Evaluation of backbone proton positions and dynamics in a small protein by liquid crystal NMR spectroscopy

Quantification of CH and NH/π-Stacking Interactions in Cells Using Nuclear Magnetic Resonance Spectroscopy

π-Stacking, a type of noncovalent interactions involving aromatic residues, plays an important role in protein folding and function. In this work, an attempt has been made to measure CH/π and NH/π stacking interactions in a protein in Escherichia coli cells using a combined double-mutant cycle and nuclear magnetic resonance spectroscopy method. The results show that the CH/π and NH/π stacking interactions are generally weaker in cells than those in the buffer. The transient intermolecular noncovalent interactions between the protein and the complex cellular environment may compete with and thus weaken the stacking interactions in the protein. The weakening of stacking interactions can enhance the local conformational opening of proteins in E. coli cells. This is evident from the faster rates of amide hydrogen/deuterium exchange observed in cells than in the buffer, for residues that undergo local conformational opening. This study highlights the influence of the cellular environment on π-stacking and the conformational dynamics of proteins.

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

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

Kinetic Resolution of the Atomic 3D Structures Formed by Ground and Excited Conformational States in an RNA Dynamic Ensemble

Knowing the 3D structures formed by the various conformations populating the RNA free-energy landscape, their relative abundance, and kinetic interconversion rates is required to obtain a quantitative and predictive understanding of how RNAs fold and function at the atomic level. While methods integrating ensemble-averaged experimental data with computational modeling are helping define the most abundant conformations in RNA ensembles, elucidating their kinetic rates of interconversion and determining the 3D structures of sparsely populated short-lived RNA excited conformational states (ESs) remains challenging. Here, we developed an approach integrating Rosetta-FARFAR RNA structure prediction with NMR residual dipolar couplings and relaxation dispersion that simultaneously determines the 3D structures formed by the ground-state (GS) and ES subensembles, their relative abundance, and kinetic rates of interconversion. The approach is demonstrated on HIV-1 TAR, whose six-nucleotide apical loop was previously shown to form a sparsely populated (∼13%) short-lived (lifetime ∼ 45 μs) ES. In the GS, the apical loop forms a broad distribution of open conformations interconverting on the pico-to-nanosecond time scale. Most residues are unpaired and preorganized to bind the Tat-superelongation protein complex. The apical loop zips up in the ES, forming a narrow distribution of closed conformations, which sequester critical residues required for protein recognition. Our work introduces an approach for determining the 3D ensemble models formed by sparsely populated RNA conformational states, provides a rare atomic view of an RNA ES, and kinetically resolves the atomic 3D structures of RNA conformational substates, interchanging on time scales spanning 6 orders of magnitude, from picoseconds to microseconds.

In silico prediction of protein binding affinities onto core-shell PEGylated noble metal nanoparticles for rational design of drug nanocarriers

Polymer-coated nanoparticles (NP) are commonly used as drug carriers or theranostic agents. Their uptake rates are modulated by the interactions with essential serum proteins such as transferrin and albumin. Understanding the control parameters of these interactions is crucial for improving the efficiency of these nanoscale devices. In this work, we perform a multiscale computational study of protein adsorption onto polyethylene glycol (PEG) coated gold and silver NPs, producing protein-NP adsorption rankings as a function of PEG grafting density, which are validated against previously reported experimental protein-NP binding constants. Furthermore, the applied nano-docking method provides information on the preferred orientation of proteins immobilised on the surface of NPs. We propose a method of construction of model core-shell NPs in silico. The presented protocol can provide molecular level insights for the experimental development of biosensors, nanocarriers, or other nanoplatforms where information on the preferred orientation of protein at the bio-nano interface is crucial, and enables fast in silico prescreening of assays of various nanocarriers, i.e., combinations of proteins, NPs, and coatings.

Intracellular environment can change protein conformational dynamics in cells through weak interactions

Conformational dynamics is important for protein functions, many of which are performed in cells. How the intracellular environment may affect protein conformational dynamics is largely unknown. Here, loop conformational dynamics is studied for a model protein in Escherichia coli cells by using nuclear magnetic resonance (NMR) spectroscopy. The weak interactions between the protein and surrounding macromolecules in cells hinder the protein rotational diffusion, which extends the dynamic detection timescale up to microseconds by the NMR spin relaxation method. The loop picosecond to microsecond dynamics is confirmed by nanoparticle-assisted spin relaxation and residual dipolar coupling methods. The loop interactions with the intracellular environment are perturbed through point mutation of the loop sequence. For the sequence of the protein that interacts stronger with surrounding macromolecules, the loop becomes more rigid in cells. In contrast, the mutational effect on the loop dynamics in vitro is small. This study provides direct evidence that the intracellular environment can modify protein loop conformational dynamics through weak interactions.

Toward a general neural network force field for protein simulations: Refining the intramolecular interaction in protein

Molecular dynamics (MD) is an extremely powerful, highly effective, and widely used approach to understanding the nature of chemical processes in atomic details for proteins. The accuracy of results from MD simulations is highly dependent on force fields. Currently, molecular mechanical (MM) force fields are mainly utilized in MD simulations because of their low computational cost. Quantum mechanical (QM) calculation has high accuracy, but it is exceedingly time consuming for protein simulations. Machine learning (ML) provides the capability for generating accurate potential at the QM level without increasing much computational effort for specific systems that can be studied at the QM level. However, the construction of general machine learned force fields, needed for broad applications and large and complex systems, is still challenging. Here, general and transferable neural network (NN) force fields based on CHARMM force fields, named CHARMM-NN, are constructed for proteins by training NN models on 27 fragments partitioned from the residue-based systematic molecular fragmentation (rSMF) method. The NN for each fragment is based on atom types and uses new input features that are similar to MM inputs, including bonds, angles, dihedrals, and non-bonded terms, which enhance the compatibility of CHARMM-NN to MM MD and enable the implementation of CHARMM-NN force fields in different MD programs. While the main part of the energy of the protein is based on rSMF and NN, the nonbonded interactions between the fragments and with water are taken from the CHARMM force field through mechanical embedding. The validations of the method for dipeptides on geometric data, relative potential energies, and structural reorganization energies demonstrate that the CHARMM-NN local minima on the potential energy surface are very accurate approximations to QM, showing the success of CHARMM-NN for bonded interactions. However, the MD simulations on peptides and proteins indicate that more accurate methods to represent protein-water interactions in fragments and non-bonded interactions between fragments should be considered in the future improvement of CHARMM-NN, which can increase the accuracy of approximation beyond the current mechanical embedding QM/MM level.

