Side-chain Conformational Entropy Research Articles

Dynamical Manifestations of Supercooling in Amyloid Hydration.

The effect of extreme temperature on amyloidogenic species remains sparsely explored. In a recent study (J. Phys. Chem. Lett., 2019, 10, (10)), we employed exhaustive molecular dynamics simulations to explore the cold thermal response of a putative small amyloid oligomer and to elicit the role of solvent modulation. Herein, we investigate the dynamical response of the hydration waters of the oligomer within the supercooled states. Using NMR-based formalism, we delineate the entropic response in terms of the side-chain conformational entropy that corroborates the weakening of the hydrophobic core with lowering of temperature. The translational dynamics of the protein and hydration waters reveal the coupling of protein dynamical fluctuations with solvent dynamics under supercooled conditions. Probing the translational motion as a space-time correlation indicates glassy dynamics exhibited by hydration waters in the supercooled regime. Caging of the water molecules with lowering of temperature and the resultant hopping dynamics are reflected in the longer β-relaxation timescales of translational motion. Furthermore, we utilized mode-coupling theory (MCT) and derived the ideal glass transition temperature from translational and rotational dynamics, around ∼196 and 209 K, respectively. Interestingly, rotational motion in the supercooled regime deviates from the MCT law, exhibits Arrhenius motion, and marks a fragile-to-strong crossover at 227 K. The low-frequency vibrational modes also coincide with the dynamical transition. This exposition lends dynamical insights into the hydration coupling of an amyloid aggregate under cryogenic conditions.

How Much Entropy Is Contained in NMR Relaxation Parameters?

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

Flexible CDOCKER: Hybrid Searching Algorithm and Scoring Function with Side Chain Conformational Entropy.

The binding of small-molecule ligands to protein or nucleic acid targets is important to numerous biological processes. Accurate prediction of the binding modes between a ligand and a macromolecule is of fundamental importance in structure-based structure-function exploration. When multiple ligands with different sizes are docked to a target receptor, it is reasonable to assume that the residues in the binding pocket may adopt alternative conformations upon interacting with the different ligands. In addition, it has been suggested that the entropic contribution to binding can be important. However, only a few attempts to include the side chain conformational entropy upon binding within the application of flexible receptor docking methodology exist. Here, we propose a new physics-based scoring function that includes both enthalpic and entropic contributions upon binding by considering the conformational variability of the flexible side chains within the ensemble of docked poses. We also describe a novel hybrid searching algorithm that combines both molecular dynamics (MD)-based simulated annealing and genetic algorithm crossovers to address the enhanced sampling of the increased search space. We demonstrate improved accuracy in flexible cross-docking experiments compared with rigid cross-docking. We test our developments by considering five protein targets, thrombin, dihydrofolate reductase(DHFR), T4 L99A, T4 L99A/M102Q, and PDE10A, which belong to different enzyme classes with different binding pocket environments, as a representative set of diverse ligands and receptors. Each target contains dozens of different ligands bound to the same binding pocket. We also demonstrate that this flexible docking algorithm may be applicable to RNA docking with a representative riboswitch example. Our findings show significant improvements in top ranking accuracy across this set, with the largest improvement relative to rigid, 23.64%, occurring for ligands binding to DHFR. We then evaluate the ability to identify lead compounds among a large chemical space for the proposed flexible receptor docking algorithm using a subset of the DUD-E containing receptor targets MCR, GCR, and ANDR. We demonstrate that our new algorithms show improved performance in modeling flexible binding site residues compared to DOCK. Finally, we select the T4 L99A and T4 L99A/M102Q decoy sets, containing dozens of binders and experimentally validated nonbinders, to test our approach in distinguishing binders from nonbinders. We illustrate that our new algorithms for searching and scoring have superior performance to rigid receptor CDOCKER as well as AutoDock Vina. Finally, we suggest that flexible CDOCKER is sufficiently fast to be utilized in high-throughput docking screens in the context of hierarchical approaches.

Correlated Response of Protein Side-Chain Fluctuations and Conformational Entropy to Ligand Binding.

