Analytical Framework to Understand the Origins of Methyl Side-Chain Dynamics in Protein Assemblies

Side-chain motions play an important role in understanding protein structure, dynamics, protein-protein, and protein-ligand interactions. However, our understanding of protein side-chain dynamics is currently limited by the lack of analytical tools. Here, we present a novel analytical framework employing experimental nuclear magnetic resonance (NMR) relaxation measurements at atomic resolution combined with molecular dynamics (MD) simulation to characterize with a high level of detail the methyl side-chain dynamics in insoluble protein assemblies, using amyloid fibrils formed by the prion HET-s. We use MD simulation to interpret experimental results, where rotameric hops, including methyl group rotation and χ1/χ2 rotations, cannot be completely described with a single correlation time but rather sample a broad distribution of correlation times, resulting from continuously changing local structure in the fibril. Backbone motion similarly samples a broad range of correlation times, from ∼100 ps to μs, although resulting from mostly different dynamic processes; nonetheless, we find that the backbone is not fully decoupled from the side-chain motion, where changes in side-chain dynamics influence backbone motion and vice versa. While the complexity of side-chain motion in protein assemblies makes it very challenging to obtain perfect agreement between experiment and simulation, our analytical framework improves the interpretation of experimental dynamics measurements for complex protein assemblies.

Unraveling motion in proteins by combining NMR relaxometry and molecular dynamics simulations: A case study on ubiquitin

Nuclear magnetic resonance (NMR) relaxation experiments shine light onto the dynamics of molecular systems in the picosecond to millisecond timescales. As these methods cannot provide an atomically resolved view of the motion of atoms, functional groups, or domains giving rise to such signals, relaxation techniques have been combined with molecular dynamics (MD) simulations to obtain mechanistic descriptions and gain insights into the functional role of side chain or domain motion. In this work, we present a comparison of five computational methods that permit the joint analysis of MD simulations and NMR relaxation experiments. We discuss their relative strengths and areas of applicability and demonstrate how they may be utilized to interpret the dynamics in MD simulations with the small protein ubiquitin as a test system. We focus on the aliphatic side chains given the rigidity of the backbone of this protein. We find encouraging agreement between experiment, Markov state models built in the χ1/χ2 rotamer space of isoleucine residues, explicit rotamer jump models, and a decomposition of the motion using ROMANCE. These methods allow us to ascribe the dynamics to specific rotamer jumps. Simulations with eight different combinations of force field and water model highlight how the different metrics may be employed to pinpoint force field deficiencies. Furthermore, the presented comparison offers a perspective on the utility of NMR relaxation to serve as validation data for the prediction of kinetics by state-of-the-art biomolecular force fields.

Fitting Force Field Parameters to NMR Relaxation Data

We present an approach to optimize force field parameters using time-dependent data from NMR relaxation experiments. To do so, we scan parameters in the dihedral angle potential energy terms describing the rotation of the methyl groups in proteins and compare NMR relaxation rates calculated from molecular dynamics simulations with the modified force fields to deuterium relaxation measurements of T4 lysozyme. We find that a small modification of C^γ methyl groups improves the agreement with experiments both for the protein used to optimize the force field and when validating using simulations of CI2 and ubiquitin. We also show that these improvements enable a more effective a posteriori reweighting of the MD trajectories. The resulting force field thus enables more direct comparison between simulations and side-chain NMR relaxation data and makes it possible to construct ensembles that better represent the dynamics of proteins in solution.

Probing Methyl Group Dynamics in Proteins by NMR Cross-Correlated Dipolar Relaxation and Molecular Dynamics Simulations