Synergism between x-ray crystallography and NMR residual dipolar couplings in characterizing protein dynamics

The important role of structural dynamics in protein function is widely recognized. Thermal or B-factors and their anisotropy, seen in x-ray analysis of protein structures, report on the presence of atomic coordinate heterogeneity that can be attributed to motion. However, their quantitative evaluation in terms of protein dynamics by x-ray ensemble refinement remains challenging. NMR spectroscopy provides quantitative information on the amplitudes and time scales of motional processes. Unfortunately, with a few exceptions, the NMR data do not provide direct insights into the atomic details of dynamic trajectories. Residual dipolar couplings, measured by solution NMR, are very precise parameters reporting on the time-averaged bond-vector orientations and may offer the opportunity to derive correctly weighted dynamic ensembles of structures for cases where multiple high-resolution x-ray structures are available. Applications to the SARS-CoV-2 main protease, Mpro, and ubiquitin highlight this complementarity of NMR and crystallography for quantitative assessment of internal motions.

Validation of X-ray Crystal Structure Ensemble Representations of SARS-CoV-2 Main Protease by Solution NMR Residual Dipolar Couplings

Considerable debate has focused on whether sampling of molecular dynamics trajectories restrained by crystallographic data can be used to develop realistic ensemble models for proteins in their natural, solution state. For the SARS-CoV-2 main protease, Mpro, we evaluated agreement between solution residual dipolar couplings (RDCs) and various recently reported multi-conformer and dynamic-ensemble crystallographic models. Although Phenix-derived ensemble models showed only small improvements in crystallographic Rfree, substantially improved RDC agreement over fits to a conventionally refined 1.2-Å X-ray structure was observed, in particular for residues with above average disorder in the ensemble. For a set of six lower resolution (1.55-2.19 Å) Mpro X-ray ensembles, obtained at temperatures ranging from 100 to 310 K, no significant improvement over conventional two-conformer representations was found. At the residue level, large differences in motions were observed among these ensembles, suggesting high uncertainties in the X-ray derived dynamics. Indeed, combining the six ensembles from the temperature series with the two 1.2-Å X-ray ensembles into a single 381-member "super ensemble" averaged these uncertainties and substantially improved agreement with RDCs. However, all ensembles showed excursions that were too large for the most dynamic fraction of residues. Our results suggest that further improvements to X-ray ensemble refinement are feasible, and that RDCs provide a sensitive benchmark in such endeavors. Remarkably, a weighted ensemble of 350 PDB Mpro X-ray structures provided slightly better cross-validated agreement with RDCs than any individual ensemble refinement, implying that differences in lattice confinement also limit the fit of RDCs to X-ray coordinates.

Surface Accessibility of an Intrinsically Disordered Protein Probed by 2D Time-Resolved Laser-Assisted NMR Spectroscopy

Probing the protein surface accessibility of different residues is a powerful way of characterizing the overall conformation of intrinsically disordered proteins (IDPs). We present a two-dimensional (2D) time-resolved photo-CIDNP (TR-CIDNP) experiment suitable for IDP analysis. Pulse stretching of high-power laser pulses, band-selective decoupling of ¹³C^α, and simultaneous application of radiofrequency and laser pulses were implemented to quantitatively analyze the IDP surface at ultrahigh resolution. Comparative analysis with other methods that measure protein surface accessibility validated the newly developed method and emphasized the importance of dye charge in photo-CIDNP. Using the neutral riboflavin dye, surface accessibilities were measured to be nearly identical for the four Tyr residues of α-synuclein (α-Syn), whose ¹H^α-¹³C^α correlations were well-resolved in the 2D TR-CIDNP spectrum. Having confirmed the similarity between the time-resolved and steady-state photo-CIDNP results for α-Syn, we used the more sensitive latter method to show that divalent cations induce compaction of the C-terminal region and release of the N-terminal region of α-Syn. The photo-CIDNP method presented herein can be used as an orthogonal and independent method for investigating important biological processes associated with changes in the overall IDP conformation.

Revisiting the concept of peptide bond planarity in an iron-sulfur protein by neutron structure analysis

The planarity of the peptide bond is important for the stability and structure formation of proteins. However, substantial distortion of peptide bonds has been reported in several high-resolution structures and computational analyses. To investigate the peptide bond planarity, including hydrogen atoms, we report a 1.2-Å resolution neutron structure of the oxidized form of high-potential iron-sulfur protein. This high-resolution neutron structure shows that the nucleus positions of the amide protons deviate from the peptide plane and shift toward the acceptors. The planarity of the H─N─C═O plane depends strongly on the pyramidalization of the nitrogen atom. Moreover, the orientation of the amide proton of Cys⁷⁵ is different in the reduced and oxidized states, possibly because of the electron storage capacity of the iron-sulfur cluster.

Quantifying Protein Electrostatic Interactions in Cells by Nuclear Magnetic Resonance Spectroscopy

Most proteins perform their functions in cells. How the cellular environment modulates protein interactions is an important question. In this work, electrostatic interactions between protein charges were studied using in-cell nuclear magnetic resonance (NMR) spectroscopy. A total of eight charge pairs were introduced in protein GB3. Compared to the charge pair electrostatic interactions in a buffer, five charge pairs in cells displayed no apparent changes whereas three pairs had the interactions weakened by more than 70%. Further investigation suggests that the transfer free energy is responsible for the electrostatic interaction modulation. Both the transfer free energy of the folded state and that of the unfolded state can contribute to the cellular environmental effect on protein electrostatics, although the latter is generally larger (more negative) than the former. Our work highlights the importance of direct in-cell studies of protein interactions and thus protein function.