The heterogeneous fast side-chain dynamics of proteins plays crucial roles in molecular recognition and binding. Site-specific NMR experiments quantify these motions by measuring the model-free order parameter (Oaxis2) on a scale of 0 (most flexible) to 1 (least flexible) for each methyl-containing residue of proteins. Here, we have examined ligand-induced variations in the fast side-chain dynamics and conformational entropy of calmodulin (CaM) using five different CaM-peptide complexes. Oaxis2 of CaM in the ligand-free (Oaxis,U2) and ligand-bound (Oaxis,B2) states are calculated from molecular dynamics trajectories and conformational energy surfaces obtained using the adaptive biasing force (ABF) method. ΔOaxis2 = Oaxis,B2 - Oaxis,U2 follows a Gaussian-like unimodal distribution whose second moment is a potential indicator of the binding affinity of these complexes. The probability for the binding-induced Oaxis,U2 → Oaxis,B2 transition decreases with increasing magnitude of ΔOaxis2, indicating that large flexibility changes are improbable for side chains of CaM after ligand binding. A linear correlation established between ΔOaxis2 and the conformational entropy change of the protein makes possible the determination of the conformational entropy of binding of protein-ligand complexes. The results not only underscore the functional importance of fast side-chain fluctuations but also highlight key motional and thermodynamic correlates of protein-ligand binding.

TMPfold, a Computational Method for Assessment of Stability of Transmembrane α-Helical Assemblies

A new physics-based computational method TMPfold has been developed and implemented in a public web server for assessment of stability of TM α-helical complexes (accessible at https://opm.phar.umich.edu/tmpfold_server). Using the available 3D structure of an arbitrary TM α-bundle formed by a single or multiple subunits as input, the method calculates the free energies of subunit-subunit and helix-helix association (ΔGasc), identifies stable two-helical units that can initiate folding, and predict the plausible folding pathways for multi-pass transmembrane (TM) proteins. The free energy components include van der Waals, hydrogen bonding and dipole interactions, side-chain conformational entropy, and solvation energy in the anisotropic lipid environment. The method was verified using the experimental ΔGasc values for 36 TM complexes, including dimers of 10 glycophorin A mutants. TMPfold was applied for evaluation of TM helix association energies in 554 PDB structures of 85 seven-helical TM proteins and identification of their stable two-helical folding intermediates. The proposed tentative paths of co-translational helix assembly of several polytopic proteins were qualitatively consistent with experimental studies of their folding. The assessment of free energy changes caused by mutations in TM helices demonstrated the good correlation between experimental ΔΔGfolding and calculated ΔΔGasc values for 42 mutants of bacteriorhodopsin (R2 of 0.41, RMSE of 0.81 kcal/mol) and 25 mutants of rhomboid protease (R2 of 0.43, RMSE of 0.40 kcal/mol).

Cost function network-based design of protein-protein interactions: predicting changes in binding affinity.

Accurate and economic methods to predict change in protein binding free energy upon mutation are imperative to accelerate the design of proteins for a wide range of applications. Free energy is defined by enthalpic and entropic contributions. Following the recent progresses of Artificial Intelligence-based algorithms for guaranteed NP-hard energy optimization and partition function computation, it becomes possible to quickly compute minimum energy conformations and to reliably estimate the entropic contribution of side-chains in the change of free energy of large protein interfaces. Using guaranteed Cost Function Network algorithms, Rosetta energy functions and Dunbrack's rotamer library, we developed and assessed EasyE and JayZ, two methods for binding affinity estimation that ignore or include conformational entropic contributions on a large benchmark of binding affinity experimental measures. If both approaches outperform most established tools, we observe that side-chain conformational entropy brings little or no improvement on most systems but becomes crucial in some rare cases. as open-source Python/C++ code at sourcesup.renater.fr/projects/easy-jayz. Supplementary data are available at Bioinformatics online.

Protein crystal lattices are dynamic assemblies: the role of conformational entropy in the protein condensed phase.

Until recently, the occurrence of conformational entropy in protein crystal contacts was considered to be a very unlikely event. A study based on the most accurately refined protein structures demonstrated that side-chain conformational entropy and static disorder might be common in protein crystal lattices. The present investigation uses structures refined using ensemble refinement to show that although paradoxical, conformational entropy is likely to be the major factor in the emergence and integrity of the protein condensed phase. This study reveals that the role of shape entropy and local entropic forces expands beyond the onset of crystallization. For the first time, the complete pattern of intermolecular interactions by protein atoms in crystal lattices is presented, which shows that van der Waals interactions dominate in crystal formation.

V67L Mutation Fills an Internal Cavity To Stabilize RecA Mtu Intein.

