Generation of the configurational ensemble of an intrinsically disordered protein from unbiased molecular dynamics simulation

Drude2019IDPC polarizable force field reveals structure-function relationship of insulin

Intrinsically disordered proteins (IDPs) lack stable tertiary structures under physiological conditions, yet play key roles in biological processes and associated with human complex diseases. Their conformational characteristics and high content of charged residues make the use of polarizable force fields an advantageous for simulating IDPs. The Drude2019IDP polarizable force field, previously introduced, has demonstrated comprehensive enhancements and improvements in dipeptides, short peptides, and IDPs, achieving a balanced sampling between IDPs and structured proteins. However, the performance in simulating 5 dipeptides was found to be underestimate. Therefore, we individually performed reweighting and grid-based energy correction map (CMAP) optimization for these 5 dipeptides, resulting in the enhanced Drude2019IDPC force field. The performance of Drude2019IDPC was evaluated with 5 dipeptides, 5 disordered short peptides, and a representative IDP. The results demonstrated a marked improvement comparing with original Drude2019IDP. To further substantiate the capabilities of Drude2019IDPC, MD simulation and Markov state model (MSM) were applied to wild type and mutant for insulin, to elucidate the difference of conformational characteristics and transition path. The findings reveal that mutation can maintain the monomorphic characteristics, providing insights for engineered insulin development. These results indicate that Drude2019IDPC could be used to reveal the structure-function relationship for other proteins.

Statistical accuracy of molecular dynamics-based methods for sampling conformational ensembles of disordered proteins

The characterization of the statistical ensemble of conformations of intrinsically disordered regions (IDRs) is a great challenge both from experimental and computational points of view. In this respect, a number of protocols have been developed using molecular dynamics (MD) simulations to sample the huge conformational space of the molecule. In this work, we consider one of the best methods available, replica exchange solute tempering (REST), as a reference to compare the results obtained using this method with the results obtained using other methods, in terms of experimentally measurable quantities. Along with the methods assessed, we propose here a novel protocol called probabilistic MD chain growth (PMD-CG), which combines the flexible-meccano and hierarchical chain growth methods with the statistical data obtained from tripeptide MD trajectories as the starting point. The system chosen for testing is a 20-residue region from the C-terminal domain of the p53 tumor suppressor protein (p53-CTD). Our results show that PMD-CG provides an ensemble of conformations extremely quickly, after suitable computation of the conformational pool for all peptide triplets of the IDR sequence. The measurable quantities computed on the ensemble of conformations agree well with those based on the REST conformational ensemble.

Quantitative Ensemble Interpretation of Membrane Paramagnetic Relaxation Enhancement (mPRE) for Studying Membrane-Associated Intrinsically Disordered Proteins

An understanding of the functional role played by a membrane-associated intrinsically disordered protein (IDP) requires characterization of its heterogeneous conformations as well as its poses relative to the membranes, which is of great interest but technically challenging. Here, we explore the membrane paramagnetic relaxation enhancement (mPRE) for constructing ensembles of IDPs that dynamically associate with membrane mimetics incorporating spin-labeled lipids. To accurately interpret the mPRE Γ2 rates, both the dynamics of IDPs and spin probe molecules are taken into account, with the latter described by a weighted three-dimensional (3D) grid model built based on all-atom simulations. The IDP internal conformations, orientations, and immersion depths in lipid bilayers are comprehensively optimized in the Γ2-based ensemble modeling. Our approach is tested and validated on the example of POPG bicelle-bound disordered cytoplasmic domain of CD3ε (CD3εCD), a component of the T-cell receptor (TCR) complex. The mPRE-derived CD3εCD ensemble provides new insights into the IDP-membrane fuzzy association, in particular for the tyrosine-based signaling motif that plays a critical role in TCR signaling. The comparative analysis of the ensembles for wild-type CD3εCD and mutants that mimic the mono- and dual-phosphorylation effects suggests a delicate membrane regulatory mechanism for activation and inhibition of the TCR activity.

Molecular Docking of Intrinsically Disordered Proteins: Challenges and Strategies

Intrinsically disordered proteins (IDPs) are a novel class of proteins that have established a significant importance and attention within a very short period of time. These proteins are essentially characterized by their inherent structural disorder, encoded mainly by their amino acid sequences. The profound abundance of IDPs and intrinsically disordered regions (IDRs) in the biological world delineates their deep-rooted functionality. IDPs and IDRs convey such extensive functionality through their unique dynamic nature, which enables them to carry out huge number of multifaceted biomolecular interactions and make them "interaction hub" of the cellular systems. Additionally, with such widespread functions, their misfunctioning is also intimately associated with multiple diseases. Thus, understanding the dynamic heterogeneity of various IDPs along with their interactions with respective binding partners is an important field with immense potentials in biomolecular research. In this context, molecular docking-based computational approaches have proven to be remarkable in case of ordered proteins. Molecular docking methods essentially model the biomolecular interactions in both structural and energetic terms and use this information to characterize the putative interactions between the two participant molecules. However, direct applications of the conventional docking methods to study IDPs are largely limited by their structural heterogeneity and demands for unique IDP-centric strategies. Thus, in this chapter, we have presented an overview of current methodologies for successful docking operations involving IDPs and IDRs. These specialized methods majorly include the ensemble-based and fragment-based approaches with their own benefits and limitations. More recently, artificial intelligence and machine learning-assisted approaches are also used to significantly reduce the complexity and computational burden associated with various docking applications. Thus, this chapter aims to provide a comprehensive summary of major challenges and recent advancements of molecular docking approaches in the IDP field for their better utilization and greater applicability.Asp (D).

The role of solvation on the conformational landscape of α-synuclein

Native ion mobility mass spectrometry has been used extensively to characterize ensembles of intrinsically disordered protein (IDP) conformers, but the extent to which the gaseous measurements provide realistic pictures of the solution conformations for such flexible proteins remains unclear. Therefore, we systematically studied the relationship between the solution and gaseous structural ensembles by measuring electrospray charge state and collision cross section (CCS) distributions for cationic and anionic forms of α-synuclein (αSN), an anionic protein in solution, as well as directly probed gas phase residue to residue distances via ion/ion reactions between gaseous α-synuclein cations and disulfonic acid linkers that form strong electrostatic bonds. We also combined results from in-solution protein crosslinking identified from native tandem mass spectrometry (MS/MS) with an initial αSN ensemble generated computationally by IDPConformerGenerator to generate an experimentally restrained solution ensemble of αSN. CCS distributions were directly calculated for the solution ensembles determined by NMR and compared to predicted gaseous conformers. While charge state and collision cross section distributions are useful for qualitatively describing the relative structural dynamics of proteins and major conformational changes induced by changes to solution states, the predicted and measured gas phase conformers include subpopulations that are significantly different than those expected from completely "freezing" solution conformations and preserving them in the gas phase. However, insights were gained on the various roles of solvent in stabilizing various conformers for extremely dynamic proteins like α-synuclein.