Advances in NMR Spectroscopy of Weakly Aligned Biomolecular Systems

The measurement and application of residual dipolar couplings (RDCs) in solution NMR studies of biological macromolecules has become well established over the past quarter of a century. Numerous methods for generating the requisite anisotropic orientational molecular distribution have been demonstrated, each with its specific strengths and weaknesses. In parallel, an enormous number of pulse schemes have been introduced to measure the many different types of RDCs, ranging from the most widely measured backbone amide ¹⁵N-¹H RDCs, to ¹H-¹H RDCs and couplings between low-γ nuclei. Applications of RDCs range from structure validation and refinement to the determination of relative domain orientations, the measurement of backbone and domain motions, and de novo structure determination. Nevertheless, it appears that the power of the RDC methodology remains underutilized. This review aims to highlight the practical aspects of sample preparation and RDC measurement while describing some of the most straightforward applications that take advantage of the exceptionally precise information contained in such data. Some emphasis will be placed on more recent developments that enable the accurate measurement of RDCs in larger systems, which is key to the ongoing shift in focus of biological NMR spectroscopy from structure determination toward gaining improved understanding of how molecular flexibility drives protein function.

TITANIA: Model-Free Interpretation of Residual Dipolar Couplings in the Context of Organic Compounds

Residual dipolar couplings (RDCs) become increasingly important as additional NMR parameters in the structure elucidation of organic compounds but are usually used in fitting procedures to discriminate between (computed) structures that are in accordance with RDCs and others that can be ruled out. Thus, the determination of configurations requires prior structural information. The direct use of RDCs as restraints to construct structures based on RDCs has only recently begun also in organic compounds. No protocol has been published though that uses the vector and dynamics information available in multialignment data sets directly for the joint determination of conformation and configuration of organic compounds. This is proposed in the current study. We show that by employing these data, even a flat or random start structure converges into the correctly configured structure when employing multiple alignment data sets in our iterative procedure. The requirements in terms of the number of RDCs and alignment media necessary are discussed in detail.

NMR hawk-eyed view of AlphaFold2 structures

The prediction of the three‐dimensional (3D) structure of proteins from the amino acid sequence made a stunning breakthrough reaching atomic accuracy. Using the neural network‐based method AlphaFold2, 3D structures of almost the entire human proteome have been predicted and made available (https://www.alphafold.ebi.ac.uk). To gain insight into how well AlphaFold2 structures represent the conformation of proteins in solution, I here compare the AlphaFold2 structures of selected small proteins with their 3D structures that were determined by nuclear magnetic resonance (NMR) spectroscopy. Proteins were selected for which the 3D solution structures were determined on the basis of a very large number of distance restraints and residual dipolar couplings and are thus some of the best‐resolved solution structures of proteins to date. The quality of the backbone conformation of the AlphaFold2 structures is assessed by fitting a large set of experimental residual dipolar couplings (RDCs). The analysis shows that experimental RDCs fit extremely well to the AlphaFold2 structures predicted for GB3, DinI, and ubiquitin. In the case of GB3, the accuracy of the AlphaFold2 structure even surpasses that of a 1.1 Å crystal structure. Fitting of experimental RDCs furthermore allows identification of AlphaFold2 structures that are best representative of the protein's conformation in solution as seen for the EF hands of the N‐terminal domain of Ca²⁺‐ligated calmodulin. Taken together, the analysis shows that structures predicted by AlphaFold2 can be highly representative of the solution conformation of proteins. The combination of AlphaFold2 structures with RDCs promises to be a powerful approach to study structural changes in proteins.

Force Field Benchmark of Amino Acids. 3. Hydration with Scaled Lennard-Jones Interactions

Classical protein force fields were reported with too weak protein-water interactions relative to protein-protein interactions, leading to more compact structures and artificial protein aggregation. Here we investigated the impacts of scaled Lennard-Jones (LJ) interactions on the hydration of amino acids and the simulation of folded and intrinsically disordered proteins (IDPs). The obtained optimal scaling parameters reproduce accurately hydration free energies of neutral amino acid side chain analogues and do not affect the compactness and structural stability of folded proteins significantly. The scaling leads to less compact IDPs and varies from case to case. Strengthening the interactions between protein and water oxygen or hydrogen atoms by increasing the interacting LJ well depth (ε) appears more effective than weakening protein-protein interactions by reducing the interacting dispersion coefficients (C₆). We demonstrate that weakening water-water interactions is a solution as well to obtaining more favorable protein-water interactions in an indirect way, although modern force fields like Amber ff19SB and a99SB-disp tend to use water models with strong water-water interactions. This is likely a compromise between strong protein-protein interactions and strong water-water interactions. Independent optimization of protein force fields and water models is therefore needed to make both interactions more close to reality, leading to good accuracy without bias or scaling.

Insight Into Pathological Integrin αIIbβ3 Activation From Safeguarding The Inactive State

The inhibition of physiological activation pathways of the platelet adhesion receptor integrin αIIbβ3 may fail to prevent fatal thrombosis, suggesting that the receptor is at risk of activation by yet an unidentified pathway. Here, we report the discovery and characterization of a structural motif that safeguards the receptor by selectively destabilizing its inactive state. At the extracellular membrane border, an overpacked αIIb(W968)-β3(I693) contact prevents αIIb(Gly972) from optimally assembling the αIIbβ3 transmembrane complex, which maintains the inactive state. This destabilization of approximately 1.0 kcal/mol could be mitigated by hydrodynamic forces but not physiological agonists, thereby identifying hydrodynamic forces as pathological activation stimulus. As reproductive life spans are not generally limited by cardiovascular disease, it appears that the evolution of the safeguard was driven by fatal, hydrodynamic force-mediated integrin αIIbβ3 activation in the healthy cardiovascular system. The triggering of the safeguard solely by pathological stimuli achieves an effective increase of the free energy barrier between inactive and active receptor states without incurring an increased risk of bleeding. Thus, integrin αIIbβ3 has evolved an effective way to protect receptor functional states that indicates the availability of a mechanical activation pathway when hydrodynamic forces exceed physiological margins.

