Structural Characterization of the Phosphotyrosine Binding Region of a High-Affinity SH2 Domain−Phosphopeptide Complex by Molecular Dynamics Simulation and Chemical Shift Calculations

Parameter Dependence of the Solubility Limit for Disodium Phosphate

The solubility limit was calculated for supersaturated solutions of disodium phosphate in water as a function of the sodium-oxygen Lennard-Jones radius parameter Rmin. We found that changes in the sodium-oxygen Rmin were clearly exponentially related to the concentration of the solubility limit. Starting from standard force fields more suited to nucleic acids and phospholipids, only relatively small changes were required to achieve the experimentally known solubility limit. Simultaneously, we found that it was possible to achieve the solubility limit and the osmotic pressure with the same model parameters. Based on transferability, the adjusted Rmin parameter can be used to more accurately model phosphorylated proteins.

Phosphorylation Modification Force Field FB18CMAP Improving Conformation Sampling of Phosphoproteins

Phosphorylation of proteins plays an important regulatory role at almost all levels of cellular organization. Molecular dynamics (MD) simulation is a promising tool to reveal the mechanism of how phosphorylation regulates many key biological processes at the atomistic level. MD simulation accuracy depends on force field precision, while the current force fields for phospho-amino acids have resulted in notable inconsistency with experimental data. Here, a new force field parameter (named FB18CMAP) is generated by fitting against quantum mechanics (QM) energy in aqueous solution with φ/ψ dihedral potential-energy surfaces optimized using CMAP parameters. MD simulations of phosphorylated dipeptides, intrinsically disordered proteins (IDPs), and ordered (folded) proteins show that FB18CMAP can mimic NMR observables and structural characteristics of phosphorylated dipeptides and proteins more accurately than the FB18 force field. These findings suggest that FB18CMAP performs well in both the simulation of ordered and disordered states of phosphorylated proteins.

Thirty years of molecular dynamics simulations on posttranslational modifications of proteins

Posttranslational modifications (PTMs) are an integral component to how cells respond to perturbation. While experimental advances have enabled improved PTM identification capabilities, the same throughput for characterizing how structural changes caused by PTMs equate to altered physiological function has not been maintained. In this Perspective, we cover the history of computational modeling and molecular dynamics simulations which have characterized the structural implications of PTMs. We distinguish results from different molecular dynamics studies based upon the timescales simulated and analysis approaches used for PTM characterization. Lastly, we offer insights into how opportunities for modern research efforts on in silico PTM characterization may proceed given current state-of-the-art computing capabilities and methodological advancements.

Development and Validation of AMBER-FB15-Compatible Force Field Parameters for Phosphorylated Amino Acids

Phosphorylation of select amino acid residues is one of the most common biological mechanisms for regulating protein structures and functions. While computational modeling can be used to explore the detailed structural changes associated with phosphorylation, most molecular mechanics force fields developed for the simulation of phosphoproteins have been noted to be inconsistent with experimental data. In this work, we parameterize force fields for the phosphorylated forms of the amino acids serine, threonine, and tyrosine using the ForceBalance software package with the goal of improving agreement with experiments for these residues. Our optimized force field, denoted as FB18, is parameterized using high-quality ab initio potential energy scans and is designed to be fully compatible with the AMBER-FB15 protein force field. When utilized in MD simulations together with the TIP3P-FB water model, we find that FB18 consistently enhances the prediction of experimental quantities such as ³J NMR couplings and intramolecular hydrogen-bonding propensities in comparison to previously published models. As was reported with AMBER-FB15, we also see improved agreement with the reference QM calculations in regions at and away from local minima. We thus believe that the FB18 parameter set provides a promising route for the further investigation of the varied effects of protein phosphorylation.

