevance of the results, the structural and conformational properties extracted from the MD simulations are compared to NMR data from the Biological Magnetic Resonance Data Bank. The systematic nature of this study enables the projection of the gained knowledge onto any phosphorylation site in the proteome and provides a general framework for the study of further PTMs. The full data set is publicly available, as a training and reference set.

Protein structure-function continuum model: Emerging nexuses between specificity, evolution, and structure

The rationale for replacing the old binary of structure-function with the trinity of structure, disorder, and function has gained considerable ground in recent years. A continuum model based on the expanded form of the existing paradigm can now subsume importance of both conformational flexibility and intrinsic disorder in protein function. The disorder is actually critical for understanding the protein-protein interactions in many regulatory processes, formation of membrane-less organelles, and our revised notions of specificity as amply illustrated by moonlighting proteins. While its importance in formation of amyloids and function of prions is often discussed, the roles of intrinsic disorder in infectious diseases and protein function under extreme conditions are also becoming clear. This review is an attempt to discuss how our current understanding of protein function, specificity, and evolution fit better with the continuum model. This integration of structure and disorder under a single model may bring greater clarity in our continuing quest for understanding proteins and molecular mechanisms of their functionality.

Machine Learning Subtle Conformational Change due to Phosphorylation in Intrinsically Disordered Proteins

Phosphorylation of intrinsically disordered proteins/regions (IDPs/IDRs) has a profound effect in biological functions such as cell signaling, protein folding or unfolding, and long-range allosteric effects. However, here we focus on two IDPs, namely 83-residue IDR transcription factor Ash1 and 92-residue long N-terminal region of CDK inhibitor Sic1 protein, found in Saccharomyces cerevisiae, for which experimental measurements of average conformational properties, namely, radius of gyration and structure factor, indicate negligible changes upon phosphorylation. Here, we show that a judicious dissection of conformational ensemble via combination of unsupervised machine learning and extensive molecular dynamics (MD) trajectories can highlight key differences and similarities among the phosphorylated and wild-type IDP. In particular, we develop Markov state model (MSM) using the latent-space dimensions of an autoencoder, trained using multi-microsecond long MD simulation trajectories. Examination of structural changes among the states, prior to and upon phosphorylation, captured several similarities and differences in their backbone contact maps, secondary structure, and torsion angles. Hydrogen bonding analysis revealed that phosphorylation not only increases the number of hydrogen bonds but also switches the pattern of hydrogen bonding between the backbone and side chain atoms with the phosphorylated residues. We also observe that although phosphorylation introduces salt bridges, there is a loss of the cation-π interaction. Phosphorylation also improved the probability for long-range hydrophobic contacts and also enhanced interaction with water molecules and improved the local structure of water as evident from the geometric order parameters. The observations on these machine-learnt states gave important insights, as it would otherwise be difficult to determine experimentally which is important, if we were to understand the role of phosphorylation of IDPs in their biological functions.

Complex Conformational Space of the RNA Polymerase II C-Terminal Domain upon Phosphorylation

Intrinsically disordered proteins (IDPs) have been closely studied during the past decade due to their importance in many biological processes. The disordered nature of this group of proteins makes it difficult to observe its full span of the conformational space using either experimental or computational studies. In this article, we explored the conformational space of the C-terminal domain (CTD) of RNA polymerase II (Pol II), which is also an intrinsically disordered low complexity domain, using enhanced sampling methods. We provided a detailed conformational analysis of model systems of CTD with different lengths; first with the last 44 residues of the human CTD sequence and finally the CTD model with 2-heptapeptide repeating units. We then investigated the effects of phosphorylation on CTD conformations by performing simulations at different phosphorylated states. We obtained broad conformational spaces in nonphosphorylated CTD models, and phosphorylation has complex effects on the conformations of the CTD. These complex effects depend on the length of the CTD, spacing between the multiple phosphorylation sites, ion coordination, and interactions with the nearby residues.

Conformational Plasticity in α-Synuclein and How Crowded Environment Modulates It

A 140-residue intrinsically disordered protein (IDP), α-synuclein (αS), is known to adopt conformations that are vastly plastic and susceptible to environmental cues and crowders. However, the inherently heterogeneous nature of αS has precluded a clear demarcation of its monomeric precursor between aggregation-prone and functionally relevant aggregation-resistant states and how a crowded environment could modulate their mutual dynamic equilibrium. Here, we identify an optimal set of distinct metastable states of αS in aqueous media by dissecting a 73 μs-long molecular dynamics ensemble via building a comprehensive Markov state model (MSM). Notably, the most populated metastable state corroborates with the dimension obtained from PRE-NMR studies of αS monomer, and it undergoes kinetic transition at diverse time scales with a weakly populated random-coil-like ensemble and a globular protein-like state. However, subjecting αS to a crowded environment results in a nonmonotonic compaction of these metastable conformations, thereby skewing the ensemble by either introducing new tertiary contacts or by reinforcing the innate contacts. The early stage of dimerization process is found to be considerably expedited in the presence of crowders, albeit promoting nonspecific interactions. Together with this, using an extensively sampled ensemble of αS, this exposition demonstrates that crowded environments can potentially modulate the conformational preferences of IDP that can either promote or inhibit aggregation events.