Sequence-Tunable Phase Behavior and Intrinsic Fluorescence in Dynamically Interacting Peptides

A conceptual framework towards understanding biological condensed phases is emerging, derived from biological, biomimetic, and synthetic sequences. However, de novo peptide condensate design remains a challenge due to an incomplete understanding of the structural and interactive complexity. We designed peptide modules based on a simple repeat motif composed of tripeptide spacers (GSG, SGS, GLG) interspersed with adhesive amino acids (R/H and Y). We show, using sequence editing and a combination of computation and experiment, that n→π* interactions in GLG backbones are a dominant factor in providing sufficient backbone structure, which in turn regulates the water interface, collectively promoting liquid droplet formation. Moreover, these R(GLG)Y and H(GLG)Y condensates unexpectedly display sequence-dependent emission that is a consequence of their non-covalent network interactions, and readily observable by confocal microscopy.

Water molecule ordering on the surface of an intrinsically disordered protein

The dynamics and local structure of the hydration water on surfaces of folded proteins have been extensively investigated. However, our knowledge of the hydration of intrinsically disordered proteins (IDPs) is more limited. Here, we compare the local structure of water molecules hydrating a globular protein, lysozyme, and the intrinsically disordered N-terminal of c-Src kinase (SH4UD) using molecular dynamics simulation. The radial distributions from the protein surface of the first and the second hydration shells are similar for the folded protein and the IDP. However, water molecules in the first hydration shell of both the folded protein and the IDP are perturbed from the bulk. This perturbation involves a loss of tetrahedrality, which is, however, significantly more marked for the folded protein than the IDP. This difference arises from an increase in the first hydration shell of the IDP of the fraction of hydration water molecules interacting with oxygen. The water ordering is independent of the compactness of the IDP. In contrast, the lifetimes of water molecules in the first hydration shell increase with IDP compactness, indicating a significant impact of IDP configuration on water surface pocket kinetics, which here is linked to differential pocket volumes and polarities.

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.

Intrinsic disorder and conformational coexistence in auxin coreceptors

AUXIN/INDOLE 3-ACETIC ACID (Aux/IAA) transcriptional repressor proteins and the TRANSPORT INHIBITOR RESISTANT 1/AUXIN SIGNALING F-BOX (TIR1/AFB) proteins to which they bind act as auxin coreceptors. While the structure of TIR1 has been solved, structural characterization of the regions of the Aux/IAA protein responsible for auxin perception has been complicated by their predicted disorder. Here, we use NMR, CD and molecular dynamics simulation to investigate the N-terminal domains of the Aux/IAA protein IAA17/AXR3. We show that despite the conformational flexibility of the region, a critical W-P bond in the core of the Aux/IAA degron motif occurs at a strikingly high (1:1) ratio of cis to trans isomers, consistent with the requirement of the cis conformer for the formation of the fully-docked receptor complex. We show that the N-terminal half of AXR3 is a mixture of multiple transiently structured conformations with a propensity for two predominant and distinct conformational subpopulations within the overall ensemble. These two states were modeled together with the C-terminal PB1 domain to provide the first complete simulation of an Aux/IAA. Using MD to recreate the assembly of each complex in the presence of auxin, both structural arrangements were shown to engage with the TIR1 receptor, and contact maps from the simulations match closely observations of NMR signal-decreases. Together, our results and approach provide a platform for exploring the functional significance of variation in the Aux/IAA coreceptor family and for understanding the role of intrinsic disorder in auxin signal transduction and other signaling systems.

Structural characterization of an intrinsically disordered protein complex using integrated small-angle neutron scattering and computing

Characterizing structural ensembles of intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) of proteins is essential for studying structure-function relationships. Due to the different neutron scattering lengths of hydrogen and deuterium, selective labeling and contrast matching in small-angle neutron scattering (SANS) becomes an effective tool to study dynamic structures of disordered systems. However, experimental timescales typically capture measurements averaged over multiple conformations, leaving complex SANS data for disentanglement. We hereby demonstrate an integrated method to elucidate the structural ensemble of a complex formed by two IDRs. We use data from both full contrast and contrast matching with residue-specific deuterium labeling SANS experiments, microsecond all-atom molecular dynamics (MD) simulations with four molecular mechanics force fields, and an autoencoder-based deep learning (DL) algorithm. From our combined approach, we show that selective deuteration provides additional information that helps characterize structural ensembles. We find that among the four force fields, a99SB-disp and CHARMM36m show the strongest agreement with SANS and NMR experiments. In addition, our DL algorithm not only complements conventional structural analysis methods but also successfully differentiates NMR and MD structures which are indistinguishable on the free energy surface. Lastly, we present an ensemble that describes experimental SANS and NMR data better than MD ensembles generated by one single force field and reveal three clusters of distinct conformations. Our results demonstrate a new integrated approach for characterizing structural ensembles of IDPs.

Not Only Expansion: Proline Content and Density Also Induce Disordered Protein Conformation Compaction

Intrinsically disordered proteins (IDPs) adopt a wide array of different conformations that can be constrained by the presence of proline residues, which are frequently found in IDPs. To assess the effects of proline, we designed a series of peptides that differ with respect to the number of prolines in the sequence and their organization. Using high-resolution atomistic molecular dynamics simulations, we found that accounting for whether the proline residues are clustered or isolated contributed significantly to explaining deviations in the experimentally-determined gyration radii of IDPs from the values expected based on the Flory scaling-law. By contrast, total proline content makes smaller contribution to explaining the effect of prolines on IDP conformation. Proline residues exhibit opposing effects depending on their organizational pattern in the IDP sequence. Clustered prolines (i.e., prolines with ≤2 intervening non-proline residues) result in expanded peptide conformations whereas isolated prolines (i.e., prolines with >2 intervening non-proline residues) impose compacted conformations. Clustered prolines were estimated to induce an expansion of ∼20% in IDP dimension (via formation of PPII structural elements) whereas isolated prolines were estimated to induce a compaction of ∼10% in IDP dimension (via the formation of backbone turns). This dual role of prolines provides a mechanism for conformational switching that does not rely on the kinetically much slower isomerization of cis proline to the trans form. Bioinformatic analysis demonstrates high populations of both isolated and clustered prolines and implementing them in coarse-grained molecular dynamics models illustrates that they improve the characterization of the conformational ensembles of IDPs.

Converging PMF Calculations of Antibiotic Permeation across an Outer Membrane Porin with Subkilocalorie per Mole Accuracy

The emergence of multidrug-resistant pathogens led to a critical need for new antibiotics. A key property of effective antibiotics against Gram-negative bacteria is their ability to permeate through the bacterial outer membrane via transmembrane porin proteins. Molecular dynamics (MD) simulations are, in principle, capable of modeling antibiotic permeation across outer membrane porins (OMPs). However, owing to sampling problems, it has remained challenging to obtain converged potentials of mean force (PMFs) for antibiotic permeation across OMPs. Here, we investigated the convergence of PMFs along a single collective variable aimed at quantifying the permeation of the antibiotic fosmidomycin across the OprO porin. We compared standard umbrella sampling (US) with three advanced flavors of the US technique: (i) Hamiltonian replica exchange with solute tempering in combination with US, (ii) simulated tempering-enhanced US, and (iii) replica-exchange US. To quantify the PMF convergence and to reveal hysteresis problems, we computed several independent sets of US simulations starting from pulling simulations in the outward and inward permeation directions. We find that replica-exchange US in combination with well-chosen restraints is highly successful for obtaining converged PMFs of fosmidomycin permeation through OprO, reaching PMFs converged to subkilocalorie per mole accuracy.