Generating Five Independent Molecular Alignments for Simultaneous Protein Structure and Dynamics Determination Using Nuclear Magnetic Resonance Spectroscopy

Residual dipolar couplings (RDCs) are commonly used in NMR for protein structure and dynamics studies, but it is challenging to generate five independent RDC data sets (required for simultaneous structure and dynamics determination) for most protein molecules in the magnetic field. In this work, a reporter protein with a lanthanide tag is introduced to create five independent alignments. This reporter protein is then attached to target proteins where five independent sets of RDCs are also obtained for the target proteins. The fitting of RDCs provides important information about the structure and dynamics of the target proteins. The method is simple and effective and, in principle, can be used to generate complete sets of RDCs for different protein molecules.

Polyol and sugar osmolytes can shorten protein hydrogen bonds to modulate function

Polyol and sugar osmolytes are commonly used in therapeutic protein formulations. How they may affect protein structure and function is an important question. In this work, through NMR measurements, we show that glycerol and sorbitol (polyols), as well as glucose (sugar), can shorten protein backbone hydrogen bonds. The hydrogen bond shortening is also captured by molecular dynamics simulations, which suggest a hydrogen bond competition mechanism. Specifically, osmolytes weaken hydrogen bonds between the protein and solvent to strengthen those within the protein. Although the hydrogen bond change is small, with the average experimental cross hydrogen bond 3hJNC' coupling of two proteins GB3 and TTHA increased by ~ 0.01 Hz by the three osmolytes (160 g/L), its effect on protein function should not be overlooked. This is exemplified by the PDZ3-peptide binding where several intermolecular hydrogen bonds are formed and osmolytes shift the equilibrium towards the bound state.

Further Optimization and Validation of the Classical Drude Polarizable Protein Force Field

The CHARMM Drude-2013 polarizable force field (FF) was developed to include the explicit treatment of induced electronic polarizability, resulting in a more accurate description of the electrostatic interactions in molecular dynamics (MD) simulations. While the Drude-2013 protein FF has shown success in improving the folding properties of α-helical peptides and to reproduce experimental observables in simulations up to 1 μs, some limitations were noted regarding the stability of β-sheet structures in simulations longer than 100 ns as well as larger deviations from crystal structures in simulations of a number of proteins compared to the additive CHARMM36 protein FF. The origin of the instability has been identified and appears to be primarily due to overestimated atomic polarizabilities and induced dipole-dipole interactions on the Cβ, Cγ, and Cδ side chain atoms. To resolve this and other issues, a number of aspects of the model were revisited, resulting in Drude-2019 protein FF. Backbone parameters were optimized targeting the conformational properties of the (Ala)5 peptide in solution along with gas phase properties of the alanine dipeptide. Dipeptides that contain N-acetylated and N'-methylamidated termini, excluding Gly, Pro, and Ala, were used as models to optimize the atomic polarizabilities and Thole screening factors on selected Cβ, Cγ, and Cδ carbons by targeting quantum mechanical (QM) dipole moments and molecular polarizabilities. In addition, to obtain better conformational properties, side chain χ1 and χ2 dihedral parameters were optimized targeting QM data for the respective side chain dipeptide conformations as well as Protein Data Bank survey data based on the χ1, χ2 sampling from Hamiltonian replica-exchange MD simulations of (Ala)4-X-(Ala)4 in solution, where X is the amino acid of interest. Further improvements include optimizing nonbonded interactions between charged residues to reproduce QM interaction energies of the charged-protein model compounds and experimental osmotic pressures. Validation of the optimized Drude protein FF includes MD simulations of a collection of peptides and proteins including β-sheet structures, as well as transmembrane ion channels. Results showed that the updated Drude-2019 protein FF yields smaller overall root-mean-square differences of proteins as compared to the additive CHARMM36m and Drude-2013 FFs as well as similar or improved agreement with experimental NMR properties, allowing for long time scale simulation studies of proteins and more complex biomolecular systems in conjunction with the remainder of the Drude polarizable FF.

Deuteration of nonexchangeable protons on proteins affects their thermal stability, side-chain dynamics, and hydrophobicity

We have investigated the effect of deuteration of non-exchangeable protons on protein global thermal stability, hydrophobicity, and local flexibility using well-known thermostable model systems such as the villin headpiece subdomain (HP36) and the third immunoglobulin G-binding domain of protein G (GB3). Reversed-phase high-performance liquid chromatography (RP-HPLC) measurements as a function of temperature probe global thermal stability in the presence of acetonitrile, while differential scanning calorimetry determines thermal stability in solution. Both indicate small but measurable changes in the order of several degrees. RP-HPLC also permitted quantification of the effect of deuteration of just three core phenylalanine side chains of HP36. NMR dynamics investigation has focused on methyl axes motions using cross-correlated relaxation measurements. The analysis of order parameters provided a complex picture indicating that deuteration generally increases motional amplitudes of sub-nanosecond motion in GB3 but decreases those in HP36. Combined with earlier dynamics measurements at C_α -C_β sites and backbone sites of GB3, which probed slower time scales, the results point to the need to probe multiple atoms in the protein and variety of time scales to the discern the full complexity of the effects of deuteration on dynamics.