Inteins mediate protein splicing, which has found extensive applications in protein science and biotechnology. In the Mycobacterium tuberculosis RecA mini-mini intein (ΔΔIhh), a single valine to leucine substitution at position 67 (V67L) dramatically increases intein stability and activity. However, crystal structures show that the V67L mutation causes minimal structural rearrangements, with a root-mean-square deviation of 0.2 Å between ΔΔIhh-V67 and ΔΔIhh-L67. Thus, the structural mechanisms for V67L stabilization and activation remain poorly understood. In this study, we used intrinsic tryptophan fluorescence, high-pressure nuclear magnetic resonance (NMR), and molecular dynamics (MD) simulations to probe the structural basis of V67L stabilization of the intein fold. Guanidine hydrochloride denaturation monitored by fluorescence yielded free energy changes (ΔGf°) of -4.4 and -6.9 kcal mol-1 for ΔΔIhh-V67 and ΔΔIhh-L67, respectively. High-pressure NMR showed that ΔΔIhh-L67 is more resistant to pressure-induced unfolding than ΔΔIhh-V67 is. The change in the volume of folding (ΔVf) was significantly larger for V67 (71 ± 2 mL mol-1) than for L67 (58 ± 3 mL mol-1) inteins. The measured difference in ΔVf (13 ± 3 mL mol-1) roughly corresponds to the volume of the additional methylene group for Leu, supporting the notion that the V67L mutation fills a nearby cavity to enhance intein stability. In addition, we performed MD simulations to show that V67L decreases side chain dynamics and conformational entropy at the active site. It is plausible that changes in cavities in V67L can also mediate allosteric effects to change active site dynamics and enhance intein activity.

Direct Determination of Site-Specific Noncovalent Interaction Strengths of Proteins from NMR-Derived Fast Side Chain Motional Parameters.

A novel approach to accurately determine residue-specific noncovalent interaction strengths (ξ) of proteins from NMR-measured fast side chain motional parameters (Oaxis2) is presented. By probing the environmental sensitivity of side chain conformational energy surfaces of individual residues of a diverse set of proteins, the microscopic connections between ξ, Oaxis2, conformational entropy (Sconf), conformational barriers, and rotamer stabilities established here are found to be universal among proteins. The results reveal that side chain flexibility and conformational entropy of each residue decrease with increasing ξ and that for each residue type there exists a critical range of ξ, determined primarily by the mean side chain conformational barriers, within which flexibility of any residue can be reversibly tuned from highly flexible (with Oaxis2 ∼ 0) to highly restricted (with Oaxis2 ∼ 1) by increasing ξ by ∼3 kcal/mol. Beyond this critical range of ξ, both side chain flexibility and conformational entropy are insensitive to ξ. The interrelationships between conformational dynamics, conformational entropy, and noncovalent interactions of protein side chains established here open up new avenues to probe perturbation-induced (for example, ligand-binding, temperature, pressure) changes in fast side chain dynamics and thermodynamics of proteins by comparing their conformational energy surfaces in the native and perturbed states.

Proteome-Wide Modeling of Transmembrane Alpha-Helical Homodimers by TMDOCK

A novel energy-based method, TMDOCK, has been developed for ab initio modeling of 3D structures of parallel homodimers in membranes. Instead of exploring the entire conformational space, the method employs a fast template-driven global energy optimization procedure that combines the knowledge of geometrically feasible packing arrangements and local energy minimization with a novel force field. Ranking and selection of optimal dimerization modes is based on the calculated free energy of α-helix association (ΔGassoc) which includes van der Waals, hydrogen bonding and dipole-dipole interactions between helices, side chain conformational entropy, and solvation energy in the anisotropic lipid environment. The fast version of the TMDOCK method is available through the web server (http://membranome.org/tm_server.php).TMDOCK successfully reproduced 26 experimental dimeric structures formed by transmembrane (TM) α-helices of 21 single-pass membrane proteins (including 4 mutants) with Cα atom r.m.s.d. from 1.0 to 3.3 A. Additional testing demonstrated consistency of calculated dimer structures with published TOXCAT, mutagenesis, or other experimental data for more than 80 bitopic proteins. Subsequent application of the method to 6041 bitopic proteins from six proteomes included in the Membranome database (membranome.org) shows that ∼70% of the proteins tend to form stable dimers with ΔGassoc<-3 kcal/mol. Results of modeling indicate three different types of dimerization behavior of TM α-helices. A unique dimerization mode is usually observed for TM domains carrying a single GxxxG-like motif, interhelical disulfide bridges, or polar residues in the middle of a helix. Proteins with several GxxxG-like motifs usually have a few dimerization modes with similar energies. Proteins with Phe-rich sequences often show multiple helix association modes. The preferred modes of dimerization are frequently evolutionarily conserved (e.g. in cadherin, HLA histocompatibility antigen, receptor tyrosine kinase, and cytochrome P450 families), but they can also change even after a single mutation.