A synergy between site-specific and transient interactions drives the phase separation of a disordered, low-complexity domain

TAR DNA-binding protein 43 (TDP-43) is involved in key processes in RNA metabolism and is frequently implicated in many neurodegenerative diseases, including amyotrophic lateral sclerosis and frontotemporal dementia. The prion-like, disordered C-terminal domain (CTD) of TDP-43 is aggregation-prone, can undergo liquid-liquid phase separation (LLPS) in isolation, and is critical for phase separation (PS) of the full-length protein under physiological conditions. While a short conserved helical region (CR, spanning residues 319-341) promotes oligomerization and is essential for LLPS, aromatic residues in the flanking disordered regions (QN-rich, IDR1/2) are also found to play a critical role in PS and aggregation. Compared with other phase-separating proteins, TDP-43 CTD has a notably distinct sequence composition including many aliphatic residues such as methionine and leucine. Aliphatic residues were previously suggested to modulate the apparent viscosity of the resulting phases, but their direct contribution toward CTD phase separation has been relatively ignored. Using multiscale simulations coupled with in vitro saturation concentration (csat) measurements, we identified the importance of aromatic residues while also suggesting an essential role for aliphatic methionine residues in promoting single-chain compaction and LLPS. Surprisingly, NMR experiments showed that transient interactions involving phenylalanine and methionine residues in the disordered flanking regions can directly enhance site-specific, CR-mediated intermolecular association. Overall, our work highlights an underappreciated mode of biomolecular recognition, wherein both transient and site-specific hydrophobic interactions act synergistically to drive the oligomerization and phase separation of a disordered, low-complexity domain.

Clustering Heterogeneous Conformational Ensembles of Intrinsically Disordered Proteins with t-Distributed Stochastic Neighbor Embedding

Intrinsically disordered proteins (IDPs) populate a range of conformations that are best described by a heterogeneous ensemble. Grouping an IDP ensemble into "structurally similar" clusters for visualization, interpretation, and analysis purposes is a much-desired but formidable task, as the conformational space of IDPs is inherently high-dimensional and reduction techniques often result in ambiguous classifications. Here, we employ the t-distributed stochastic neighbor embedding (t-SNE) technique to generate homogeneous clusters of IDP conformations from the full heterogeneous ensemble. We illustrate the utility of t-SNE by clustering conformations of two disordered proteins, Aβ42, and α-synuclein, in their APO states and when bound to small molecule ligands. Our results shed light on ordered substates within disordered ensembles and provide structural and mechanistic insights into binding modes that confer specificity and affinity in IDP ligand binding. t-SNE projections preserve the local neighborhood information, provide interpretable visualizations of the conformational heterogeneity within each ensemble, and enable the quantification of cluster populations and their relative shifts upon ligand binding. Our approach provides a new framework for detailed investigations of the thermodynamics and kinetics of IDP ligand binding and will aid rational drug design for IDPs.

Generation of unfolded outer membrane protein ensembles defined by hydrodynamic properties

Outer membrane proteins (OMPs) must exist as an unfolded ensemble while interacting with a chaperone network in the periplasm of Gram-negative bacteria. Here, we developed a method to model unfolded OMP (uOMP) conformational ensembles using the experimental properties of two well-studied OMPs. The overall sizes and shapes of the unfolded ensembles in the absence of a denaturant were experimentally defined by measuring the sedimentation coefficient as a function of urea concentration. We used these data to model a full range of unfolded conformations by parameterizing a targeted coarse-grained simulation protocol. The ensemble members were further refined by short molecular dynamics simulations to reflect proper torsion angles. The final conformational ensembles have polymer properties different from unfolded soluble and intrinsically disordered proteins and reveal inherent differences in the unfolded states that necessitate further investigation. Building these uOMP ensembles advances the understanding of OMP biogenesis and provides essential information for interpreting structures of uOMP-chaperone complexes.

Sequence controlled secondary structure is important for the site-selectivity of lanthipeptide cyclization

Lanthipeptides are ribosomally synthesized and post-translationally modified peptides that are generated from precursor peptides through a dehydration and cyclization process. ProcM, a class II lanthipeptide synthetase, demonstrates high substrate tolerance. It is enigmatic that a single enzyme can catalyze the cyclization process of many substrates with high fidelity. Previous studies suggested that the site-selectivity of lanthionine formation is determined by substrate sequence rather than by the enzyme. However, exactly how substrate sequence contributes to site-selective lanthipeptide biosynthesis is not clear. In this study, we performed molecular dynamic simulations for ProcA3.3 variants to explore how the predicted solution structure of the substrate without enzyme correlates to the final product formation. Our simulation results support a model in which the secondary structure of the core peptide is important for the final product's ring pattern for the substrates investigated. We also demonstrate that the dehydration step in the biosynthesis pathway does not influence the site-selectivity of ring formation. In addition, we performed simulation for ProcA1.1 and 2.8, which are well-suited candidates to investigate the connection between order of ring formation and solution structure. Simulation results indicate that in both cases, C-terminal ring formation is more likely which was supported by experimental results. Our findings indicate that the substrate sequence and its solution structure can be used to predict the site-selectivity and order of ring formation, and that secondary structure is a crucial factor influencing the site-selectivity. Taken together, these findings will facilitate our understanding of the lanthipeptide biosynthetic mechanism and accelerate bioengineering efforts for lanthipeptide-derived products.

Benchmarking Molecular Dynamics Force Fields for All-Atom Simulations of Biological Condensates

Proteins containing intrinsically disordered regions are integral parts of the cellular signaling pathways and common components of biological condensates. Point mutations in the protein sequence, genetic at birth or acquired through aging, can alter the properties of the condensates, marking the onset of neurodegenerative diseases such as ALS and dementia. While the all-atom molecular dynamics method can, in principle, elucidate the conformational changes that arise from point mutations, the applications of this method to protein condensate systems is conditioned upon the availability of molecular force fields that can accurately describe both structured and disordered regions of such proteins. Using the special-purpose Anton 2 supercomputer, we benchmarked the efficacy of nine presently available molecular force fields in describing the structure and dynamics of a Fused in sarcoma (FUS) protein. Five-microsecond simulations of the full-length FUS protein characterized the effect of the force field on the global conformation of the protein, self-interactions among its side chains, solvent accessible surface area, and the diffusion constant. Using the results of dynamic light scattering as a benchmark for the FUS radius of gyration, we identified several force fields that produced FUS conformations within the experimental range. Next, we used these force fields to perform ten-microsecond simulations of two structured RNA binding domains of FUS bound to their respective RNA targets, finding the choice of the force field to affect stability of the RNA-FUS complex. Taken together, our data suggest that a combination of protein and RNA force fields sharing a common four-point water model provides an optimal description of proteins containing both disordered and structured regions and RNA-protein interactions. To make simulations of such systems available beyond the Anton 2 machines, we describe and validate implementation of the best performing force fields in a publicly available molecular dynamics program NAMD. Our NAMD implementation enables simulations of large (tens of millions of atoms) biological condensate systems and makes such simulations accessible to a broader scientific community.