Improved GROMOS 54A7 Charge Sets for Phosphorylated Tyr, Ser, and Thr to Deal with pH-Dependent Binding Phenomena

Phosphorylation is a ubiquitous post-translational modification in proteins, and the phosphate group is present constitutively or transiently in most biological building blocks. These phosphorylated biomolecules are involved in many high-affinity binding/unbinding events that rely predominantly on electrostatic interactions. To build accurate models of these molecules, we need an improved description of the atomic partial charges for all relevant protonation states. In this work, we showed that the commonly used protocols to derive atomic partial charges using well-solvated molecules are inadequate to model the protonation equilibria in binding events. We introduced a protocol based on PB/MC calculations with a single representative conformation (of both protonation states) and used the resulting pK_a estimations to help manually curate the atomic partial charges. The final charge set, which is fully compatible with the GROMOS 54A7 force field, proved to be very effective in modeling the protonation equilibrium in different phosphorylated peptides in the free (tetrapeptides, pentapeptides, and pY1021) and protein-complexed forms (pY1021/PLC-γ1 complex). This was particularly important in the case of the pY1021 bound to the SH2 domain of PLC-γ1, where only our curated charge set captured the correct protonation equilibrium at the neutral to slightly acidic pH range. The binding/unbinding phenomena in that pH range are biologically relevant, and to improve our models, we need to go beyond the commonly used protocols and obtain revised force field parameters for these molecules.

AMBER and CHARMM Force Fields Inconsistently Portray the Microscopic Details of Phosphorylation

Phosphorylation of serine, threonine, and tyrosine is one of the most frequently occurring and crucial post-translational modifications of proteins often associated with important structural and functional changes. We investigated the direct effect of phosphorylation on the intrinsic conformational preferences of amino acids as a potential trigger of larger structural events. We conducted a comparative study of force fields on terminally capped amino acids (dipeptides) as the simplest model for phosphorylation. Our bias-exchange metadynamics simulations revealed that all model dipeptides sampled a great heterogeneity of ensembles affected by introduction of mono- and dianionic phosphate groups. However, the detected changes in populations of backbone conformers and side-chain rotamers did not reveal a strong discriminatory shift in preferences, as could be anticipated for the bulky, charged phosphate group. Furthermore, the AMBER and CHARMM force fields provided inconsistent populations of individual conformers as well as net structural trends upon phosphorylation. Detailed analysis of ensembles revealed competition between hydration and formation of internal hydrogen bonds involving amide hydrogens and the phosphate group. The observed difference in hydration free energy and potential for hydrogen bonding in individual force fields could be attributed to the different partial atomic charges used in each force field and, hence, the different parametrization strategies. Nevertheless, conformational propensities and net structural changes upon phosphorylation are difficult to extract from experimental measurements, and existing experimental data provide limited guidance for force field assessment and further development.

Classical Drude Polarizable Force Field Model for Methyl Phosphate and Its Interactions with Mg2

Phosphate groups are essential components of nucleic acids and proteins, whose interactions with solvent, metal ions, and ionic side chains help control folding and binding. Methyl phosphate (MP) represents a simple analog of phosphate moieties that are post-translation modifications in proteins and present at the termini of nucleic acids, among other environments. In the present study, we optimized parameters for use in polarizable molecular dynamics simulations of MP in its mono- and dianionic forms, MP- ≡ CH3HPO4- and MP2- ≡ CH3PO42-, along with P i2- ≡ HPO42-, in the context of the classical Drude oscillator model. Parameter optimization was done in a manner consistent with the remainder of the Drude molecular mechanics force field, choosing atomic charges and polarizabilities to reproduce molecular properties from quantum mechanics as well as experimental hydration free energies. Optimized parameters were similar to existing dimethyl phosphate parameters, with a few significant differences. The developed parameters were then used to compute magnesium binding affinities in aqueous solution, using alchemical molecular dynamics free energy simulations. Good agreement with experiment was obtained, and outer sphere binding was shown to be predominant for MP- and MP2-.