TMDOCK: An Energy-Based Method for Modeling α-Helical Dimers in Membranes

TMDOCK is a novel computational method for the modeling of parallel homodimers formed by transmembrane (TM) α-helices. Three-dimensional (3D) models of dimers are generated by threading a target amino acid sequence through several structural templates, followed by local energy minimization. This is the first method that identifies helix dimerization modes and ranks them based on the calculated free energy of α-helix association. Free energy components include van der Waals, hydrogen bonding, and dipole interactions; side-chain conformational entropy; and solvation energy in the anisotropic lipid environment. TMDOCK reproduced 26 experimental dimeric structures formed by TM α-helices of 21 single-pass membrane proteins (including 4 mutants) with Cα atom rmsd from 1.0 to 3.3Å. Assessment of dimerization heterogeneity of these TM domains demonstrated that 7 of them have a unique dimer structure, 12 have at least 2 alternative conformations, and 2 have a large number of different association modes. All unique experimental structures of proteins from the first group and eight structures from the second group were reproduced in computations as top-ranked models. A fast version of the method is available through the web server (http://membranome.org/tm_server.php).

Changes in conformational dynamics of basic side chains upon protein-DNA association.

Basic side chains play major roles in recognition of nucleic acids by proteins. However, dynamic properties of these positively charged side chains are not well understood. In this work, we studied changes in conformational dynamics of basic side chains upon protein–DNA association for the zinc-finger protein Egr-1. By nuclear magnetic resonance (NMR) spectroscopy, we characterized the dynamics of all side-chain cationic groups in the free protein and in the complex with target DNA. Our NMR order parameters indicate that the arginine guanidino groups interacting with DNA bases are strongly immobilized, forming rigid interfaces. Despite the strong short-range electrostatic interactions, the majority of the basic side chains interacting with the DNA phosphates exhibited high mobility, forming dynamic interfaces. In particular, the lysine side-chain amino groups exhibited only small changes in the order parameters upon DNA-binding. We found a similar trend in the molecular dynamics (MD) simulations for the free Egr-1 and the Egr-1–DNA complex. Using the MD trajectories, we also analyzed side-chain conformational entropy. The interfacial arginine side chains exhibited substantial entropic loss upon binding to DNA, whereas the interfacial lysine side chains showed relatively small changes in conformational entropy. These data illustrate different dynamic characteristics of the interfacial arginine and lysine side chains.

An integrative structure-based framework for predicting biological effects mediated by antipeptide antibodies

A general framework is presented for predicting quantitative biological effects mediated by antipeptide antibodies, primarily on the basis of antigen structure (possibly featuring intrinsic disorder) analyzed to estimate epitope–paratope binding affinities, which in turn is considered within the context of dose–response relationships as regards antibody concentration. This is illustrated mainly using an approach based on protein structural energetics, whereby expected amounts of solvent-accessible surface area buried upon epitope–paratope binding are related to the corresponding binding affinity, which is estimated from putative B-cell epitope structure with implicit treatment of paratope structure, for antipeptide antibodies either reacting with peptides or cross-reacting with cognate protein antigens. Key methods described are implemented in SAPPHIRE/SUITE (Structural-energetic Analysis Program for Predicting Humoral Immune Response Epitopes/SAPPHIRE User Interface Tool Ensemble; publicly accessible via http://freeshell.de/~badong/suite.htm). Representative results thus obtained are compared with published experimental data on binding affinities and quantitative biological effects, with special attention to loss of paratope sidechain conformational entropy (neglected in previous analyses) and in light of key in-vivo constraints on antigen-antibody binding affinity and antibody-mediated effects. Implications for further refinement of B-cell epitope prediction methods are discussed as regards envisioned biomedical applications including the development of prophylactic and therapeutic antibodies, peptide-based vaccines and immunodiagnostics.

