Dynamics may significantly influence the estimation of interatomic distances in biomolecular X-ray structures

In silico approach to explore the disruption in the molecular mechanism of human hyaluronidase 1 by mutant E268K that directs Natowicz syndrome

Natowicz syndrome (mucopolysaccharidoses type 9) is a lysosomal storage disorder caused by deficient or defective human hyaluronidase 1. The disorder is not well studied at the molecular level. Therefore, a new in silico approach was proposed to study the molecular basis on which one clinically observed mutation, Glu268Lys, results in a defective enzyme. The native and mutant structures were subjected to comparative analyses using a conformational sampling approach for geometrical variables viz, RMSF, RMSD, and Ramachandran plot. In addition, the strength of a Cys207-Cys221 disulfide bond and electrostatic interaction between Arg265 and Asp206 were studied, as they are known to be involved in the catalytic activity of the enzyme. Native and mutant E268K showed statistically significant variations with p < 0.05 in RMSD, Ramachandran plot, strengths of disulfide bond, and electrostatic interactions. Further, single model analysis showed variations between native and mutant structures in terms of intra-protein interactions, hydrogen bond dilution, secondary structure, and dihedral angles. Docking analysis predicted the mutant to have a less favorable substrate binding energy compared to the native protein. Additionally, steered MD analysis indicated that the substrate should have more affinity to the native than mutant enzymes. The observed changes theoretically explain the less favorable binding energy of substrate towards mutant E268K, thereby providing a structural basis for its reduced catalytic activity. Hence, our study provides a basis for understanding the disruption in the molecular mechanism of human hyaluronidase 1 by mutation E268K, which may prove useful for the development of synthetic chaperones as a treatment option for Natowicz syndrome.

Ensemble-based evaluation for protein structure models

Motivation: Comparing protein tertiary structures is a fundamental procedure in structural biology and protein bioinformatics. Structure comparison is important particularly for evaluating computational protein structure models. Most of the model structure evaluation methods perform rigid body superimposition of a structure model to its crystal structure and measure the difference of the corresponding residue or atom positions between them. However, these methods neglect intrinsic flexibility of proteins by treating the native structure as a rigid molecule. Because different parts of proteins have different levels of flexibility, for example, exposed loop regions are usually more flexible than the core region of a protein structure, disagreement of a model to the native needs to be evaluated differently depending on the flexibility of residues in a protein.

Results: We propose a score named FlexScore for comparing protein structures that consider flexibility of each residue in the native state of proteins. Flexibility information may be extracted from experiments such as NMR or molecular dynamics simulation. FlexScore considers an ensemble of conformations of a protein described as a multivariate Gaussian distribution of atomic displacements and compares a query computational model with the ensemble. We compare FlexScore with other commonly used structure similarity scores over various examples. FlexScore agrees with experts’ intuitive assessment of computational models and provides information of practical usefulness of models.

Availability and implementation:https://bitbucket.org/mjamroz/flexscore

Contact:dkihara@purdue.edu

Supplementary information:Supplementary data are available at Bioinformatics online.

Measuring and modeling diffuse scattering in protein X-ray crystallography

X-ray diffraction has the potential to provide rich information about the structural dynamics of macromolecules. To realize this potential, both Bragg scattering, which is currently used to derive macromolecular structures, and diffuse scattering, which reports on correlations in charge density variations, must be measured. Until now, measurement of diffuse scattering from protein crystals has been scarce because of the extra effort of collecting diffuse data. Here, we present 3D measurements of diffuse intensity collected from crystals of the enzymes cyclophilin A and trypsin. The measurements were obtained from the same X-ray diffraction images as the Bragg data, using best practices for standard data collection. To model the underlying dynamics in a practical way that could be used during structure refinement, we tested translation-libration-screw (TLS), liquid-like motions (LLM), and coarse-grained normal-modes (NM) models of protein motions. The LLM model provides a global picture of motions and was refined against the diffuse data, whereas the TLS and NM models provide more detailed and distinct descriptions of atom displacements, and only used information from the Bragg data. Whereas different TLS groupings yielded similar Bragg intensities, they yielded different diffuse intensities, none of which agreed well with the data. In contrast, both the LLM and NM models agreed substantially with the diffuse data. These results demonstrate a realistic path to increase the number of diffuse datasets available to the wider biosciences community and indicate that dynamics-inspired NM structural models can simultaneously agree with both Bragg and diffuse scattering.