Dissecting the Effect of ALS Mutation G335D on the Early Aggregation of the TDP-43 Amyloidogenic Core Peptide: Helix-to-β-Sheet Transition and Conformational Shift

The aggregation of TAR DNA-binding protein of 43 kDa (TDP-43) into fibrillary deposits is associated with amyotrophic lateral sclerosis (ALS). The 311-360 fragment of TDP-43 (TDP-43311-360), the amyloidogenic core region, can spontaneously aggregate into fibrils, and the ALS-associated mutation G335D has an enhanced effect on TDP-43311-360 fibrillization. However, the molecular mechanism underlying G335D-enhanced aggregation at atomic level remains largely unknown. By utilizing all-atom molecular dynamics (MD) and replica exchange with solute tempering 2 (REST2) simulations, we investigated influences of G335D on the dimerization (the first step of aggregation) and conformational ensemble of the TDP-43311-360 peptide. Our simulations show that G335D mutation increases inter-peptide interactions, especially inter-peptide hydrogen-bonding interactions in which the mutant site has a relatively large contribution, and enhances the dimerization of TDP-43311-360 peptides. The α-helix regions in the NMR-resolved conformation of the TDP-43311-360 monomer (321-330 and 335-343) play an essential role in the formation of the dimer. G335D mutation induces helix unfolding and promotes α-to-β conversion. G335D mutation alters the conformational distribution of TDP-43311-360 dimers and causes population shift from helix-rich to β-sheet-rich conformations, which facilitates the fibrillization of the TDP-43311-360 peptide. Our MD and REST2 simulation results suggest that the 321-330 region is of paramount importance to α-to-β transition and could be the initiation site for TDP-43311-360 fibrillization. Our work reveals the mechanism underlying the enhanced aggregation propensity of the G335D TDP-43311-360 peptide, which provides atomistic insights into the G335D mutation-caused pathogenicity of TDP-43 protein.

Catch bond models may explain how force amplifies TCR signaling and antigen discrimination

The TCR integrates forces in its triggering process upon interaction with pMHC. Force elicits TCR catch-slip bonds with strong pMHCs but slip-only bonds with weak pMHCs. We develop two models and apply them to analyze 55 datasets, demonstrating the models' ability to quantitatively integrate and classify a broad range of bond behaviors and biological activities. Comparing to a generic two-state model, our models can distinguish class I from class II MHCs and correlate their structural parameters with the TCR/pMHC's potency to trigger T cell activation. The models are tested by mutagenesis using an MHC and a TCR mutated to alter conformation changes. The extensive comparisons between theory and experiment provide model validation and testable hypothesis regarding specific conformational changes that control bond profiles, thereby suggesting structural mechanisms for the inner workings of the TCR mechanosensing machinery and plausible explanations of why and how force may amplify TCR signaling and antigen discrimination.

Energy landscapes of Aβ monomers are sculpted in accordance with Ostwald's rule of stages

The transition from a disordered to an assembly-competent monomeric state (N*) in amyloidogenic sequences is a crucial event in the aggregation cascade. Using a well-calibrated model for intrinsically disordered proteins (IDPs), we show that the N* states, which bear considerable resemblance to the polymorphic fibril structures found in experiments, not only appear as excitations in the free energy landscapes of Aβ40 and Aβ42, but also initiate the aggregation cascade. For Aβ42, the transitions to the different N* states are in accord with Ostwald's rule of stages, with the least stable structures forming ahead of thermodynamically favored ones. The Aβ40 and Aβ42 monomer landscapes exhibit different extents of local frustration, which we show have profound implications in dictating subsequent self-assembly. Using kinetic transition networks, we illustrate that the most favored dimerization routes proceed via N* states. We argue that Ostwald's rule also holds for the aggregation of fused in sarcoma and polyglutamine proteins.

ALS-Linked A315T and A315E Mutations Enhance β-Barrel Formation of the TDP-43307-319 Hexamer: A REST2 Simulation Study

Pathogenic mutations of transactivation response element DNA-binding protein 43 (TDP-43) are closely linked with amyotrophic lateral sclerosis (ALS). It was recently reported that two ALS-linked familial mutants A315T and A315E of TDP-43_307-319 peptides can self-assemble into oligomers including tetramers, hexamers, and octamers, among which hexamers were suggested to form the β-barrel structure. However, due to the transient nature of oligomers, their conformational properties and the atomic mechanisms underlying the β-barrel formation remain largely elusive. Herein, we investigated the hexameric conformational distributions of the wild-type (WT) TDP-43_307-319 fragment and its A315T and A315E mutants by performing all-atom explicit-solvent replica exchange with solute tempering 2 simulations. Our simulations reveal that each peptide can self-assemble into diverse conformations including ordered β-barrels, bilayer β-sheets and/or monolayer β-sheets, and disordered complexes. A315T and A315E mutants display higher propensity to form β-barrel structures than the WT, which provides atomic explanation for their enhanced neurotoxicity reported previously. Detailed interaction analysis shows that A315T and A315E mutations increase inter-molecular interactions. Also, the β-barrel structures formed by the three different peptides are stabilized by distinct inter-peptide side-chain hydrogen bonding, hydrophobic, and aromatic stacking interactions. This study demonstrates the enhanced β-barrel formation of the TDP-43_307-319 hexamer by the pathogenic A315T and A315E mutations and reveals the underlying molecular determinants, which may be helpful for in-depth understanding of the ALS-mutation-induced neurotoxicity of TDP-43 protein.

Benchmarking Molecular Dynamics Force Fields for All-Atom Simulations of Biological Condensates

Proteins containing intrinsically disordered regions are integral components of the cellular signaling pathways and common components of biological condensates. Point mutations in the protein sequence, genetic at birth or acquired through aging, can alter the properties of the condensates, marking the onset of neurodegenerative diseases such as ALS and dementia. While all-atom molecular dynamics method can, in principle, elucidate the conformational changes responsible for the aging of the condensate, the applications of this method to protein condensate systems is conditioned by the availability of molecular force fields that can accurately describe both structured and disordered regions of such proteins. Using the special-purpose Anton 2 supercomputer, we benchmarked the efficacy of nine presently available molecular force fields in describing the structure and dynamics of a Fused in sarcoma (FUS) protein. Five-microsecond simulations of the full-length FUS protein characterized the effect of the force field on the global conformation of the protein, self-interactions among its side chains, solvent accessible surface area and the diffusion constant. Using the results of dynamic light scattering as a benchmark for the FUS radius of gyration, we identified several force field that produced FUS conformations within the experimental range. Next, we used these force fields to perform ten-microsecond simulations of two structured RNA binding domains of FUS bound to their respective RNA targets, finding the choice of the force field to affect stability of the RNA-FUS complex. Taken together, our data suggest that a combination of protein and RNA force fields sharing a common four-point water model provides an optimal description of proteins containing both disordered and structured regions and RNA-protein interactions. To make simulations of such systems available beyond the Anton 2 machines, we describe and validate implementation of the best performing force fields in a publicly available molecular dynamics program NAMD. Our NAMD implementation enables simulations of large (tens of millions of atoms) biological condensate systems and makes such simulations accessible to a broader scientific community.