Nuclear magnetic resonance (NMR) spin relaxation is the most informative approach to experimentally probe the internal dynamics of proteins on the picosecond to nanosecond time scale. At the same time, molecular dynamics (MD) simulations of biological macromolecules are steadily improving through better physical models, enhanced sampling methods, and increased computational power, and they provide exquisite information about flexibility and its role in protein stability and molecular interactions. Many examples have shown that MD is now adept in probing protein backbone motion, but improvements are still required toward a quantitative description of the dynamics of side chains, for example, probed by the dynamics of methyl groups. Thus far, the comparison of computation with experiment for side chain dynamics has primarily focused on the relaxation of ¹³C and ²H nuclei induced by autocorrelated variation of spin interactions. However, the cross-correlation of ¹³C-¹H dipolar interactions in methyl groups offers an attractive alternative. Here, we establish a computational framework to extract cross-correlation relaxation parameters of methyl groups in proteins from all-atom MD simulations. To demonstrate the utility of the approach, cross-correlation relaxation rates of ubiquitin are computed from MD simulations performed with the AMBER99SB*-ILDN and CHARMM36 force fields. Simulation results were found to agree well with those obtained by experiment. Moreover, the data obtained with the two force fields are highly consistent.

How does it really move? Recent progress in the investigation of protein nanosecond dynamics by NMR and simulation

Nuclear magnetic resonance (NMR) spin relaxation experiments currently probe molecular motions on timescales from picoseconds to nanoseconds. The detailed interpretation of these motions in atomic detail benefits from complementarity with the results from molecular dynamics (MD) simulations. In this mini-review, we describe the recent developments in experimental techniques to study the backbone dynamics from ¹⁵N relaxation and side-chain dynamics from ¹³C relaxation, discuss the different analysis approaches from model-free to dynamics detectors, and highlight the many ways that NMR relaxation experiments and MD simulations can be used together to improve the interpretation and gain insights into protein dynamics.

Effect of the R126C mutation on the structure and function of the glucose transporter GLUT1: A molecular dynamics simulation study

Glucose transporter 1 (GLUT1) is responsible for basal glucose uptake and is expressed in most tissues under normal conditions. GLUT1 mutations can cause early-onset absence epilepsy and myoclonus dystonia syndrome (MDS), with MDS potentially lethal. In this study, the effect of the R126C mutation, which is associated with MDS, on structural stability and substrate transport of GLUT1 was investigated. Various bioinformatics tools were used to predict the stability of GLUT1, revealing that the R126C mutation reduces the structural stability of GLUT1. Molecular dynamics (MD) simulations were used to further characterize the effect of the R126C mutation on GLUT1 structural stability. Based on the MD simulations, specific conformational changes and dominant motions of the GLUT1 mutant were characterized by Principal component analysis (PCA). The mutation disrupts hydrogen bonds between substrate-binding residues and glucose, thus likely reducing substrate affinity. The R126C mutation reduces the conformational stability of the protein, and fewer intramolecular hydrogen bonds were present in the mutated GLUT1 when compared with that of wild-type GLUT1. The mutation increased the free energy of glucose transport through GLUT1 significantly, especially at the mutation site, indicating that passage of glucose through the channel is hindered, and this mutant may even release cytoplasmic glucose. This study provides a detailed atomic-level explanation for the reduced structural stability and substrate transport capacity of a GLUT1 mutant. The results aid our understanding of the structure of GLUT1 and provide a framework for developing drugs to treat GLUT1-related diseases, such as MDS.

Advances in the exact nuclear Overhauser effect 2018-2022

The introduction of the exact nuclear Overhauser enhancement (eNOE) methodology to solution-state nuclear magnetic resonance (NMR) spectroscopy results in tighter distance restraints from NOEs than in convention analysis. These improved restraints allow for higher resolution in structure calculation and even the disentanglement of different conformations of macromolecules. While initial work primarily focused on technical development of the eNOE, structural studies aimed at the elucidation of spatial sampling in proteins and nucleic acids were published in parallel prior to 2018. The period of 2018-2022 saw a continued series of technical innovation, but also major applications addressing biological questions. Here, we review both aspects, covering topics from the implementation of non-uniform sampling of NOESY buildups, novel pulse sequences, adaption of the eNOE to solid-state NMR, advances in eNOE data analysis, and innovations in structural ensemble calculation, to applications to protein, RNA, and DNA structure elucidation.