X-ray refinement significantly underestimates the level of microscopic heterogeneity in biomolecular crystals

Biomolecular X-ray structures typically provide a static, time- and ensemble-averaged view of molecular ensembles in crystals. In the absence of rigid-body motions and lattice defects, B-factors are thought to accurately reflect the structural heterogeneity of such ensembles. In order to study the effects of averaging on B-factors, we employ molecular dynamics simulations to controllably manipulate microscopic heterogeneity of a crystal containing 216 copies of villin headpiece. Using average structure factors derived from simulation, we analyse how well this heterogeneity is captured by high-resolution molecular-replacement-based model refinement. We find that both isotropic and anisotropic refined B-factors often significantly deviate from their actual values known from simulation: even at high 1.0 Å resolution and Rfree of 5.9%, B-factors of some well-resolved atoms underestimate their actual values even sixfold. Our results suggest that conformational averaging and inadequate treatment of correlated motion considerably influence estimation of microscopic heterogeneity via B-factors, and invite caution in their interpretation.

Predicting X-ray diffuse scattering from translation-libration-screw structural ensembles

Identifying the intramolecular motions of proteins and nucleic acids is a major challenge in macromolecular X-ray crystallography. Because Bragg diffraction describes the average positional distribution of crystalline atoms with imperfect precision, the resulting electron density can be compatible with multiple models of motion. Diffuse X-ray scattering can reduce this degeneracy by reporting on correlated atomic displacements. Although recent technological advances are increasing the potential to accurately measure diffuse scattering, computational modeling and validation tools are still needed to quantify the agreement between experimental data and different parameterizations of crystalline disorder. A new tool, phenix.diffuse, addresses this need by employing Guinier's equation to calculate diffuse scattering from Protein Data Bank (PDB)-formatted structural ensembles. As an example case, phenix.diffuse is applied to translation-libration-screw (TLS) refinement, which models rigid-body displacement for segments of the macromolecule. To enable the calculation of diffuse scattering from TLS-refined structures, phenix.tls_as_xyz builds multi-model PDB files that sample the underlying T, L and S tensors. In the glycerophosphodiesterase GpdQ, alternative TLS-group partitioning and different motional correlations between groups yield markedly dissimilar diffuse scattering maps with distinct implications for molecular mechanism and allostery. These methods demonstrate how, in principle, X-ray diffuse scattering could extend macromolecular structural refinement, validation and analysis.

E pluribus unum, no more: from one crystal, many conformations

Several distinct computational approaches have recently been implemented to represent conformational heterogeneity from X-ray crystallography datasets that are averaged in time and space. As these modeling methods mature, newly discovered alternative conformations are being used to derive functional protein mechanisms. Room temperature X-ray data collection is emerging as a key variable for sampling functionally relevant conformations also observed in solution studies. Although concerns about radiation damage are warranted with higher temperature data collection, 'diffract and destroy' strategies on X-ray free electron lasers may permit radiation damage-free data collection. X-ray crystallography need not be confined to 'static unique snapshots'; these experimental and computational advances are revealing how the many conformations populated within a single crystal are used in biological mechanisms.

On the Contribution of Linear Correlations to Quasi-harmonic Conformational Entropy in Proteins

We study the contribution of linear, pairwise atom-positional correlations (covariances) to absolute and relative conformational entropy as calculated by quasi-harmonic analysis of molecular dynamics (MD) trajectories (SQH and ΔSQH). By analyzing a total of 25 μs of MD simulations of ubiquitin and six of its binding partners in bound and unbound states, and 2.4 μs of simulations of eight different proteins in phosphorylated and unphosphorylated states, we show that ΔSQH represents a remarkably constant fraction of a quasi-harmonic entropy change obtained if one ignores the contribution of covariance terms and uses mass-weighted atom-positional variances only (ΔSVAR). In other words, the relative contribution of linear correlations to conformational entropy change for different proteins and in different biomolecular processes appears to be largely constant. Based on this, we establish an empirical relationship between relative quasi-harmonic conformational entropy and changes in crystallographic B-factors induced by different processes, and we use it to estimate conformational-entropic contribution to the free energy of binding for a large set of protein complexes based on their X-ray structures. Our results suggest a simple way for relating other types of dynamical observables with conformational entropy in the absence of information on correlated motions, such as in the case of NMR order parameters.