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Disordered Domain Shifts the Conformational Ensemble of the Folded Regulatory Domain of the Multidomain Oncoprotein c-Src

c-Src kinase is a multidomain non-receptor tyrosine kinase that aberrantly phosphorylates several signaling proteins in cancers. Although the structural properties of the regulatory domains (SH3-SH2) and the catalytic kinase domain have been extensively characterized, there is less knowledge about the N-terminal disordered region (SH4UD) and its interactions with the other c-Src domains. Here, we used domain-selective isotopic labeling combined with the small-angle neutron scattering contrast matching technique to study SH4UD interactions with SH3-SH2. Our results show that in the presence of SH4UD, the radius of gyration (R_g) of SH3-SH2 increases, indicating that it has a more extended conformation. Hamiltonian replica exchange molecular dynamics simulations provide a detailed molecular description of the structural changes in SH4UD-SH3-SH2 and show that the regulatory loops of SH3 undergo significant conformational changes in the presence of SH4UD, while SH2 remains largely unchanged. Overall, this study highlights how a disordered region can drive a folded region of a multidomain protein to become flexible, which may be important for allosteric interactions with binding partners. This may help in the design of therapeutic interventions that target the regulatory domains of this important family of kinases.

Improved predictions of phase behaviour of intrinsically disordered proteins by tuning the interaction range

The formation and viscoelastic properties of condensates of intrinsically disordered proteins (IDPs) is dictated by amino acid sequence and solution conditions. Because of the involvement of biomolecular condensates in cell physiology and disease, advancing our understanding of the relationship between protein sequence and phase separation (PS) may have important implications in the formulation of new therapeutic hypotheses. Here, we present CALVADOS 2, a coarse-grained model of IDPs that accurately predicts conformational properties and propensities to undergo PS for diverse sequences and solution conditions. In particular, we systematically study the effect of varying the range of the nonionic interactions and use our findings to improve the temperature scale of the model. We further optimize the residue-specific model parameters against experimental data on the conformational properties of 55 proteins, while also leveraging 70 hydrophobicity scales from the literature to avoid overfitting the training data. Extensive testing shows that the model accurately predicts chain compaction and PS propensity for sequences of diverse length and charge patterning, as well as at different temperatures and salt concentrations.

Improved predictions of phase behaviour of intrinsically disordered proteins by tuning the interaction range

The formation and viscoelastic properties of condensates of intrinsically disordered proteins (IDPs) is dictated by amino acid sequence and solution conditions. Because of the involvement of biomolecular condensates in cell physiology and disease, advancing our understanding of the relationship between protein sequence and phase separation (PS) may have important implications in the formulation of new therapeutic hypotheses. Here, we present CALVADOS 2, a coarse-grained model of IDPs that accurately predicts conformational properties and propensities to undergo PS for diverse sequences and solution conditions. In particular, we systematically study the effect of varying the range of the nonionic interactions and use our findings to improve the temperature scale of the model. We further optimize the residue-specific model parameters against experimental data on the conformational properties of 55 proteins, while also leveraging 70 hydrophobicity scales from the literature to avoid overfitting the training data. Extensive testing shows that the model accurately predicts chain compaction and PS propensity for sequences of diverse length and charge patterning, as well as at different temperatures and salt concentrations.

Myofilament-associated proteins with intrinsic disorder (MAPIDs) and their resolution by computational modeling

The cardiac sarcomere is a cellular structure in the heart that enables muscle cells to contract. Dozens of proteins belong to the cardiac sarcomere, which work in tandem to generate force and adapt to demands on cardiac output. Intriguingly, the majority of these proteins have significant intrinsic disorder that contributes to their functions, yet the biophysics of these intrinsically disordered regions (IDRs) have been characterized in limited detail. In this review, we first enumerate these myofilament-associated proteins with intrinsic disorder (MAPIDs) and recent biophysical studies to characterize their IDRs. We secondly summarize the biophysics governing IDR properties and the state-of-the-art in computational tools toward MAPID identification and characterization of their conformation ensembles. We conclude with an overview of future computational approaches toward broadening the understanding of intrinsic disorder in the cardiac sarcomere.

Performance evaluation of the balanced force field ff03CMAP for intrinsically disordered and ordered proteins

Intrinsically disordered proteins (IDPs) have been found to be closely associated with various human diseases. Because IDPs have no fixed tertiary structure under physiological conditions, current experimental methods, such as X-ray spectroscopy, NMR, and CryoEM, cannot capture all the dynamic conformations. Molecular dynamics simulation is an useful tool that is widely used to study the conformer distributions of IDPs and has become an important complementary tool for experimental methods. However, the accuracy of MD simulations directly depends on utilizing a precise force field. Recently a CMAP optimized force field based on the Amber ff03 force field (termed ff03CMAP herein) was developed for a balanced sampling of IDPs and folded proteins. In order to further evaluate the performance, more types of disordered and ordered proteins were used to test the ability for conformer sampling. The results showed that simulated chemical shifts, J-coupling, and R_g distribution with the ff03CMAP force field were in better agreement with NMR measurements and were more accurate than those with the ff03 force field. The sampling conformations by ff03CMAP were more diverse than those of ff03. At the same time, ff03CMAP could stabilize the conformers of the ordered proteins. These findings indicate that ff03CMAP can be widely used to sample diverse conformers for proteins, including the intrinsically disordered regions.

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.

Guide to studying intrinsically disordered proteins by high-speed atomic force microscopy

Intrinsically disordered proteins (IDPs) are partially or entirely disordered. Their intrinsically disordered regions (IDRs) dynamically explore a wide range of structural space by their highly flexible nature. Due to this distinct feature largely different from structured proteins, conventional structural analyses relying on ensemble averaging is unsuitable for characterizing the dynamic structure of IDPs. Therefore, single-molecule measurement tools have been desired in IDP studies. High-speed atomic force microscopy (HS-AFM) is a unique tool that allows us to directly visualize single biomolecules at 2-3 nm lateral and ∼ 0.1 nm vertical spatial resolution, and at sub-100 ms temporal resolution under near physiological conditions, without any chemical labeling. HS-AFM has been successfully used not only to characterize the shape and motion of IDP molecules but also to visualize their function-related dynamics. In this article, after reviewing the principle and current performances of HS-AFM, we describe experimental considerations in the HS-AFM imaging of IDPs and methods to quantify molecular features from captured images. Finally, we outline recent HS-AFM imaging studies of IDPs.

Sequence-Dependent Backbone Dynamics of Intrinsically Disordered Proteins

For intrinsically disordered proteins (IDPs), a pressing question is how sequence codes for function. Dynamics serves as a crucial link, reminiscent of the role of structure in sequence-function relations of structured proteins. To define general rules governing sequence-dependent backbone dynamics, we carried out long molecular dynamics simulations of eight IDPs. Blocks of residues exhibiting large amplitudes in slow dynamics are rigidified by local inter-residue interactions or secondary structures. A long region or an entire IDP can be slowed down by long-range contacts or secondary-structure packing. On the other hand, glycines promote fast dynamics and either demarcate rigid blocks or facilitate multiple modes of local and long-range inter-residue interactions. The sequence-dependent backbone dynamics endows IDPs with versatile response to binding partners, with some blocks recalcitrant while others readily adapting to intermolecular interactions.