Theoretical Studies of Interactions between O-Phosphorylated and Standard Amino-Acid Side-Chain Models in Water

Phosphorylation is a common post-translational modification of the amino-acid side chains (serine, tyrosine, and threonine) that contain hydroxyl groups. The transfer of the negatively charged phosphate group from an ATP molecule to such amino-acid side chains leads to changes in the local conformations of proteins and the pattern of interactions with other amino-acid side-chains. A convenient characteristic of the side chain-side chain interactions in the context of an aqueous environment is the potential of mean force (PMF) in water. A series of umbrella-sampling molecular dynamic (MD) simulations with the AMBER force field were carried out for pairs of O-phosphorylated serine (pSer), threonine (pThr), and tyrosine, (pTyr) with natural amino acids in a TIP3P water model as a solvent at 298 K. The weighted-histogram analysis method was used to calculate the four-dimensional potentials of mean force. The results demonstrate that the positions and depths of the contact minima and the positions and heights of the desolvation maxima, including their dependence on the relative orientation depend on the character of the interacting pairs. More distinct minima are observed for oppositely charged pairs such as, e.g., O-phosphorylated side-chains and positively charged ones, such as the side-chains of lysine and arginine.

Multiple steps to activate FAK's kinase domain: adaptation to confined environments?

Protein kinases regulate cell signaling by phosphorylating their substrates in response to environment-specific stimuli. Using molecular dynamics, we studied the catalytically active and inactive conformations of the kinase domain of the focal adhesion kinase (FAK), which are distinguished by displaying a structured or unstructured activation loop, respectively. Upon removal of an ATP analog, we show that the nucleotide-binding pocket in the catalytically active conformation is structurally unstable and fluctuates between an open and closed configuration. In contrast, the pocket remains open in the catalytically inactive form upon removal of an inhibitor from the pocket. Because temporal pocket closures will slow the ATP on-rate, these simulations suggest a multistep process in which the kinase domain is more likely to bind ATP in the catalytically inactive than in the active form. Transient closures of the ATP-binding pocket might allow FAK to slow down its catalytic cycle. These short cat naps could be adaptions to crowded or confined environments by giving the substrate sufficient time to diffuse away. The simulations show further how either the phosphorylation of the activation loop or the activating mutations of the so-called SuperFAK influence the electrostatic switch that controls kinase activity.

Phosphorylation primes vinculin for activation

Vinculin phosphorylation has been implicated as a potential mechanism for focal adhesion growth and maturation. Four vinculin residues-Y100, S1033, S1045, and Y1065-are phosphorylated by kinases during focal adhesion maturation. In this study, phosphorylation at each of these residues is simulated using molecular dynamics models. The simulations demonstrate that once each phosphorylated vinculin structure is at equilibrium, significant local conformational changes result that may impact either vinculin activation or vinculin binding to actin and PIP2. Simulation of vinculin activation after phosphorylation shows that the added phosphoryl groups can prime vinculin for activation. It remains to be seen if vinculin can be phosphorylated at S1033 in vivo, but these simulations highlight that in the event of a S1033 phophorylation vinculin will likely be primed for activation.

Influence of the enzyme phosphorylation state and the substrate on PKA enzyme dynamics

cAMP-dependent protein kinase (PKA) is one of the simplest and best understood members of the protein kinase family. In a previous study, we have theoretically studied the complex between PKA and the heptapeptide substrate Kemptide by classical molecular dynamics. On the basis of the results obtained for Kemptide, the aim of the present work is to explore how the different conditions, such as phosphorylation state, substrate, and mutations of key residues affect the enzyme dynamics. We have built different models of the complex; particularly we have focused our attention on two crystallographic structures which main difference consists in their phosphorylation state. The first one has the residue Thr197 modified into a phospho-threonine (pThr197); the second one, in addition to the same Thr197, has also the residue Ser338 modified into a phospho-serine (pSer338). In addition, we have analyzed the effect of the choice of the substrate by building a model of the PKA-SP20 Michaelis complex. Finally, we have theoretically studied the effect of the mutation of the highly conserved residue Asp166 that, experimentally, leads to a decrease of the reaction rate. The results of this study give insight into the dynamical states of the enzyme and their relationship with different elements of the model, which correspond to different natural or human guided situations of the active biological system.