Energy landscape reshaped by strain-specific mutations underlies epistasis in NS1 evolution of influenza A virus

Elucidating how individual mutations affect the protein energy landscape is crucial for understanding how proteins evolve. However, predicting mutational effects remains challenging because of epistasis—the nonadditive interactions between mutations. Here, we investigate the biophysical mechanism of strain-specific epistasis in the nonstructural protein 1 (NS1) of influenza A viruses (IAVs). We integrate structural, kinetic, thermodynamic, and conformational dynamics analyses of four NS1s of influenza strains that emerged between 1918 and 2004. Although functionally near-neutral, strain-specific NS1 mutations exhibit long-range epistatic interactions with residues at the p85β-binding interface. We reveal that strain-specific mutations reshaped the NS1 energy landscape during evolution. Using NMR spin dynamics, we find that the strain-specific mutations altered the conformational dynamics of the hidden network of tightly packed residues, underlying the evolution of long-range epistasis. This work shows how near-neutral mutations silently alter the biophysical energy landscapes, resulting in diverse background effects during molecular evolution.

Influenza A virus (IAV) nonstructural protein 1 (NS1) is a multifunctional virulence factor that interacts with several host factors such as phosphatidylinositol-3-kinase (PI3K). NS1 binds specifically to the p85β regulatory subunit of PI3K and subsequently activates PI3K signaling. Here, Kim et al. show that functionally near-neutral, strain-specific NS1 mutations lead to variations in binding kinetics to p85β exhibit long-range epistatic interactions. Applying NMR they provide evidence that the structural dynamics of the NS1 hydrophobic core have evolved over time and contributed to epistasis.

Rebuilding the lid region from conformational and dynamic features to engineering applications of lipase in foods: Current status and future prospects

The applications of lipases in esterification, amidation, and transesterification have broadened their potential in the production of fine compounds with high cumulative values. Mostly, the catalytic triad of lipases is covered by either one or two mobile peptides called the "lid" that control the substrate channel to the catalytic center. The lid holds unique conformational allostery via interfacial activation to regulate the dynamics and catalytic functions of lipases, thereby highlighting its importance in redesigning these enzymes for industrial applications. The structural characteristic of lipase, the dynamics of lids, and the roles of lid in lipase catalysis were summarized, providing opportunities for rebuilding lid region by biotechniques (e.g., metagenomic technology and protein engineering) and enzyme immobilization. The review focused on the advantages and disadvantages of strategies rebuilding the lid region. The main shortcomings of biotechnologies on lid rebuilding were discussed such as negative effects on lipase (e.g., a decrease of activity). Additionally, the main shortcomings (e.g., enzyme desorption at high temperatre) in immobilization on hydrophobic supports via interfacial action were presented. Solutions to the mentioned problems were proposed by combinations of computational design with biotechnologies, and improvements of lipase immobilization (e.g., immobilization protocols and support design). Finally, the review provides future perspectives about designing hyperfunctional lipases as biocatalysts in the food industry based on lid conformation and dynamics.

Development and Validation of Fluorinated, Aromatic Amino Acid Parameters for Use with the AMBER ff15ipq Protein Force Field

We developed force field parameters for fluorinated, aromatic amino acids enabling molecular dynamics (MD) simulations of fluorinated proteins. These parameters are tailored to the AMBER ff15ipq protein force field and enable the modeling of 4, 5, 6, and 7F-tryptophan, 3F- and 3,5F-tyrosine, and 4F- or 4-CF3-phenylalanine. The parameters include 181 unique atomic charges derived using the implicitly polarized charge (IPolQ) scheme in the presence of SPC/Eb explicit water molecules and 9 unique bond, angle, or torsion terms. Our simulations of benchmark peptides and proteins maintain expected conformational propensities on the μs time scale. In addition, we have developed an open-source Python program to calculate fluorine relaxation rates from MD simulations. The extracted relaxation rates from protein simulations are in good agreement with experimental values determined by 19F NMR. Collectively, our results illustrate the power and robustness of the IPolQ lineage of force fields for modeling the structure and dynamics of fluorine-containing proteins at the atomic level.