Polarizable Force Field of Intrinsically Disordered Proteins with CMAP and Reweighting Optimization

Intrinsically disordered proteins (IDPs) are highly structurally heterogeneous without a specific tertiary structure under physiology conditions and play key roles in the development of human diseases. Due to the characteristics of diverse conformations, as one of the important methods, molecular dynamics simulation can complement information for experimental methods. Because of the enrichment for charged amino acids for IDPs, polarizable force fields should be a good choice for the simulation of IDPs. However, current polarizable force fields are limited in sampling conformer features of IDPs. Therefore, a polarizable force field was released and named Drude2019IDP based on Drude2019 with reweighting and grid-based potential energy correction map optimization. In order to evaluate the performance of Drude2019IDP, 16 dipeptides, 18 short peptides, 3 representative IDPs, and 5 structural proteins were simulated. The results show that the NMR observables driven by Drude2019IDP are in better agreement with the experiment data than those by Drude2019 on short peptides and IDPs. Drude2019IDP can sample more diverse conformations than Drude2019. Furthermore, the performances of the two force fields are similar to the sample ordered proteins. These results confirm that the developed Drude2019IDP can improve the reproduction of conformers for intrinsically disordered proteins and can be used to gain insight into the paradigm of sequence-disorder for IDPs.

eIF4G1 N-terminal intrinsically disordered domain is a multi-docking station for RNA, Pab1, Pub1, and self-assembly

Yeast eIF4G1 interacts with RNA binding proteins (RBPs) like Pab1 and Pub1 affecting its function in translation initiation and stress granules formation. We present an NMR and SAXS study of the N-terminal intrinsically disordered region of eIF4G1 (residues 1-249) and its interactions with Pub1, Pab1 and RNA. The conformational ensemble of eIF4G11-249 shows an α-helix within the BOX3 conserved element and a dynamic network of fuzzy π-π and π-cation interactions involving arginine and aromatic residues. The Pab1 RRM2 domain interacts with eIF4G1 BOX3, the canonical interaction site, but also with BOX2, a conserved element of unknown function to date. The RNA1 region interacts with RNA through a new RNA interaction motif and with the Pub1 RRM3 domain. This later also interacts with eIF4G1 BOX1 modulating its intrinsic self-assembly properties. The description of the biomolecular interactions involving eIF4G1 to the residue detail increases our knowledge about biological processes involving this key translation initiation factor.

Quantitative prediction of ensemble dynamics, shapes and contact propensities of intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) are highly dynamic systems that play an important role in cell signaling processes and their misfunction often causes human disease. Proper understanding of IDP function not only requires the realistic characterization of their three-dimensional conformational ensembles at atomic-level resolution but also of the time scales of interconversion between their conformational substates. Large sets of experimental data are often used in combination with molecular modeling to restrain or bias models to improve agreement with experiment. It is shown here for the N-terminal transactivation domain of p53 (p53TAD) and Pup, which are two IDPs that fold upon binding to their targets, how the latest advancements in molecular dynamics (MD) simulations methodology produces native conformational ensembles by combining replica exchange with series of microsecond MD simulations. They closely reproduce experimental data at the global conformational ensemble level, in terms of the distribution properties of the radius of gyration tensor, and at the local level, in terms of NMR properties including 15N spin relaxation, without the need for reweighting. Further inspection revealed that 10-20% of the individual MD trajectories display the formation of secondary structures not observed in the experimental NMR data. The IDP ensembles were analyzed by graph theory to identify dominant inter-residue contact clusters and characteristic amino-acid contact propensities. These findings indicate that modern MD force fields with residue-specific backbone potentials can produce highly realistic IDP ensembles sampling a hierarchy of nano- and picosecond time scales providing new insights into their biological function.

Impacts of a Zwitterionic Peptide on its Fusion Protein

Therapeutic proteins frequently need to be modified with high-molecular-weight molecules to improve their pharmacokinetic properties. The genetic linkage of therapeutic proteins to a high-molecular-weight zwitterionic peptide, termed EKP, offers a promising approach. As with any protein modification, EKP could impact the structural behavior and receptor binding properties of the linked therapeutic protein, thereby altering its bioactivity. To evaluate the effects of EKP on therapeutic proteins, we study the receptor binding properties of high-molecular-weight EKP linked to the growth colony-stimulating factor (GCSF) using the genetically based yeast display platform. We find that yeast-displayed EKP-GCSF and GCSF exhibits similar binding to its receptor GCSF-R, suggesting that EKP does not hinder receptor binding. Furthermore, yeast-displayed EKP-GCSF demonstrates protection against thermal denaturation compared to GCSF. Similarly, to study the structural effects of EKP on GCSF, we employ in silico modeling using alphaFold2 in conjunction with molecular dynamics (MD) simulations. Likewise, in silico modeling reveals that EKP does not alter the structural behavior of GCSF. Finally, we demonstrate the functional benefits of EKP, by which the EKP-GCSF fusion protein produced in Escherichia coli exhibits improved pharmacokinetics and prolonged bioactivity in vivo.

PP2A is activated by cytochrome c upon formation of a diffuse encounter complex with SET/TAF-Iβ

Intrinsic protein flexibility is of overwhelming relevance for intermolecular recognition and adaptability of highly dynamic ensemble of complexes, and the phenomenon is essential for the understanding of numerous biological processes. These conformational ensembles-encounter complexes-lack a unique organization, which prevents the determination of well-defined high resolution structures. This is the case for complexes involving the oncoprotein SET/template-activating factor-Iβ (SET/TAF-Iβ), a histone chaperone whose functions and interactions are significantly affected by its intrinsic structural plasticity. Besides its role in chromatin remodeling, SET/TAF-Iβ is an inhibitor of protein phosphatase 2A (PP2A), which is a key phosphatase counteracting transcription and signaling events controlling the activity of DNA damage response (DDR) mediators. During DDR, SET/TAF-Iβ is sequestered by cytochrome c (Cc) upon migration of the hemeprotein from mitochondria to the cell nucleus. Here, we report that the nuclear SET/TAF-Iβ:Cc polyconformational ensemble is able to activate PP2A. In particular, the N-end folded, globular region of SET/TAF-Iβ (a.k.a. SET/TAF-Iβ ΔC)-which exhibits an unexpected, intrinsically highly dynamic behavior-is sufficient to be recognized by Cc in a diffuse encounter manner. Cc-mediated blocking of PP2A inhibition is deciphered using an integrated structural and computational approach, combining small-angle X-ray scattering, electron paramagnetic resonance, nuclear magnetic resonance, calorimetry and molecular dynamics simulations.

Insights into the Atomistic Mechanisms of Phosphorylation in Disrupting Liquid-Liquid Phase Separation and Aggregation of the FUS Low-Complexity Domain

Fused in sarcoma (FUS), a nuclear RNA binding protein, can not only undergo liquid-liquid phase separation (LLPS) to form dynamic biomolecular condensates but also aggregate into solid amyloid fibrils which are associated with the pathology of amyotrophic lateral sclerosis and frontotemporal lobar degeneration diseases. Phosphorylation in the FUS low-complexity domain (FUS-LC) inhibits FUS LLPS and aggregation. However, it remains largely elusive what are the underlying atomistic mechanisms of this inhibitory effect and whether phosphorylation can disrupt preformed FUS fibrils, reversing the FUS gel/solid phase toward the liquid phase. Herein, we systematically investigate the impacts of phosphorylation on the conformational ensemble of the FUS_37-97 monomer and dimer and the structure of the FUS_37-97 fibril by performing extensive all-atom molecular dynamics simulations. Our simulations reveal three key findings: (1) phosphorylation shifts the conformations of FUS_37-97 from the β-rich, fibril-competent state toward a helix-rich, fibril-incompetent state; (2) phosphorylation significantly weakens protein-protein interactions and enhances protein-water interactions, which disfavor FUS-LC LLPS as well as aggregation and facilitate the dissolution of the preformed FUS-LC fibril; and (3) the FUS_37-97 peptide displays a high β-strand probability in the region spanning residues 52-67, and phosphorylation at S54 and S61 residues located in this region is crucial for the disruption of LLPS and aggregation of FUS-LC. This study may pave the way for ameliorating phase-separation-related pathologies via site-specific phosphorylation.