On the complementarity of X-ray and NMR data

X-ray crystallography and NMR contain complementary information for the structural characterization of biological macromolecules. X-ray diffraction is primarily sensitive to the overall shape of the molecule, whereas NMR is mostly sensitive to the atomic detail. Their combination can therefore provide a stronger justification for the resulting structure. For their combination we have recently proposed REFMAC-NMR, which relies on primary data from both techniques for joint refinement. This possibility raises the compelling question of how far the complementarity can be extended. In this paper, we describe an integrative approach to the refinement with NMR data of four X-ray structures of hen-egg-white lysozyme, solved at atomic resolution in four different crystal forms, and we demonstrate that the outcome critically depends on the crystal form itself, reflecting the sensitivity of NMR to fine details.

Enhanced solvation force extrapolation for speeding up molecular dynamics simulations of complex biochemical liquids

We propose an enhanced approach to the extrapolation of mean potential forces acting on atoms of solute macromolecules due to their interactions with solvent atoms in complex biochemical liquids. It improves and extends our previous extrapolation schemes by additionally including new techniques such as an exponential scaling transformation of coordinate space with weights complemented by an automatically adjusted balancing between the least square minimization of force deviations and the norm of expansion coefficients in the approximation. The expensive mean potential forces are treated in terms of the three-dimensional reference interaction site model with Kovalenko-Hirata closure molecular theory of solvation. During the dynamics, they are calculated only after every long (outer) time interval, i.e., quite rarely to reduce the computational costs. At much shorter (inner) time steps, these forces are extrapolated on the basis of their outer values. The equations of motion are then solved using a multiple time step integration within an optimized isokinetic Nosé-Hoover chain thermostat. The new approach is applied to molecular dynamics simulations of various systems consisting of solvated organic and biomolecules of different complexity. For example, we consider hydrated alanine dipeptide, asphaltene in toluene solvent, miniprotein 1L2Y, and protein G in aqueous solution. It is shown that in all these cases, the enhanced extrapolation provides much better accuracy of the solvation force approximation than the existing approaches. As a result, it can be used with much larger outer time steps, leading to a significant speedup of the simulations.

ff19SB: Amino-Acid-Specific Protein Backbone Parameters Trained against Quantum Mechanics Energy Surfaces in Solution

Molecular dynamics (MD) simulations have become increasingly popular in studying the motions and functions of biomolecules. The accuracy of the simulation, however, is highly determined by the molecular mechanics (MM) force field (FF), a set of functions with adjustable parameters to compute the potential energies from atomic positions. However, the overall quality of the FF, such as our previously published ff99SB and ff14SB, can be limited by assumptions that were made years ago. In the updated model presented here (ff19SB), we have significantly improved the backbone profiles for all 20 amino acids. We fit coupled φ/ψ parameters using 2D φ/ψ conformational scans for multiple amino acids, using as reference data the entire 2D quantum mechanics (QM) energy surface. We address the polarization inconsistency during dihedral parameter fitting by using both QM and MM in aqueous solution. Finally, we examine possible dependency of the backbone fitting on side chain rotamer. To extensively validate ff19SB parameters, and to compare to results using other Amber models, we have performed a total of ∼5 ms MD simulations in explicit solvent. Our results show that after amino-acid-specific training against QM data with solvent polarization, ff19SB not only reproduces the differences in amino-acid-specific Protein Data Bank (PDB) Ramachandran maps better but also shows significantly improved capability to differentiate amino-acid-dependent properties such as helical propensities. We also conclude that an inherent underestimation of helicity is present in ff14SB, which is (inexactly) compensated for by an increase in helical content driven by the TIP3P bias toward overly compact structures. In summary, ff19SB, when combined with a more accurate water model such as OPC, should have better predictive power for modeling sequence-specific behavior, protein mutations, and also rational protein design. Of the explicit water models tested here, we recommend use of OPC with ff19SB.

Extensive tests and evaluation of the CHARMM36IDPSFF force field for intrinsically disordered proteins and folded proteins

Intrinsically disordered proteins (IDPs) have received increasing attention in recent studies due to their structural heterogeneity and critical biological functions. To fully understand the structural properties and determine accurate ensembles of IDPs, molecular dynamics (MD) simulation was widely used to sample diverse conformations and reveal the structural dynamics. However, the classical state-of-the-art force fields perform well for folded proteins while being unsatisfactory for the simulations of disordered proteins reported in many previous studies. Thus, improved force fields were developed to precisely describe both folded proteins and disordered proteins. Preliminary tests show that our newly developed CHARMM36IDPSFF (C36IDPSFF) force field can well reproduce the experimental observables of several disordered proteins, but more tests on different types of proteins are needed to further evaluate the performance of C36IDPSFF. Here, we extensively simulate short peptides, disordered proteins, and fast-folding proteins as well as folded proteins, and compare the simulated results with the experimental observables. The simulation results show that C36IDPSFF could substantially reproduce the experimental observables for most of the tested proteins but some limitations are also found in the radius of gyration of large disordered proteins and the stability of fast-folding proteins. This force field will facilitate large scale studies of protein structural dynamics and functions using MD simulations.

Solution NMR Spectroscopy for the Determination of Structures of Membrane Proteins in a Lipid Environment

NMR spectroscopy has harnessed the recent technical advances to emerge as a competitive, elegant, and eminently viable technique for determining the solution structures of membrane proteins at the level of atomic resolution. Once a good level of cell-based or cell-free expression and purification of a suitably sized membrane protein has been achieved, then NMR offers a combination of several versatile strategies, for example choice of appropriate deuterated or nondeuterated detergents, temperature, and ionic strength; isotope labeling with ²H, ¹³C, ¹⁵N, with or without protonation of Ile (δ1), Leu, and Val methyl protons; combinatorial labeling or unlabeling of specific amino acids; TROSY based-, nonuniform sampling (NUS) based-, and other NMR experiments; measurement of residual dipolar couplings using stretched polyacrylamide gels or DNA nanotubes; spin labeling and paramagnetic relaxation enhancements (PRE). Strategic combinations of these advancements together with availability of highly sensitive cryogenically cooled-probes equipped high-field NMR spectrometers (up to 1 GHz ¹H frequency) have allowed the perseverant investigator to successfully overcome several of the conventional pitfalls associated with the NMR technique and membrane proteins, viz., low sensitivity, poor sample stability, spectral crowding, and a limited number of NOEs and other constraints for structure calculations. This has resulted in an unprecedented growth in the number of successfully determined NMR structures of large and complex membrane proteins over the last two decades, and this technique now holds great promise for the structure determination of an ever larger body of membrane proteins.