Double Mutant of Chymotrypsin Inhibitor 2 Stabilized through Increased Conformational Entropy

The conformational heterogeneity of a folded protein can affect not only its function but also stability and folding. We recently discovered and characterized a stabilized double mutant (L49I/I57V) of the protein CI2 and showed that state-of-the-art prediction methods could not predict the increased stability relative to the wild-type protein. Here, we have examined whether changed native-state dynamics, and resulting entropy changes, can explain the stability changes in the double mutant protein, as well as the two single mutant forms. We have combined NMR relaxation measurements of the ps-ns dynamics of amide groups in the backbone and the methyl groups in the side chains with molecular dynamics simulations to quantify the native-state dynamics. The NMR experiments reveal that the mutations have different effects on the conformational flexibility of CI2: a reduction in conformational dynamics (and entropy estimated from this) of the native state of the L49I variant correlates with its decreased stability, while increased dynamics of the I57V and L49I/I57V variants correlates with their increased stability. These findings suggest that explicitly accounting for changes in native-state entropy might be needed to improve the predictions of the effect of mutations on protein stability.

How Much Entropy Is Contained in NMR Relaxation Parameters?

Solution-state NMR relaxation experiments are the cornerstone to study internal protein dynamics at an atomic resolution on time scales that are faster than the overall rotational tumbling time τ_R. Since the motions described by NMR relaxation parameters are connected to thermodynamic quantities like conformational entropies, the question arises how much of the total entropy is contained within this tumbling time. Using all-atom molecular dynamics simulations of the T4 lysozyme, we found that entropy buildup is rather fast for the backbone, such that the majority of the entropy is indeed contained in the short-time dynamics. In contrast, the contribution of the slow dynamics of side chains on time scales beyond τ_R on the side-chain conformational entropy is significant and should be taken into account for the extraction of accurate thermodynamic properties.

Model-Free or Not?

Relaxation in nuclear magnetic resonance is a powerful method for obtaining spatially resolved, timescale-specific dynamics information about molecular systems. However, dynamics in biomolecular systems are generally too complex to be fully characterized based on NMR data alone. This is a familiar problem, addressed by the Lipari-Szabo model-free analysis, a method that captures the full information content of NMR relaxation data in case all internal motion of a molecule in solution is sufficiently fast. We investigate model-free analysis, as well as several other approaches, and find that model-free, spectral density mapping, LeMaster's approach, and our detector analysis form a class of analysis methods, for which behavior of the fitted parameters has a well-defined relationship to the distribution of correlation times of motion, independent of the specific form of that distribution. In a sense, they are all "model-free." Of these methods, only detectors are generally applicable to solid-state NMR relaxation data. We further discuss how detectors may be used for comparison of experimental data to data extracted from molecular dynamics simulation, and how simulation may be used to extract details of the dynamics that are not accessible via NMR, where detector analysis can be used to connect those details to experiments. We expect that combined methodology can eventually provide enough insight into complex dynamics to provide highly accurate models of motion, thus lending deeper insight into the nature of biomolecular dynamics.

Observation of Sub-Microsecond Protein Methyl-Side Chain Dynamics by Nanoparticle-Assisted NMR Spin Relaxation

Amino-acid side-chain properties in proteins are key determinants of protein function. NMR spin relaxation of side chains is an important source of information about local protein dynamics and flexibility. However, traditional solution NMR relaxation methods are most sensitive to sub-nanosecond dynamics lacking information on slower ns-μs time-scale motions. Nanoparticle-assisted NMR spin relaxation (NASR) of methyl-side chains is introduced here as a window into these ns-μs dynamics. NASR utilizes the transient and nonspecific interactions between folded proteins and slowly tumbling spherical nanoparticles (NPs), whereby the increase of the relaxation rates reflects motions on time scales from ps all the way to the overall tumbling correlation time of the NPs ranging from hundreds of ns to μs. The observed motional amplitude of each methyl group can then be expressed by a model-free NASR S² order parameter. The method is demonstrated for ²H-relaxation of CH₂D methyl moieties and cross-correlated relaxation of CH₃ groups for proteins Im7 and ubiquitin in the presence of anionic silica-nanoparticles. Both types of relaxation experiments, dominated by either quadrupolar or dipolar interactions, yield highly consistent results. Im7 shows additional dynamics on the intermediate time scales taking place in a functionally important loop, whereas ubiquitin visits the majority of its conformational substates on the sub-ns time scale. These experimental observations are in good agreement with 4-10 μs all-atom molecular dynamics trajectories. NASR probes side-chain dynamics on a much wider range of motional time scales than previously possible, thereby providing new insights into the interplay between protein structure, dynamics, and molecular interactions that govern protein function.