CHARMM general force field: A force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields

The widely used CHARMM additive all-atom force field includes parameters for proteins, nucleic acids, lipids, and carbohydrates. In the present article, an extension of the CHARMM force field to drug-like molecules is presented. The resulting CHARMM General Force Field (CGenFF) covers a wide range of chemical groups present in biomolecules and drug-like molecules, including a large number of heterocyclic scaffolds. The parametrization philosophy behind the force field focuses on quality at the expense of transferability, with the implementation concentrating on an extensible force field. Statistics related to the quality of the parametrization with a focus on experimental validation are presented. Additionally, the parametrization procedure, described fully in the present article in the context of the model systems, pyrrolidine, and 3-phenoxymethylpyrrolidine will allow users to readily extend the force field to chemical groups that are not explicitly covered in the force field as well as add functional groups to and link together molecules already available in the force field. CGenFF thus makes it possible to perform "all-CHARMM" simulations on drug-target interactions thereby extending the utility of CHARMM force fields to medicinally relevant systems.

CHARMM: the biomolecular simulation program

CHARMM (Chemistry at HARvard Molecular Mechanics) is a highly versatile and widely used molecular simulation program. It has been developed over the last three decades with a primary focus on molecules of biological interest, including proteins, peptides, lipids, nucleic acids, carbohydrates, and small molecule ligands, as they occur in solution, crystals, and membrane environments. For the study of such systems, the program provides a large suite of computational tools that include numerous conformational and path sampling methods, free energy estimators, molecular minimization, dynamics, and analysis techniques, and model-building capabilities. The CHARMM program is applicable to problems involving a much broader class of many-particle systems. Calculations with CHARMM can be performed using a number of different energy functions and models, from mixed quantum mechanical-molecular mechanical force fields, to all-atom classical potential energy functions with explicit solvent and various boundary conditions, to implicit solvent and membrane models. The program has been ported to numerous platforms in both serial and parallel architectures. This article provides an overview of the program as it exists today with an emphasis on developments since the publication of the original CHARMM article in 1983.

Conformational changes in protein loops and helices induced by post-translational phosphorylation

Post-translational phosphorylation is a ubiquitous mechanism for modulating protein activity and protein-protein interactions. In this work, we examine how phosphorylation can modulate the conformation of a protein by changing the energy landscape. We present a molecular mechanics method in which we phosphorylate proteins in silico and then predict how the conformation of the protein will change in response to phosphorylation. We apply this method to a test set comprised of proteins with both phosphorylated and non-phosphorylated crystal structures, and demonstrate that it is possible to predict localized phosphorylation-induced conformational changes, or the absence of conformational changes, with near-atomic accuracy in most cases. Examples of proteins used for testing our methods include kinases and prokaryotic response regulators. Through a detailed case study of cyclin-dependent kinase 2, we also illustrate how the computational methods can be used to provide new understanding of how phosphorylation drives conformational change, why substituting Glu or Asp for a phosphorylated amino acid does not always mimic the effects of phosphorylation, and how a phosphatase can “capture” a phosphorylated amino acid. This work illustrates how computational methods can be used to elucidate principles and mechanisms of post-translational phosphorylation, which can ultimately help to bridge the gap between the number of known sites of phosphorylation and the number of structures of phosphorylated proteins.

Many proteins are chemically modified after they are synthesized in the cell. These post-translational modifications can modulate the ability of a protein to perform chemical reactions and to interact with other proteins. At the cellular level, for example, these chemical modifications are critical for allowing the cell to respond to its environment and control its division. One of the most common mechanisms by which proteins can be modified is by phosphorylation—the addition of a phosphate group to an amino acid side chain of the protein. Thousands of proteins are known to be modified by phosphorylation, but only for a small minority of these do we have any detailed understanding of how the chemical modification regulates the function of the protein. The authors describe a computational method that can make testable predictions about the structural changes that occur in a protein induced by post-translational phosphorylation. Their results show that the method can produce structural models of the phosphorylated proteins with near-atomic accuracy, and provide insight into the energetics of conformational switches driven by phosphorylation. As such, the computational method complements experiments aimed at understanding the mechanisms of protein regulation by phosphorylation.