Motion and Conformational Entropy in Protein Function: Creation of an NMR-Based Entropy Meter

Conformational entropy is a potentially important thermodynamic parameter contributing to protein function. Quantitative measures of conformational entropy are necessary for an understanding of its role but have been difficult to obtain. We have recently introduced empirical method that utilizes changes in conformational dynamics as a proxy for changes in conformational entropy. We have now used molecular dynamics simulations to probe the microscopic origins of the link between conformational dynamics and conformational entropy. Simulation of seven proteins gave an excellent correlation with measures of side-chain motion derived from NMR relaxation. The simulations show that the motion of methyl-bearing side-chains are sufficiently coupled to that of other side chains to serve as excellent reporters of the overall side-chain conformational entropy. These results tend to validate the use of experimentally accessible measures of methyl motion - the NMR-derived generalized order parameters - as a proxy from which to derive changes in protein conformational entropy due to a perturbation such as the binding of a ligand. A slightly modified weighting scheme to project the change in dynamics of experimental methyl dynamics into conformational entropy is presented. Originally based on data from the calmodulin system, we will describe experimental results from other systems that indicate that the “entropy meter” approach is both robust and general and that the involved conformational entropies are often large and cannot be ignored. Supported by the NIH and the Mathers Foundation.

Life at the border: adaptation of proteins to anisotropic membrane environment.

This review discusses main features of transmembrane (TM) proteins which distinguish them from water-soluble proteins and allow their adaptation to the anisotropic membrane environment. We overview the structural limitations on membrane protein architecture, spatial arrangement of proteins in membranes and their intrinsic hydrophobic thickness, co-translational and post-translational folding and insertion into lipid bilayers, topogenesis, high propensity to form oligomers, and large-scale conformational transitions during membrane insertion and transport function. Special attention is paid to the polarity of TM protein surfaces described by profiles of dipolarity/polarizability and hydrogen-bonding capacity parameters that match polarity of the lipid environment. Analysis of distributions of Trp resides on surfaces of TM proteins from different biological membranes indicates that interfacial membrane regions with preferential accumulation of Trp indole rings correspond to the outer part of the lipid acyl chain region-between double bonds and carbonyl groups of lipids. These "midpolar" regions are not always symmetric in proteins from natural membranes. We also examined the hydrophobic effect that drives insertion of proteins into lipid bilayer and different free energy contributions to TM protein stability, including attractive van der Waals forces and hydrogen bonds, side-chain conformational entropy, the hydrophobic mismatch, membrane deformations, and specific protein-lipid binding.

Hidden regularity and universal classification of fast side chain motions in proteins.

Proteins display characteristic dynamical signatures that appear to be universal across all proteins regardless of topology and size. Here, we systematically characterize the universal features of fast side chain motions in proteins by examining the conformational energy surfaces of individual residues obtained using enhanced sampling molecular dynamics simulation (618 free energy surfaces obtained from 0.94 μs MD simulation). The side chain conformational free energy surfaces obtained using the adaptive biasing force (ABF) method for a set of eight proteins with different molecular weights and secondary structures are used to determine the methyl axial NMR order parameters (O(axis)(2)), populations of side chain rotamer states (ρ), conformational entropies (S(conf)), probability fluxes, and activation energies for side chain inter-rotameric transitions. The free energy barriers separating side chain rotamer states range from 0.3 to 12 kcal/mol in all proteins and follow a trimodal distribution with an intense peak at ~5 kcal/mol and two shoulders at ~3 and ~7.5 kcal/mol, indicating that some barriers are more favored than others by proteins to maintain a balance between their conformational stability and flexibility. The origin and the influences of the trimodal barrier distribution on the distribution of O(axis)(2) and the side chain conformational entropy are discussed. A hierarchical grading of rotamer states based on the conformational free energy barriers, entropy, and probability flux reveals three distinct classes of side chains in proteins. A unique nonlinear correlation is established between O(axis)(2) and the side chain rotamer populations (ρ). The apparent universality in O(axis)(2) versus ρ correlation, trimodal barrier distribution, and distinct characteristics of three classes of side chains observed among all proteins indicates a hidden regularity (or commonality) in the dynamical heterogeneity of fast side chain motions in proteins.