Dynamic cluster formation determines viscosity and diffusion in dense protein solutions

We develop a detailed description of protein translational and rotational diffusion in concentrated solution on the basis of all-atom molecular dynamics simulations in explicit solvent. Our systems contain up to 540 fully flexible proteins with 3.6 million atoms. In concentrated protein solutions (100 mg/mL and higher), the proteins ubiquitin and lysozyme, as well as the protein domains third IgG-binding domain of protein G and villin headpiece, diffuse not as isolated particles, but as members of transient clusters between which they constantly exchange. A dynamic cluster model nearly quantitatively explains the increase in viscosity and the decrease in protein diffusivity with protein volume fraction, which both exceed the predictions from widely used colloid models. The Stokes-Einstein relations for translational and rotational diffusion remain valid, but the effective hydrodynamic radius grows linearly with protein volume fraction. This increase follows the observed increase in cluster size and explains the more dramatic slowdown of protein rotation compared with translation. Baxter's sticky-sphere model of colloidal suspensions captures the concentration dependence of cluster size, viscosity, and rotational and translational diffusion. The consistency between simulations and experiments for a diverse set of soluble globular proteins indicates that the cluster model applies broadly to concentrated protein solutions, with equilibrium dissociation constants for nonspecific protein-protein binding in the Kd ≈ 10-mM regime.

Distance-independent Cross-correlated Relaxation and Isotropic Chemical Shift Modulation in Protein Dynamics Studies

Cross-correlated relaxation (CCR) in multiple-quantum coherences differs from other relaxation phenomena in its theoretical ability to be mediated across an infinite distance. The two interfering relaxation mechanisms may be dipolar interactions, chemical shift anisotropies, chemical shift modulations or quadrupolar interactions. These properties make multiple-quantum CCR an attractive probe for structure and dynamics of biomacromolecules not accessible from other measurements. Here, we review the use of multiple-quantum CCR measurements in dynamics studies of proteins. We compile a list of all experiments proposed for CCR rate measurements, provide an overview of the theory with a focus on protein dynamics, and present applications to various protein systems.

Peptide bond conformation in peptides and proteins probed by dipolar coupling-chemical shift tensor correlation solid-state NMR

Multidimensional magic-angle spinning solid-state NMR experiments are described that permit cis and trans peptide bonds in uniformly 13C,15N-labeled peptides and proteins to be unambiguously distinguished in residue-specific manner by determining the relative orientations of the amide 13C' CSA and 1H-15N dipolar coupling tensors. The experiments are demonstrated for model peptides glycylglycine and 2,5-diketopiperazine containing trans and cis peptide bonds, respectively. Subsequently, the measurements are extended to two representative proteins that contain exclusively trans peptide bonds, microcrystalline B3 immunoglobulin domain of protein G and Y145Stop human prion protein amyloid fibrils, to illustrate their applicability to a wide range of protein systems.

Correlated motions of C'-N and Cα-Cβ pairs in protonated and per-deuterated GB3

We investigated correlated µs-ms time scale motions of neighboring ¹³C'-¹⁵N and ¹³C_α-¹³C_β nuclei in both protonated and perdeuterated samples of GB3. The techniques employed, NMR relaxation due to cross-correlated chemical shift modulations, specifically target concerted changes in the isotropic chemical shifts of the two nuclei associated with spatial fluctuations. Field-dependence of the relaxation rates permits identification of the parameters defining the chemical exchange rate constant under the assumption of a two-site exchange. The time scale of motions falls into the intermediate to fast regime (with respect to the chemical shift time scale, 100-400 s^-1 range) for the ¹³C'-¹⁵N pairs and into the slow to intermediate regime for the ¹³C_α-¹³C_β pairs (about 150 s^-1). Comparison of the results obtained for protonated and deuterated GB3 suggests that deuteration has a tendency to reduce these slow scale correlated motions, especially for the ¹³C_α-¹³C_β pairs.

Residual Dipolar Couplings in Structure Determination of Natural Products

The determination of natural products stereochemistry remains a formidable task. Residual dipolar couplings (RDCs) induced by anisotropic media are a powerful tool for determination of the stereochemistry of organic molecule in solution. This review will provide a short introduction on RDCs-based methodology for the structural elucidation of natural products. Special attention is given to the current availability of alignment media in organic solvents. The applications of RDCs for structural analysis of some examples of natural products were discussed and summarized. This review provides a short introduction on RDCs-based methodology for the structural elucidation of natural products. Special attention is given to the current availability of alignment media in organic solvents. The applications of RDCs for structural analysis of some examples of natural products were discussed and summarized.

Chemical shift-based methods in NMR structure determination

Chemical shifts are highly sensitive probes harnessed by NMR spectroscopists and structural biologists as conformational parameters to characterize a range of biological molecules. Traditionally, assignment of chemical shifts has been a labor-intensive process requiring numerous samples and a suite of multidimensional experiments. Over the past two decades, the development of complementary computational approaches has bolstered the analysis, interpretation and utilization of chemical shifts for elucidation of high resolution protein and nucleic acid structures. Here, we review the development and application of chemical shift-based methods for structure determination with a focus on ab initio fragment assembly, comparative modeling, oligomeric systems, and automated assignment methods. Throughout our discussion, we point out practical uses, as well as advantages and caveats, of using chemical shifts in structure modeling. We additionally highlight (i) hybrid methods that employ chemical shifts with other types of NMR restraints (residual dipolar couplings, paramagnetic relaxation enhancements and pseudocontact shifts) that allow for improved accuracy and resolution of generated 3D structures, (ii) the utilization of chemical shifts to model the structures of sparsely populated excited states, and (iii) modeling of sidechain conformations. Finally, we briefly discuss the advantages of contemporary methods that employ sparse NMR data recorded using site-specific isotope labeling schemes for chemical shift-driven structure determination of larger molecules. With this review, we aim to emphasize the accessibility and versatility of chemical shifts for structure determination of challenging biological systems, and to point out emerging areas of development that lead us towards the next generation of tools.