Src kinase activation: A switched electrostatic network

Src tyrosine kinases are essential in numerous cell signaling pathways, and improper functioning of these enzymes has been implicated in many diseases. The activity of Src kinases is regulated by conformational activation, which involves several structural changes within the catalytic domain (CD): the orientation of two lobes of CD; rearrangement of the activation loop (A-loop); and movement of an alpha-helix (alphaC), which is located at the interface between the two lobes, into or away from the catalytic cleft. Conformational activation was investigated using biased molecular dynamics to explore the transition pathway between the active and the down-regulated conformation of CD for the Src-kinase family member Lyn kinase, and to gain insight into the interdependence of these changes. Lobe opening is observed to be a facile motion, whereas movement of the A-loop motion is more complex requiring secondary structure changes as well as communication with alphaC. A key result is that the conformational transition involves a switch in an electrostatic network of six polar residues between the active and the down-regulated conformations. The exchange between interactions links the three main motions of the CD. Kinetic experiments that would demonstrate the contribution of the switched electrostatic network to the enzyme mechanism are proposed. Possible implications for regulation conferred by interdomain interactions are also discussed.

An AMBER/DYANA/MOLMOL phosphorylated amino acid library set and incorporation into NMR structure calculations

Protein structure determination using Nuclear Magnetic Resonance (NMR) requires the use of molecular dynamics programs that incorporate both NMR experimental and implicit atomic data. Atomic parameters for each amino acid type are encoded in libraries used by structure calculation programs such as DYANA and AMBER. However, only a few non-standard amino acid library sets are included in these programs or the molecular visualization program MOLMOL. Our laboratory is calculating the phosphorylated and non-phosphorylated states of peptides and proteins using NMR methods. To calculate chemically correct structures, we have extended the available molecular libraries for these programs to include the modified amino acids phosphoserine, phosphothreonine, and phosphotyrosine.

Grid-based steered thermodynamic integration accelerates the calculation of binding free energies

The calculation of binding free energies is important in many condensed matter problems. Although formally exact computational methods have the potential to complement, add to, and even compete with experimental approaches, they are difficult to use and extremely time consuming. We describe a Grid-based approach for the calculation of relative binding free energies, which we call Steered Thermodynamic Integration calculations using Molecular Dynamics (STIMD), and its application to Src homology 2 (SH2) protein cell signalling domains. We show that the time taken to compute free energy differences using thermodynamic integration can be significantly reduced: potentially from weeks or months to days of wall-clock time. To be able to perform such accelerated calculations requires the ability to both run concurrently and control in realtime several parallel simulations on a computational Grid. We describe how the RealityGrid computational steering system, in conjunction with a scalable classical MD code, can be used to dramatically reduce the time to achieve a result. This is necessary to improve the adoption of this technique and further allows more detailed investigations into the accuracy and precision of thermodynamic integration. Initial results for the Src SH2 system are presented and compared to a reported experimental value. Finally, we discuss the significance of our approach.

Competition between Intramolecular Hydrogen Bonds and Solvation in Phosphorylated Peptides: Simulations with Explicit and Implicit Solvent