Low rotational barriers for the most dynamically active methyl groups in the proposed antiviral drugs for treatment of SARS-CoV-2, apilimod and tetrandrine

A recent screening study highlighted a molecular compound, apilimod, for its efficacy against the SARS-CoV-2 virus, while another compound, tetrandrine, demonstrated a remarkable synergy with the benchmark antiviral drug, remdesivir. Here, we find that because of significantly reduced potential energy barriers, which also give rise to pronounced quantum effects, the rotational dynamics of the most dynamically active methyl groups in apilimod and tetrandrine are much faster than those in remdesivir. Because dynamics of methyl groups are essential for biochemical activity, screening studies based on the computed potential energy profiles may help identify promising candidates within a given class of drugs.

Fitting Side-Chain NMR Relaxation Data Using Molecular Simulations

Proteins display a wealth of dynamical motions that can be probed using both experiments and simulations. We present an approach to integrate side-chain NMR relaxation measurements with molecular dynamics simulations to study the structure and dynamics of these motions. The approach, which we term ABSURDer (average block selection using relaxation data with entropy restraints), can be used to find a set of trajectories that are in agreement with relaxation measurements. We apply the method to deuterium relaxation measurements in T4 lysozyme and show how it can be used to integrate the accuracy of the NMR measurements with the molecular models of protein dynamics afforded by the simulations. We show how fitting of dynamic quantities leads to improved agreement with static properties and highlight areas needed for further improvements of the approach.

Methodological advancements for characterising protein side chains by NMR spectroscopy

The surface of proteins is covered by side chains of polar amino acids that are imperative for modulating protein functionality through the formation of noncovalent intermolecular interactions. However, despite their tremendous importance, the unique structures of protein side chains require tailored approaches for investigation by nuclear magnetic resonance spectroscopy and so have traditionally been understudied compared with the protein backbone. Here, we review substantial recent methodological advancements within nuclear magnetic resonance spectroscopy to address this issue. Specifically, we consider advancements that provide new insight into methyl-bearing side chains, show the potential of using non-natural amino acids and reveal the actions of charged side chains. Combined, the new methods promise unprecedented characterisations of side chains that will further elucidate protein function.

The Picornavirus Precursor 3CD Has Different Conformational Dynamics Compared to 3Cpro and 3Dpol in Functionally Relevant Regions

Viruses have evolved numerous strategies to maximize the use of their limited genetic material, including proteolytic cleavage of polyproteins to yield products with different functions. The poliovirus polyprotein 3CD is involved in important protein-protein, protein-RNA and protein-lipid interactions in viral replication and infection. It is a precursor to the 3C protease and 3D RNA-dependent RNA polymerase, but has different protease specificity, is not an active polymerase, and participates in other interactions differently than its processed products. These functional differences are poorly explained by the known X-ray crystal structures. It has been proposed that functional differences might be due to differences in conformational dynamics between 3C, 3D and 3CD. To address this possibility, we conducted nuclear magnetic resonance spectroscopy experiments, including multiple quantum relaxation dispersion, chemical exchange saturation transfer and methyl spin-spin relaxation, to probe conformational dynamics across multiple timescales. Indeed, these studies identified differences in conformational dynamics in functionally important regions, including enzyme active sites, and RNA and lipid binding sites. Expansion of the conformational ensemble available to 3CD may allow it to perform additional functions not observed in 3C and 3D alone despite having nearly identical lowest-energy structures.