Microscopic Insights into the NMR Relaxation-Based Protein Conformational Entropy Meter

Conformational entropy is a potentially important thermodynamic parameter contributing to protein function. Quantitative measures of conformational entropy are necessary for an understanding of its role but have been difficult to obtain. An empirical method that utilizes changes in conformational dynamics as a proxy for changes in conformational entropy has recently been introduced. Here we probe the microscopic origins of the link between conformational dynamics and conformational entropy using molecular dynamics simulations. Simulation of seven proteins gave an excellent correlation with measures of side-chain motion derived from NMR relaxation. The simulations show that the motion of methyl-bearing side chains are sufficiently coupled to that of other side chains to serve as excellent reporters of the overall side-chain conformational entropy. These results tend to validate the use of experimentally accessible measures of methyl motion--the NMR-derived generalized order parameters--as a proxy from which to derive changes in protein conformational entropy.

Three Entropic Classes of Side Chain in a Globular Protein

The relationship between the NMR methyl group axial order parameter and the side chain conformational entropy is investigated in inhibitor-bound and apo human HIV protease using molecular dynamics simulation. Three distinct entropic classes of methyl-bearing side chains, determined by the topological distance of the methyl group from the protein backbone (i.e., the number of χ-bonds between the Cα and the carbon of the CH3 group), are revealed by atomistic trajectory analyses performed in the local frame of reference of individual methyl probes. The results demonstrate that topologically equivalent methyl groups experience similar nonbonded microenvironments regardless of the type of residues to which they are attached. Similarly, methyl groups that belong to the same side chain but that are not topologically equivalent exhibit different thermodynamic and dynamic properties. The two-parameter classification (based upon entropy and methyl axial order parameter) of side chains described here permits improved estimates of the conformational entropies of proteins from NMR motional parameters.

Enhanced crystal packing due to solvent reorganization through reductive methylation of lysine residues in oxidoreductase from Streptococcus pneumoniae

Protein crystallization is in part driven by the changes in the entropy of the system, but opinions differ as to whether the solute (protein) or solvent (water) molecules make more of a contribution to the overall entropic change. Methylation of lysine residues in proteins has been used to enhance protein crystallization. We investigated using molecular dynamics simulations with explicit solvent molecules, the behavior of several native proteins and their methylated counterparts chosen from an earlier large-scale study. Methylated lysines are capable of making a variety of interactions including H-bonds with protein residues and solvent. We demonstrate that methylation on the lysine slightly increases its side chain conformational entropy by about 3.5 J mol(-1) K(-1). Analysis of the radial and spatial distributions of the water molecules around the methylated lysine surface in oxidoreductase from Streptococcus pneumoniae revealed a larger sphere of water molecules with low entropy, as compared with solvent associated with unmethylated lysine. If methylated lysine were to make interactions at the protein-protein interface, the low-entropy water molecules associated with methylated lysines would be released, resulting in a gain of entropy. We show that this gain more than compensates for the loss of protein entropy. Therefore, we propose that lysine methylation favors the formation of crystals through solvent entropic gain.

Protein Side-Chain Dynamics and Residual Conformational Entropy

Changes in residual conformational entropy of proteins can be significant components of the thermodynamics of folding and binding. Nuclear magnetic resonance (NMR) spin relaxation is the only experimental technique capable of probing local protein entropy, by inference from local internal conformational dynamics. To assess the validity of this approach, the picosecond-to-nanosecond dynamics of the arginine side-chain N(epsilon)-H(epsilon) bond vectors of Escherichia coli ribonuclease H (RNase H) were determined by NMR spin relaxation and compared to the mechanistic detail provided by molecular dynamics (MD) simulations. The results indicate that arginine N(epsilon) spin relaxation primarily reflects persistence of guanidinium salt bridges and correlates well with simulated side-chain conformational entropy. In particular cases, the simulations show that the aliphatic part of the arginine side chain can retain substantial disorder while the guanidinium group maintains its salt bridges; thus, the N(epsilon)-H(epsilon) bond-vector orientation is conserved and side-chain flexibility is concealed from N(epsilon) spin relaxation. The MD simulations and an analysis of a rotamer library suggest that dynamic decoupling of the terminal moiety from the remainder of the side chain occurs for all five amino acids with more than two side-chain dihedral angles (R, K, E, Q, and M). Dynamic decoupling thus may represent a general biophysical strategy for minimizing the entropic penalties of folding and binding.