Exploring Structures and Dynamics of Protamine Molecules through Molecular Dynamics Simulations

Protamines are arginine-rich proteins that condense DNA in sperm. Despite their importance in reproduction, information on protamine structure is scarce. We, therefore, used molecular dynamics to examine the structures of salmon, bull P1, and human P1 protamines. The sizes and shapes of each protamine varied widely, indicating that they were disordered with structures covering a broad conformational landscape, from hairpin loop structures to extended coils. Despite their general disorder, the protamines did form secondary structures, including helices and hairpin loops. In eutherians, hairpins may promote disulfide bonding that facilitates protamine-DNA condensation, but the specifics of this bonding is not well established. We examined inter-residue distances in the simulations to predict residue pairs likely to form intramolecular bonds, leading to the identification of bonding pairs consistent with previous results in bull and human. These results support a model for eutherian protamine structures where a highly charged center is surrounded by disulfide-bond-stabilized loops.

Balanced Force Field ff03CMAP Improving the Dynamics Conformation Sampling of Phosphorylation Site

Phosphorylation plays a key role in plant biology, such as the accumulation of plant cells to form the observed proteome. Statistical analysis found that many phosphorylation sites are located in disordered regions. However, current force fields are mainly trained for structural proteins, which might not have the capacity to perfectly capture the dynamic conformation of the phosphorylated proteins. Therefore, we evaluated the performance of ff03CMAP, a balanced force field between structural and disordered proteins, for the sampling of the phosphorylated proteins. The test results of 11 different phosphorylated systems, including dipeptides, disordered proteins, folded proteins, and their complex, indicate that the ff03CMAP force field can better sample the conformations of phosphorylation sites for disordered proteins and disordered regions than ff03. For the solvent model, the results strongly suggest that the ff03CMAP force field with the TIP4PD water model is the best combination for the conformer sampling. Additional tests of CHARMM36m and FB18 force fields on two phosphorylated systems suggest that the overall performance of ff03CMAP is similar to that of FB18 and better than that of CHARMM36m. These results can help other researchers to choose suitable force field and solvent models to investigate the dynamic properties of phosphorylation proteins.

A Mechanistic Model for Cell Cycle Control in Which CDKs Act as Switches of Disordered Protein Phase Separation

Cyclin-dependent kinases (CDKs) are presumed to control the cell cycle by phosphorylating a large number of proteins involved in S-phase and mitosis, two mechanistically disparate biological processes. While the traditional qualitative model of CDK-mediated cell cycle control relies on differences in inherent substrate specificity between distinct CDK-cyclin complexes, they are largely dispensable according to the opposing quantitative model, which states that changes in the overall CDK activity level promote orderly progression through S-phase and mitosis. However, a mechanistic explanation for how such an activity can simultaneously regulate many distinct proteins is lacking. New evidence suggests that the CDK-dependent phosphorylation of ostensibly very diverse proteins might be achieved due to underlying similarity of phosphorylation sites and of the biochemical effects of their phosphorylation: they are preferentially located within intrinsically disordered regions of proteins that are components of membraneless organelles, and they regulate phase separation. Here, we review this evidence and suggest a mechanism for how a single enzyme’s activity can generate the dynamics required to remodel the cell at mitosis.

Phosphorylation tunes elongation propensity and cohesiveness of INCENP's intrinsically disordered region

The inner centromere protein, INCENP, is crucial for correct chromosome segregation during mitosis. It connects the kinase Aurora B to the inner centromere allowing this kinase to dynamically access its kinetochore targets. However, the function of its central, 440-residue long intrinsically disordered region (IDR) and its multiple phosphorylation sites is unclear. Here, we determined the conformational ensemble of INCENP's IDR, systematically varying the level of phosphorylation, using all-atom and coarse-grain molecular dynamics simulations. Our simulations show that phosphorylation expands INCENP's IDR, both locally and globally, mainly by increasing its overall net charge. The disordered region undergoes critical globule-to-coil conformational transitions and the transition temperature non-monotonically depends on the degree of phosphorylation, with a mildly phosphorylated case of neutral net charge featuring the highest collapse propensity. The IDR transitions from a multitude of globular states, accompanied by several specific internal contacts that reduce INCENP length by loop formation, to weakly interacting and highly extended coiled conformations. Phosphorylation critically shifts the population between these two regimes. It thereby influences cohesiveness and phase behavior of INCENP IDR assemblies, a feature presumably relevant for INCENP's function in the chromosomal passenger complex. Overall, we propose the disordered region of INCENP to act as a phosphorylation-regulated and length-variable component, within the previously defined "dog-leash" model, that thereby regulates how Aurora B reaches its targets for proper chromosome segregation.