Hydration-Induced Disorder Lowers the Energy Barriers for Methyl Rotation in Drug Molecules

The thermally activated dynamics of methyl groups are important for biochemical activity as they allow for a more efficient sampling of the energy landscape. Here, we compare methyl rotations in the dry and variously hydrated states of three primary drugs under consideration to treat the recent coronavirus disease (COVID-19), namely, hydroxychloroquine and its sulfate, dexamethasone and its sodium diphosphate, and remdesivir. We find that the main driving force behind the considerable reduction in the activation energy for methyl rotations in the hydrated state is the hydration-induced disorder in the methyl group local environments. Furthermore, the activation energy for methyl rotations in the hydration-induced disordered state is much lower than that in an isolated drug molecule, indicating that neither isolated molecules nor periodic crystalline structures can be used to analyze the potential landscape governing the side group dynamics in drug molecules. Instead, only the explicitly considered disordered structures can provide insight.

Sensitive and simplified: a combinatorial acquisition of five distinct 2D constant-time 13C-1H NMR protein correlation spectra

A procedure is presented for the substantial simplification of 2D constant-time ¹³C-¹H heteronuclear single-quantum correlation (HSQC) spectra of ¹³C-enriched proteins. In this approach, a single pulse sequence simultaneously records eight sub-spectra wherein the phases of the NMR signals depend on spin topology. Signals from different chemical groups are then stratified into different sub-spectra through linear combination based on Hadamard encoding of ¹³CH_n multiplicity (n = 1, 2, and 3) and the chemical nature of neighboring ¹³C nuclei (aliphatic, carbonyl/carboxyl, aromatic). This results in five sets of 2D NMR spectra containing mutually exclusive signals from: (i) ¹³C^β-¹H^β correlations of asparagine and aspartic acid, ¹³C^γ-¹H^γ correlations of glutamine and glutamic acid, and ¹³C^α-¹H^α correlations of glycine, (ii) ¹³C^α-¹H^α correlations of all residues but glycine, and (iii) ¹³C^β-¹H^β correlations of phenylalanine, tyrosine, histidine, and tryptophan, and the remaining (iv) aliphatic ¹³CH₂ and (v) aliphatic ¹³CH/¹³CH₃ resonances. As HSQC is a common element of many NMR experiments, the spectral simplification proposed in this article can be straightforwardly implemented in experiments for resonance assignment and structure determination and should be of widespread utility.

Protein Motional Details Revealed by Complementary Structural Biology Techniques

Proteins depend on defined molecular plasticity for their functionality. How to comprehensively capture dynamics correctly is of ubiquitous biological importance. Approaches commonly used to probe protein dynamics include model-free elucidation of site-specific motion by NMR relaxation, molecular dynamics (MD)-based approaches, and capturing the substates within a dynamic ensemble by recent eNOE-based multiple-structure approaches. Even though MD is sometimes combined with ensemble-averaged NMR restraints, these approaches have largely been developed and used individually. Owing to the different underlying concepts and practical requirements, it has remained unclear how they compare, and how they cross-validate and complement each other. Here, we extract and compare the differential information contents of MD simulations, NMR relaxation measurements, and eNOE-based multi-state structures for the SH3 domain of chicken α-spectrin. The data show that a validated, consistent, and detailed picture is feasible both for timescales and actual conformational states sampled in the dynamic ensemble. This includes the biologically important side-chain plasticity, for which experimentally cross-validated assessment is a significant challenge.

13C NMR Relaxation Analysis of Protein GB3 for the Assessment of Side Chain Dynamics Predictions by Current AMBER and CHARMM Force Fields

Molecular simulations with seven current AMBER- and CHARMM-based force fields yield markedly differing internal bond vector autocorrelation function predictions for many of the 223 methine and methylene H-C bonds of the 56-residue protein GB3. To enable quantification of accuracy, ¹³C R₁, R₂, and heteronuclear NOE relaxation rates have been determined for the methine and stereochemically assigned methylene C^α and C^β positions. With only three experimental relaxation values for each bond vector, central to this analysis is the accuracy with which MD-derived autocorrelation curves can be represented by a 3-parameter equation which, in turn, maps onto the NMR relaxation values. In contrast to the more widely used extended Lipari-Szabo order parameter representation, 95% of these MD-derived internal autocorrelation curves for GB3 can be fitted to within 1.0% rmsd over the time frame from 30 ps to 4 ns by a biexponential Larmor frequency-selective representation (LF-S²). Applying the LF-S² representation to the experimental relaxation rates and uncertainties serves to determine the boundary range for the autocorrelation function of each bond vector consistent with the experimental data. Not surprisingly, all seven force fields predict the autocorrelation functions for the more motionally restricted ¹H^α-¹³C^α and ¹H^β-¹³C^β bond vectors with reasonable accuracy. However, for the ¹H^β-¹³C^β bond vectors exhibiting aggregate order parameter S² values less than 0.85, only 1% of the MD-derived predictions lie with 1 σ of the experimentally determined autocorrelation functions and only 7% within 2 σ. On the other hand, substantial residue type-specific improvements in predictive performance were observed among the recent AMBER force fields. This analysis indicates considerable potential for the use of ¹³C relaxation measurements in guiding the optimization of the side chain dynamics characteristics of protein molecular simulations.