The atomic-level mechanisms of protein regulation by post-translational phosphorylation remain poorly understood, except in a few well-studied systems. Molecular mechanics simulations can in principle be used to help understand and predict the effects of protein phosphorylation, but the accuracy of the results will of course depend on the quality of the force field parameters for the phosphorylated residues as well as the quality of the solvent model. The phosphorylated residues typically carry a -2 charge at physiological pH; however, the effects of phosphorylation can sometimes be mimicked by substituting Asp or Glu for the phosphorylated residue. Here we examine the suitability of explicit and implicit solvent models for simulating phospho-serine in both the -1 and -2 charge states. Specifically, we simulate a capped phosphorylated peptide, Ace-Gly-Ser-pSer-Ser-Nme, and compare the results to each other and to experimental observables from an NMR experiment. The first major conclusion is that explicit water models (TIP3P, TIP4P and SPC/E) and a Generalized Born implicit solvent model provide reasonable agreement with the experimental observables, given appropriate partial charges for the phosphate group. The Generalized Born results, however, show greater hydrogen bonding propensity than the explicit solvent results. Distance dependent dielectric treatments perform poorly. The second major conclusion is that many ensemble-averaged properties obtained for the phosphopeptide in the -1 and -2 charge states are strikingly similar; the -1 species has a slightly higher propensity to form internal hydrogen bonds. All of the results can be rationalized by quantifying the strength of the P-O/H-N hydrogen bond, which depends on a sensitive balance between strongly favorable charge/dipole and dipole/dipole interactions and strongly unfavorable desolvation.

Sequence, structure and energetic determinants of phosphopeptide selectivity of SH2 domains

Here, we present an approach for the prediction of binding preferences of members of a large protein family for which structural information for a number of family members bound to a substrate is available. The approach involves a number of steps. First, an accurate multiple alignment of sequences of all members of a protein family is constructed on the basis of a multiple structural superposition of family members with known structure. Second, the methods of continuum electrostatics are used to characterize the energetic contribution of each residue in a protein to the binding of its substrate. Residues that make a significant contribution are mapped onto the protein sequence and are used to define a "binding site signature" for the complex being considered. Third, sequences whose structures have not been determined are checked to see if they have binding-site signatures similar to one of the known complexes. Predictions of binding affinity to a given substrate are based on similarities in binding-site signature. An important component of the approach is the introduction of a context-specific substitution matrix suitable for comparison of binding-site residues. The methods are applied to the prediction of phosphopeptide selectivity of SH2 domains. To this end, the energetic roles of all protein residues in 17 different complexes of SH2 domains with their cognate targets are analyzed. The total number of residues that make significant contributions to binding is found to vary from nine to 19 in different complexes. These energetically important residues are found to contribute to binding through a variety of mechanisms, involving both electrostatic and hydrophobic interactions. Binding-site signatures are found to involve residues in different positions in SH2 sequences, some of them as far as 9A away from a bound peptide. Surprisingly, similarities in the signatures of different domains do not correlate with whole-domain sequence identities unless the latter is greater than 50%. An extensive comparison with the optimal binding motifs determined by peptide library experiments, as well as other experimental data indicate that the similarity in binding preferences of different SH2 domains can be deduced on the basis of their binding-site signatures. The analysis provides a rationale for the empirically derived classification of SH2 domains described by Songyang & Cantley, in that proteins in the same group are found to have similar residues at positions important for binding. Confident predictions of binding preference can be made for about 85% of SH2 domain sequences found in SWISSPROT. The approach described in this work is quite general and can, in principle, be used to analyze binding preferences of members of large protein families for which structural information for a number of family members is available. It also offers a strategy for predicting cross-reactivity of compounds designed to bind to a particular target, for example in structure-based drug design.

Prediction of secondary ionization of the phosphate group in phosphotyrosine peptides

A computational approach, based on a continuum molecular electrostatics model, for the calculation of the pK(a) values of secondary ionization of the phosphate group in phenyl phosphate derivatives is described. The method uses the ESP atomic charges of the mono-anionic and di-anionic forms of the ionizable phosphate group, computed with the use of the density functional method, and applies a new concept of the model group, being the reference state for the pK(a) calculations. Both conformational flexibility and tautomeric degrees of freedom are taken into account in the calculations. The method was parameterized using experimentally available pK(a) values of four derivatives of phenyl phosphates, and phosphotyrosine. Subsequently this parameterization was used to predict pK(a) of the phosphate group in a short peptide Gly-Gly-Tyr(P)-Ala, and in a longer peptide consisting of 12 residues, the latter in water, and in a complex with a protein-phospholipase. The agreement between the computed and the experimental pK(a) values is better than +/-0.3 pH units for the optimized solute dielectric constant of 11-13. This approach is promising and its extension to other phospho-amino acids is in progress.