A Force Balanced Fragmentation Method for ab Initio Molecular Dynamic Simulation of Protein

A force balanced generalized molecular fractionation with conjugate caps (FB-GMFCC) method is proposed for ab initio molecular dynamic simulation of proteins. In this approach, the energy of the protein is computed by a linear combination of the QM energies of individual residues and molecular fragments that account for the two-body interaction of hydrogen bond between backbone peptides. The atomic forces on the caped H atoms were corrected to conserve the total force of the protein. Using this approach, ab initio molecular dynamic simulation of an Ace-(ALA)₉-NME linear peptide showed the conservation of the total energy of the system throughout the simulation. Further a more robust 110 ps ab initio molecular dynamic simulation was performed for a protein with 56 residues and 862 atoms in explicit water. Compared with the classical force field, the ab initio molecular dynamic simulations gave better description of the geometry of peptide bonds. Although further development is still needed, the current approach is highly efficient, trivially parallel, and can be applied to ab initio molecular dynamic simulation study of large proteins.

Utilizing dipole-dipole cross-correlated relaxation for the measurement of angles between pairs of opposing CαHα-CαHα bonds in anti-parallel β-sheets

Dipole-dipole cross-correlated relaxation (CCR) between two spin pairs is rich with macromolecular structural and dynamic information on inter-nuclear bond vectors. Measurement of short range dipolar CCR rates has been demonstrated for a variety of inter-nuclear vector spin pairs in proteins and nucleic acids, where the multiple quantum coherence necessary for observing the CCR rate is created by through-bond scalar coupling. In principle, CCR rates can be measured for any pair of inter-nuclear vectors where coherence can be generated between one spin of each spin pair, regardless of both the distance between the two spin pairs and the distance of the two spins forming the multiple quantum coherence. In practice, however, long range CCR (lrCCR) rates are challenging to measure due to difficulties in linking spatially distant spin pairs. By utilizing through-space relaxation allowed coherence transfer (RACT), we have developed a new method for the measurement of lrCCR rates involving CαHα bonds on opposing anti-parallel β-strands. The resulting lrCCR rates are straightforward to interpret since only the angle between the two vectors modulates the strength of the interference effect. We applied our lrCCR measurement to the third immunoglobulin-binding domain of the streptococcal protein G (GB3) and utilize published NMR ensembles and static NMR/X-ray structures to highlight the relationship between the lrCCR rates and the CαHα-CαHα inter-bond angle and bond mobility. Furthermore, we employ the lrCCR rates to guide the selection of sub-ensembles from the published NMR ensembles for enhancing the structural and dynamic interpretation of the data. We foresee this methodology for measuring lrCCR rates as improving the generation of structural ensembles by providing highly accurate details concerning the orientation of CαHα bonds on opposing anti-parallel β-strands.

Direct Observation of CH/CH van der Waals Interactions in Proteins by NMR

van der Waals interactions are important to protein stability and function. These interactions are usually identified empirically based on protein 3D structures. In this work, we performed a solution nuclear magnetic resonance (NMR) spectroscopy study of van der Waals interactions by detecting the through-space vdw JCC-coupling between protein aliphatic side chain groups. Specifically, vdw JCC-coupling values up to ∼0.5 Hz were obtained between the methyl and nearby aliphatic groups in protein GB3, providing direct experimental evidence for the van der Waals interactions. Quantum mechanical calculations suggest that the J-coupling is correlated with the exchange-repulsion term of van der Waals interaction. NMR detection of vdw JCC-coupling offers a new tool to characterize such interactions in proteins.

Overview of refinement procedures within REFMAC5: utilizing data from different sources

Refinement is a process that involves bringing into agreement the structural model, available prior knowledge and experimental data. To achieve this, the refinement procedure optimizes a posterior conditional probability distribution of model parameters, including atomic coordinates, atomic displacement parameters (B factors), scale factors, parameters of the solvent model and twin fractions in the case of twinned crystals, given observed data such as observed amplitudes or intensities of structure factors. A library of chemical restraints is typically used to ensure consistency between the model and the prior knowledge of stereochemistry. If the observation-to-parameter ratio is small, for example when diffraction data only extend to low resolution, the Bayesian framework implemented in REFMAC5 uses external restraints to inject additional information extracted from structures of homologous proteins, prior knowledge about secondary-structure formation and even data obtained using different experimental methods, for example NMR. The refinement procedure also generates the `best' weighted electron-density maps, which are useful for further model (re)building. Here, the refinement of macromolecular structures using REFMAC5 and related tools distributed as part of the CCP4 suite is discussed.

Ab Initio Prediction of NMR Spin Relaxation Parameters from Molecular Dynamics Simulations

¹H-¹⁵N NMR spin relaxation and relaxation dispersion experiments can reveal the time scale and extent of protein motions across the ps-ms range, where the ps-ns dynamics revealed by fundamental quantities R₁, R₂, and heteronuclear NOE can be well-sampled by molecular dynamics simulations (MD). Although the principles of relaxation prediction from simulations are well-established, numerous NMR-MD comparisons have hitherto focused upon the aspect of order parameters S² due to common artifacts in the prediction of transient dynamics. We therefore summarize here all necessary components and highlight existing and proposed solutions, such as the inclusion of quantum mechanical zero-point vibrational corrections and separate MD convergence of global and local motions in coarse-grained and all-atom force fields, respectively. For the accuracy of the MD prediction to be tested, two model proteins GB3 and Ubiquitin are used to validate five atomistic force fields against published NMR data supplemented by the coarse-grained force field MARTINI+EN. In Amber and CHARMM-type force fields, quantitative agreement was achieved for structured elements with minimum adjustment of global parameters. Deviations from experiment occur in flexible loops and termini, indicating differences in both the extent and time scale of backbone motions. The lack of systematic patterns and water model dependence suggests that modeling of the local environment limits prediction accuracy. Nevertheless, qualitative accuracy in a 2 μs CHARMM36m Stam2 VHS domain simulation demonstrates the potential of MD-based interpretation in combination with NMR-measured dynamics, increasing the utility of spin relaxation in integrative structural biology.