Nucleotide Binding and Active Site Gate Dynamics for the Hsp90 Chaperone ATPase Domain from Benchtop and High Field 19F NMR Spectroscopy

Protein turnover in cells is regulated by the ATP dependent activity of the Hsp90 chaperone. In concert with accessory proteins, ATP hydrolysis drives the obligate Hsp90 dimer through a cycle between open and closed states that is critical for assisting the folding and stability of hundreds of proteins. Cycling is initiated by ATP binding to the ATPase domain, with the chaperone and the active site gates in the dimer in open states. The chaperone then adopts a short-lived, ATP bound closed state with a closed active site gate. The structural and dynamic changes induced in the ATPase domain and active site gate upon nucleotide binding, and their impact on dimer closing are not well understood. We site-specifically ¹⁹F-labeled the ATPase domain at the active site gate to enable benchtop and high field ¹⁹F NMR spectroscopic studies. Combined with MD simulations, this allowed accurate characterization of pico- to nanosecond time scale motions of the active site gate, as well as slower micro- to millisecond time scale processes resulting from nucleotide binding. ATP binding induces increased flexibility at one of the hinges of the active site gate, a necessary prelude to release of the second hinge and eventual gate closure in the intact chaperone.

How do mutations affect the structural characteristics and substrate binding of CYP21A2? An investigation by molecular dynamics simulations

CYP21A2 mutations affect the activity of the protein leading to CAH disease.

Localized and Collective Motions in HET-s(218-289) Fibrils from Combined NMR Relaxation and MD Simulation

Nuclear magnetic resonance (NMR) relaxation data and molecular dynamics (MD) simulations are combined to characterize the dynamics of the fungal prion HET-s(218-289) in its amyloid form. NMR data is analyzed with the dynamics detector method, which yields timescale-specific information. An analogous analysis is performed on MD trajectories. Because specific MD predictions can be verified as agreeing with the NMR data, MD was used for further interpretation of NMR results: for the different timescales, cross-correlation coefficients were derived to quantify the correlation of the motion between different residues. Short timescales are the result of very local motions, while longer timescales are found for longer-range correlated motion. Similar trends on ns- and μs-timescales suggest that μs motion in fibrils is the result of motion correlated over many fibril layers.

Side-Chain Dynamics of the Trifluoroacetone Cysteine Derivative Characterized by 19F NMR Relaxation and Molecular Dynamics Simulations

¹⁹F NMR spectroscopy is a powerful tool for the study of the structures, dynamics, and interactions of proteins bearing cysteine residues chemically modified with a trifluoroacetone group (CYF residue). ¹⁹F NMR relaxation rates for the fluoromethyl group of CYF residues are sensitive to overall rotational tumbling of proteins, fast rotation about the CF₃ methyl axis, and the internal motion of the CYF side-chain. To develop a quantitative understanding of these various motional contributions, we used the model-free approach to extend expressions for ¹⁹F- T₂ NMR relaxation to include side-chain motions for the CYF residue. We complemented the NMR studies with atomic views of methyl rotation and side-chain motions using molecular dynamics simulations. This combined methodology allows for quantitative separation of the contributions of fast pico- to nanosecond dynamics from micro- to millisecond exchange processes to the ¹⁹F line width and highlights the utility of the CYF residue as a sensitive reporter of side-chain environment and dynamics in proteins.