Hierarchy of simulation models in predicting molecular recognition mechanisms from the binding energy landscapes: structural analysis of the peptide complexes with SH2 domains

Computer simulations using the simplified energy function and simulated tempering dynamics have accurately determined the native structure of the pYVPML, SVLpYTAVQPNE, and SPGEpYVNIEF peptides in the complexes with SH2 domains. Structural and equilibrium aspects of the peptide binding with SH2 domains have been studied by generating temperature-dependent binding free energy landscapes. Once some native peptide-SH2 domain contacts are constrained, the underlying binding free energy profile has the funnel-like shape that leads to a rapid and consistent acquisition of the native structure. The dominant native topology of the peptide-SH2 domain complexes represents an extended peptide conformation with strong specific interactions in the phosphotyrosine pocket and hydrophobic interactions of the peptide residues C-terminal to the pTyr group. The topological features of the peptide-protein interface are primarily determined by the thermodynamically stable phosphotyrosyl group. A diversity of structurally different binding orientations has been observed for the amino-terminal residues to the phosphotyrosine. The dominant native topology for the peptide residues carboxy-terminal to the phosphotyrosine is tolerant to flexibility in this region of the peptide-SH2 domain interface observed in equilibrium simulations. The energy landscape analysis has revealed a broad, entropically favorable topology of the native binding mode for the bound peptides, which is robust to structural perturbations. This could provide an additional positive mechanism underlying tolerance of the SH2 domains to hydrophobic conservative substitutions in the peptide specificity region.

Exploring the dynamic information content of a protein NMR structure: comparison of a molecular dynamics simulation with the NMR and X-ray structures of Escherichia coli ribonuclease HI

The multiconformer nature of solution nuclear magnetic resonance (NMR) structures of proteins results from the effects of intramolecular dynamics, spin diffusion and an uneven distribution of structural restraints throughout the molecule. A delineation of the former from the latter two contributions is attempted in this work for an ensemble of 15 NMR structures of the protein Escherichia coli ribonuclease HI (RNase HI). Exploration of the dynamic information content of the NMR ensemble is carried out through correlation with data from two crystal structures and a 1.7-ns molecular dynamics (MD) trajectory of RNase HI in explicit solvent. Assessment of the consistency of the crystal and mean MD structures with nuclear Overhauser effect (NOE) data showed that the NMR ensemble is overall more compatible with the high-resolution (1.48 A) crystal structure than with either the lower-resolution (2.05 A) crystal structure or the MD simulation. Furthermore, the NMR ensemble is found to span more conformational space than the MD simulation for both the backbone and the sidechains of RNase HI. Nonetheless, the backbone conformational variability of both the NMR ensemble and the simulation is especially consistent with NMR relaxation measurements of two loop regions that are putative sites of substrate recognition. Plausible side-chain dynamic information is extracted from the NMR ensemble on the basis of (i) rotamericity and syn-pentane character of variable torsion angles, (ii) comparison of the magnitude of atomic mean-square fluctuations (msf) with those deduced from crystallographic thermal factors, and (iii) comparison of torsion angle conformational behavior in the NMR ensemble and the simulation. Several heterogeneous torsion angles, while adopting non-rotameric/syn-pentane conformations in the NMR ensemble, exist in a unique conformation in the simulation and display low X-ray thermal factors. These torsions are identified as sites whose variability is likely to be an artifact of the NMR structure determination procedure. A number of other torsions show a close correspondence between the conformations sampled in the NMR and MD ensembles, as well as significant correlations among crystallographic thermal factors and atomic msf calculated from the NMR ensemble and the simulation. These results indicate that a significant amount of dynamic information is contained in the NMR ensemble. The relevance of the present findings for the biological function of RNase HI, protein recognition studies, and previous investigations of the motional content of protein NMR structures are discussed.