Evaluation of implicit solvent models in molecular dynamics simulation of α-Synuclein

We report conventional and accelerated molecular dynamics simulations of α-Synuclein, designed to assess performance of using different starting conformation, solvation environment and force field combination. Backbone and sidechain chemical shifts, radius of gyration, presence of β-hairpin structures in KTK(E/Q)GV repeats and secondary structure percentages were used to evaluate how variations in forcefield, solvation model and simulation protocol provide results that correlate with experimental findings. We show that with suitable choice of forcefield and solvent, ff03ws and OBC implicit model, respectively, acceptable reproduction of experimental data on size and secondary structure is obtained by both conventional and accelerated MD. In contrast to the implicit solvent model, simulations in explicit TIP4P/2005 solvent do not properly represent size or secondary structure of α-Synuclein.Communicated by Ramaswamy H. Sarma.

Integrative ensemble modeling of proteins and their complexes with distance distribution restraints

Many proteins and protein complexes exhibit regions that are intrinsically disordered. Whereas an arsenal of techniques exists to characterize structured proteins or protein regions, characterization of the vast conformational space occupied by intrinsically disordered regions remains a challenging task due the ensemble-averaging nature of many techniques that provide mean value restraints. More representative information can be gained in the form of distribution restraints, such as EPR-derived distance distributions. Previously we developed the ensemble modeling tool MMM, where we partition the macromolecule into structured and unstructured domains and utilize an integrative structural approach with a focus on EPR-derived distance restraints. Here we present the successor program of MMM: MMMx. All the modeling functionality was ported to MMMx and is now accessed by a uniform script format, allowing to combine the different modules at will to modeling pipelines. During the conception of MMMx many of the tools were improved or updated. We discuss the general functionality of MMMx and its modules, and illustrate some of the modeling tools by application examples.

Modeling the Structure and Interactions of Intrinsically Disordered Peptides with Multiple Replica, Metadynamics-Based Sampling Methods and Force-Field Combinations

Intrinsically disordered proteins play a key role in many biological processes, including the formation of biomolecular condensates within cells. A detailed characterization of their configurational ensemble and structure-function paradigm is crucial for understanding their biological activity and for exploiting them as building blocks in material sciences. In this work, we incorporate bias-exchange metadynamics and parallel-tempering well-tempered metadynamics with CHARMM36m and CHARMM22* to explore the structural and thermodynamic characteristics of a short archetypal disordered sequence derived from a DEAD-box protein. The conformational landscapes emerging from our simulations are largely congruent across methods and force fields. Nevertheless, differences in fine details emerge from varying combinations of force-fields and sampling methods. For this protein, our analysis identifies features that help to explain the low propensity of this sequence to undergo self-association in vitro, which are common to all force-field/sampling method combinations. Overall, our work demonstrates the importance of using multiple force-field and sampling method combinations for accurate structural and thermodynamic information in the study of disordered proteins.

Intrinsically disordered proteins: Ensembles at the limits of Anfinsen's dogma

Intrinsically disordered proteins (IDPs) are proteins that lack rigid 3D structure. Hence, they are often misconceived to present a challenge to Anfinsen's dogma. However, IDPs exist as ensembles that sample a quasi-continuum of rapidly interconverting conformations and, as such, may represent proteins at the extreme limit of the Anfinsen postulate. IDPs play important biological roles and are key components of the cellular protein interaction network (PIN). Many IDPs can interconvert between disordered and ordered states as they bind to appropriate partners. Conformational dynamics of IDPs contribute to conformational noise in the cell. Thus, the dysregulation of IDPs contributes to increased noise and "promiscuous" interactions. This leads to PIN rewiring to output an appropriate response underscoring the critical role of IDPs in cellular decision making. Nonetheless, IDPs are not easily tractable experimentally. Furthermore, in the absence of a reference conformation, discerning the energy landscape representation of the weakly funneled IDPs in terms of reaction coordinates is challenging. To understand conformational dynamics in real time and decipher how IDPs recognize multiple binding partners with high specificity, several sophisticated knowledge-based and physics-based in silico sampling techniques have been developed. Here, using specific examples, we highlight recent advances in energy landscape visualization and molecular dynamics simulations to discern conformational dynamics and discuss how the conformational preferences of IDPs modulate their function, especially in phenotypic switching. Finally, we discuss recent progress in identifying small molecules targeting IDPs underscoring the potential therapeutic value of IDPs. Understanding structure and function of IDPs can not only provide new insight on cellular decision making but may also help to refine and extend Anfinsen's structure/function paradigm.

Molecular simulations of proteins: From simplified physical interactions to complex biological phenomena

Molecular dynamics simulation is the most popular computational technique for investigating the structural and dynamical behaviour of proteins, in search of the molecular basis of their function. Far from being a completely settled field of research, simulations are still evolving to best capture the essential features of the atomic interactions that govern a protein's inner motions. Modern force fields are becoming increasingly accurate in providing a physical description adequate to this purpose, and allow us to model complex biological systems under fairly realistic conditions. Furthermore, the use of accelerated sampling techniques is improving our access to the observation of progressively larger molecular structures, longer time scales, and more hidden functional events. In this review, the basic principles of molecular dynamics simulations and a number of key applications in the area of protein science are summarized, and some of the most important results are discussed. Examples include the study of the structure, dynamics and binding properties of 'difficult' targets, such as intrinsically disordered proteins and membrane receptors, and the investigation of challenging phenomena like hydration-driven processes and protein aggregation. The findings described provide an overall picture of the current state of this research field, and indicate new perspectives on the road ahead to the upcoming future of molecular simulations.

K-edge anomalous SAXS for protein solution structure modeling

K-edge anomalous SAXS intensity was measured from a small, dimeric, partly unstructured protein segment of myosin X by using cupric ions bound to its C-terminal polyhistidine tags. Energy-dependent anomalous SAXS can provide key location-specific information about metal-labeled protein structures in solution that cannot be obtained from routine SAXS analysis. However, anomalous SAXS is seldom used for protein research due to practical difficulties, such as a lack of generic multivalent metal-binding tags and the challenges of measuring weak anomalous signal at the metal absorption edge. This pilot feasibility study suggests that weak K-edge anomalous SAXS signal can be obtained from transition metals bound to terminally located histidine tags of small proteins. The measured anomalous signal can provide information about the distribution of all metal–protein distances in the complex. Such an anomalous SAXS signal can assist in the modeling and validation of structured or unstructured proteins in solution and may potentially become a new addition to the repertoire of techniques in integrative structural biology.