Multiscale methods framework: self-consistent coupling of molecular theory of solvation with quantum chemistry, molecular simulations, and dissipative particle dynamics

In this work, we will address different aspects of self-consistent field coupling of computational chemistry methods at different time and length scales in modern materials and biomolecular science.

Broadening the functionality of a J-protein/Hsp70 molecular chaperone system

By binding to a multitude of polypeptide substrates, Hsp70-based molecular chaperone systems perform a range of cellular functions. All J-protein co-chaperones play the essential role, via action of their J-domains, of stimulating the ATPase activity of Hsp70, thereby stabilizing its interaction with substrate. In addition, J-proteins drive the functional diversity of Hsp70 chaperone systems through action of regions outside their J-domains. Targeting to specific locations within a cellular compartment and binding of specific substrates for delivery to Hsp70 have been identified as modes of J-protein specialization. To better understand J-protein specialization, we concentrated on Saccharomyces cerevisiae SIS1, which encodes an essential J-protein of the cytosol/nucleus. We selected suppressors that allowed cells lacking SIS1 to form colonies. Substitutions changing single residues in Ydj1, a J-protein, which, like Sis1, partners with Hsp70 Ssa1, were isolated. These gain-of-function substitutions were located at the end of the J-domain, suggesting that suppression was connected to interaction with its partner Hsp70, rather than substrate binding or subcellular localization. Reasoning that, if YDJ1 suppressors affect Ssa1 function, substitutions in Hsp70 itself might also be able to overcome the cellular requirement for Sis1, we carried out a selection for SSA1 suppressor mutations. Suppressing substitutions were isolated that altered sites in Ssa1 affecting the cycle of substrate interaction. Together, our results point to a third, additional means by which J-proteins can drive Hsp70's ability to function in a wide range of cellular processes-modulating the Hsp70-substrate interaction cycle.

Detection of Correlated Protein Backbone and Side-Chain Angle Fluctuations

NMR methods for the characterization of local protein motions have attained a high level of sophistication. Measurement of the synchronization between those motions, however, poses a serious challenge. Such correlated motions are one of the underlying mechanisms for the propagation of local changes to remote sites and as such for information transfer. Here, we demonstrate the experimental detection of the synchronization of motion over an intermediate range. To that purpose, we designed pulse sequences for the measurement of cross-correlated relaxation between the backbone H^N -N and side-chain H^β -C^β dipoles in Ile, Thr, and Val in the protein GB3. These bonds are related through two and three intervening dihedral angles. We show that the correlated motions inherent in a structural ensemble obtained from a large and diverse array of NMR probes are in excellent agreement with our measurements.

Dynamic Descriptions of Highly Flexible Molecules from NMR Dipolar Couplings: Physical Basis and Limitations

Biomolecules that control physiological function by changing their conformation play key roles in biology and remain poorly characterized. NMR dipolar couplings (DCs) depend intrinsically on both molecular shape and structural fluctuations, thereby providing the enticing prospect of tracking these conformational changes at atomic detail. Although this dual dependence has until now severely complicated analysis of DCs from highly dynamic systems, general approaches have recently been proposed that simplify interpretation of experimental DCs, by entirely eliminating molecular alignment from the analysis. Using simple and intuitive simulation of target ensembles, we investigate the impact of such approaches on the resulting descriptions of the conformational energy landscape. We find that ensemble descriptions of highly flexible systems derived from DCs without explicit consideration of the alignment properties of the constituent conformations can be compromised and inaccurate, despite exhibiting high correlation with experimental measurement.

Cross-correlated relaxation rates between protein backbone H-X dipolar interactions

The relaxation interference between dipole-dipole interactions of two separate spin pairs carries structural and dynamics information. In particular, when compared to individual dynamic behavior of those spin pairs, such cross-correlated relaxation (CCR) rates report on the correlation between the spin pairs. We have recently mapped out correlated motion along the backbone of the protein GB3, using CCR rates among and between consecutive H^N-N and H^α-C^α dipole-dipole interactions. Here, we provide a detailed account of the measurement of the four types of CCR rates. All rates were obtained from at least two different pulse sequences, of which the yet unpublished ones are presented. Detailed comparisons between the different methods and corrections for unwanted pathways demonstrate that the averaged CCR rates are highly accurate and precise with errors of 1.5-3% of the entire value ranges.

Automated Fragmentation Polarizable Embedding Density Functional Theory (PE-DFT) Calculations of Nuclear Magnetic Resonance (NMR) Shielding Constants of Proteins with Application to Chemical Shift Predictions

Full-protein nuclear magnetic resonance (NMR) shielding constants based on ab initio calculations are desirable, because they can assist in elucidating protein structures from NMR experiments. In this work, we present NMR shielding constants computed using a new automated fragmentation (J. Phys. Chem. B 2009, 113, 10380-10388) approach in the framework of polarizable embedding density functional theory. We extend our previous work to give both basis set recommendations and comment on how large the quantum mechanical region should be to successfully compute ¹³C NMR shielding constants that are comparable with experiment. The introduction of a probabilistic linear regression model allows us to substantially reduce the number of snapshots that are needed to make comparisons with experiment. This approach is further improved by augmenting snapshot selection with chemical shift predictions by which we can obtain a representative subset of snapshots that gives the smallest predicted error, compared to experiment. Finally, we use this subset of snapshots to calculate the NMR shielding constants at the PE-KT3/pcSseg-2 level of theory for all atoms in the protein GB3.