Single-molecule Detection of Ultrafast Biomolecular Dynamics with Nanophotonics

Single-molecule Förster resonance energy transfer (FRET) is a versatile technique for probing the structure and dynamics of biomolecules even in heterogeneous ensembles. However, because of the limited fluorescence brightness per molecule and the relatively long fluorescence lifetimes, probing ultrafast structural dynamics in the nanosecond time scale has thus far been very challenging. Here, we demonstrate that nanophotonic fluorescence enhancement in zero-mode waveguides enables measurements of previously inaccessible low-nanosecond dynamics by dramatically improving time resolution and reduces data acquisition times by more than an order of magnitude. As a prototypical example, we use this approach to probe the dynamics of a short intrinsically disordered peptide that were previously inaccessible with single-molecule FRET measurements. We show that we are now able to detect the low-nanosecond correlations in this peptide, and we obtain a detailed interpretation of the underlying distance distributions and dynamics in conjunction with all-atom molecular dynamics simulations, which agree remarkably well with the experiments. We expect this combined approach to be widely applicable to the investigation of very rapid biomolecular dynamics.

Visualization of intrinsically disordered proteins by high-speed atomic force microscopy

High-speed atomic force microscopy (HS-AFM) is a powerful tool established 13 years ago. This methodology can capture individual protein molecules carrying out functional activities under near-physiological conditions, without chemical labeling, at 2-3 nm lateral and ∼0.1 nm vertical spatial resolution, and at sub-100 ms temporal resolution. Although most biological HS-AFM studies thus far target structured proteins, HS-AFM is also ideally suited to study the dynamics of intrinsically disordered proteins. Here we review some of the dynamic structures and processes of intrinsically disordered proteins that have been unveiled by HS-AFM imaging.

Aggregation-Prone Structural Ensembles of Transthyretin Collected With Regression Analysis for NMR Chemical Shift

Monomer dissociation and subsequent misfolding of the transthyretin (TTR) is one of the most critical causative factors of TTR amyloidosis. TTR amyloidosis causes several human diseases, such as senile systemic amyloidosis and familial amyloid cardiomyopathy/polyneuropathy; therefore, it is important to understand the molecular details of the structural deformation and aggregation mechanisms of TTR. However, such molecular characteristics are still elusive because of the complicated structural heterogeneity of TTR and its highly sensitive nature to various environmental factors. Several nuclear magnetic resonance (NMR) spectroscopy and molecular dynamics (MD) studies of TTR variants have recently reported evidence of transient aggregation-prone structural states of TTR. According to these studies, the stability of the DAGH β-sheet, one of the two main β-sheets in TTR, is a crucial determinant of the TTR amyloidosis mechanism. In addition, its conformational perturbation and possible involvement of nearby structural motifs facilitates TTR aggregation. This study proposes aggregation-prone structural ensembles of TTR obtained by MD simulation with enhanced sampling and a multiple linear regression approach. This method provides plausible structural models that are composed of ensemble structures consistent with NMR chemical shift data. This study validated the ensemble models with experimental data obtained from circular dichroism (CD) spectroscopy and NMR order parameter analysis. In addition, our results suggest that the structural deformation of the DAGH β-sheet and the AB loop regions may correlate with the manifestation of the aggregation-prone conformational states of TTR. In summary, our method employing MD techniques to extend the structural ensembles from NMR experimental data analysis may provide new opportunities to investigate various transient yet important structural states of amyloidogenic proteins.

Accurate model of liquid-liquid phase behavior of intrinsically disordered proteins from optimization of single-chain properties

Many intrinsically disordered proteins (IDPs) may undergo liquid-liquid phase separation (LLPS) and participate in the formation of membraneless organelles in the cell, thereby contributing to the regulation and compartmentalization of intracellular biochemical reactions. The phase behavior of IDPs is sequence dependent, and its investigation through molecular simulations requires protein models that combine computational efficiency with an accurate description of intramolecular and intermolecular interactions. We developed a general coarse-grained model of IDPs, with residue-level detail, based on an extensive set of experimental data on single-chain properties. Ensemble-averaged experimental observables are predicted from molecular simulations, and a data-driven parameter-learning procedure is used to identify the residue-specific model parameters that minimize the discrepancy between predictions and experiments. The model accurately reproduces the experimentally observed conformational propensities of a set of IDPs. Through two-body as well as large-scale molecular simulations, we show that the optimization of the intramolecular interactions results in improved predictions of protein self-association and LLPS.

Accurate model of liquid-liquid phase behavior of intrinsically disordered proteins from optimization of single-chain properties

Many intrinsically disordered proteins (IDPs) may undergo liquid-liquid phase separation (LLPS) and participate in the formation of membraneless organelles in the cell, thereby contributing to the regulation and compartmentalization of intracellular biochemical reactions. The phase behavior of IDPs is sequence dependent, and its investigation through molecular simulations requires protein models that combine computational efficiency with an accurate description of intramolecular and intermolecular interactions. We developed a general coarse-grained model of IDPs, with residue-level detail, based on an extensive set of experimental data on single-chain properties. Ensemble-averaged experimental observables are predicted from molecular simulations, and a data-driven parameter-learning procedure is used to identify the residue-specific model parameters that minimize the discrepancy between predictions and experiments. The model accurately reproduces the experimentally observed conformational propensities of a set of IDPs. Through two-body as well as large-scale molecular simulations, we show that the optimization of the intramolecular interactions results in improved predictions of protein self-association and LLPS.

Membrane-bound KRAS approximates an entropic ensemble of configurations

KRAS4B is a membrane-anchored signaling protein and a primary target in cancer research. Predictions from molecular dynamics simulations that have previously shaped our mechanistic understanding of KRAS signaling disagree with recent experimental results from neutron reflectometry, NMR, and thermodynamic binding studies. To gain insight into these discrepancies, we compare this body of biophysical data to back-calculated experimental results from a series of molecular simulations that implement different subsets of molecular interactions. Our results show that KRAS4B approximates an entropic ensemble of configurations at model membranes containing 30% phosphatidylserine lipids, which is not significantly shaped by interactions between the globular G-domain of KRAS4B and the lipid membrane. These findings revise our understanding of KRAS signaling and promote a model in which the protein samples the accessible conformational space in a near-uniform manner while being available to bind to effector proteins.

pH-Dependent Conformations of an Antimicrobial Spider Venom Peptide, Cupiennin 1a, from Unbiased HREMD Simulations

Cupiennin 1a is an antimicrobial peptide found in the venom of the spider Cupiennius salei. A highly cationic peptide, its cell lysis activity has been found to vary between neutral and charged membranes. In this study, Hamiltonian replica-exchange molecular dynamics (HREMD) was used to determine the conformational ensemble of the peptide in both charged (pH 3) and neutral (pH 11) states. The obtained free energy landscapes demonstrated the conformational diversity of the neutral peptide. At high pH, the peptide was found to adopt helix-hinge-helix and disordered structures. At pH 3, the peptide is structured with a high propensity toward α-helices. The presence of these α-helices seems to assist the peptide in recognizing membrane surfaces. These results highlight the importance of the charged residues in the stabilization of the peptide structure and the subsequent effects of pH on the peptide's conformational diversity and membrane activity. These findings may provide insights into the antimicrobial activity of Cupiennin 1a and other amphipathic linear peptides toward different cell membranes.