Nathalie Reuter

WEBnm@: a web application for normal mode analyses of proteins

BackgroundNormal mode analysis (NMA) has become the method of choice to investigate the slowest motions in macromolecular systems. NMA is especially useful for large biomolecular assemblies, such as transmembrane channels or virus capsids. NMA relies on the hypothesis that the vibrational normal modes having the lowest frequencies (also named soft modes) describe the largest movements in a protein and are the ones that are functionally relevant.ResultsWe developed a web-based server to perform normal modes calculations and different types of analyses. Starting from a structure file provided by the user in the PDB format, the server calculates the normal modes and subsequently offers the user a series of automated calculations; normalized squared atomic displacements, vector field representation and animation of the first six vibrational modes. Each analysis is performed independently from the others and results can be visualized using only a web browser. No additional plug-in or software is required. For users who would like to analyze the results with their favorite software, raw results can also be downloaded. The application is available on http://www.bioinfo.no/tools/normalmodes. We present here the underlying theory, the application architecture and an illustration of its features using a large transmembrane protein as an example.ConclusionWe built an efficient and modular web application for normal mode analysis of proteins. Non specialists can easily and rapidly evaluate the degree of flexibility of multi-domain protein assemblies and characterize the large amplitude movements of their domains.

Principal component and normal mode analysis of proteins; a quantitative comparison using the GroEL subunit

Principal component analysis (PCA) and normal mode analysis (NMA) have emerged as two invaluable tools for studying conformational changes in proteins. To compare these approaches for studying protein dynamics, we have used a subunit of the GroEL chaperone, whose dynamics is well characterized. We first show that both PCA on trajectories from molecular dynamics (MD) simulations and NMA reveal a general dynamical behavior in agreement with what has previously been described for GroEL. We thus compare the reproducibility of PCA on independent MD runs and subsequently investigate the influence of the length of the MD simulations. We show that there is a relatively poor one‐to‐one correspondence between eigenvectors obtained from two independent runs and conclude that caution should be taken when analyzing principal components individually. We also observe that increasing the simulation length does not improve the agreement with the experimental structural difference. In fact, relatively short MD simulations are sufficient for this purpose. We observe a rapid convergence of the eigenvectors (after ca. 6 ns). Although there is not always a clear one‐to‐one correspondence, there is a qualitatively good agreement between the movements described by the first five modes obtained with the three different approaches; PCA, all‐atoms NMA, and coarse‐grained NMA. It is particularly interesting to relate this to the computational cost of the three methods. The results we obtain on the GroEL subunit contribute to the generalization of robust and reproducible strategies for the study of protein dynamics, using either NMA or PCA of trajectories from MD simulations. Proteins 2010.

Measuring and comparing structural fluctuation patterns in large protein datasets

MOTIVATION The function of a protein depends not only on its structure but also on its dynamics. This is at the basis of a large body of experimental and theoretical work on protein dynamics. Further insight into the dynamics-function relationship can be gained by studying the evolutionary divergence of protein motions. To investigate this, we need appropriate comparative dynamics methods. The most used dynamical similarity score is the correlation between the root mean square fluctuations (RMSF) of aligned residues. Despite its usefulness, RMSF is in general less evolutionarily conserved than the native structure. A fundamental issue is whether RMSF is not as conserved as structure because dynamics is less conserved or because RMSF is not the best property to use to study its conservation. RESULTS We performed a systematic assessment of several scores that quantify the (dis)similarity between protein fluctuation patterns. We show that the best scores perform as well as or better than structural dissimilarity, as assessed by their consistency with the SCOP classification. We conclude that to uncover the full extent of the evolutionary conservation of protein fluctuation patterns, it is important to measure the directions of fluctuations and their correlations between sites. CONTACT Nathalie.Reuter@mbi.uib.no SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics Online.

Structures of human proteinase 3 and neutrophil elastase – so similar yet so different

Proteinase 3 and neutrophil elastase are serine proteinases of the polymorphonuclear neutrophils, which are considered to have both similar localization and ligand specificity because of their high sequence similarity. However, recent studies indicate that they might have different and yet complementary physiologic roles. Specifically, proteinase 3 has intracellular specific protein substrates resulting in its involvement in the regulation of intracellular functions such as proliferation or apoptosis. It behaves as a peripheral membrane protein and its membrane expression is a risk factor in chronic inflammatory diseases. Moreover, in contrast to human neutrophil elastase, proteinase 3 is the preferred target antigen in Wegener’s granulomatosis, a particular type of vasculitis. We review the structural basis for the different ligand specificities and membrane binding mechanisms of both enzymes, as well as the putative anti‐neutrophil cytoplasm autoantibody epitopes on human neutrophil elastase 3. We also address the differences existing between murine and human enzymes, and their consequences with respect to the development of animal models for the study of human proteinase 3‐related pathologies. By integrating the functional and the structural data, we assemble many pieces of a complicated puzzle to provide a new perspective on the structure–function relationship of human proteinase 3 and its interaction with membrane, partner proteins or cleavable substrates. Hence, precise and meticulous structural studies are essential tools for the rational design of specific proteinase 3 substrates or competitive ligands that modulate its activities.

Biochemical and cellular analysis of Ogden syndrome reveals downstream Nt-acetylation defects

The X-linked lethal Ogden syndrome was the first reported human genetic disorder associated with a mutation in an N-terminal acetyltransferase (NAT) gene. The affected males harbor an Ser37Pro (S37P) mutation in the gene encoding Naa10, the catalytic subunit of NatA, the major human NAT involved in the co-translational acetylation of proteins. Structural models and molecular dynamics simulations of the human NatA and its S37P mutant highlight differences in regions involved in catalysis and at the interface between Naa10 and the auxiliary subunit hNaa15. Biochemical data further demonstrate a reduced catalytic capacity and an impaired interaction between hNaa10 S37P and Naa15 as well as Naa50 (NatE), another interactor of the NatA complex. N-Terminal acetylome analyses revealed a decreased acetylation of a subset of NatA and NatE substrates in Ogden syndrome cells, supporting the genetic findings and our hypothesis regarding reduced Nt-acetylation of a subset of NatA/NatE-type substrates as one etiology for Ogden syndrome. Furthermore, Ogden syndrome fibroblasts display abnormal cell migration and proliferation capacity, possibly linked to a perturbed retinoblastoma pathway. N-Terminal acetylation clearly plays a role in Ogden syndrome, thus revealing the in vivo importance of N-terminal acetylation in human physiology and disease.

Two-Level Approach to Efficient Visualization of Protein Dynamics

Proteins are highly flexible and large amplitude deformations of their structure, also called slow dynamics, are often decisive to their function. We present a two-level rendering approach that enables visualization of slow dynamics of large protein assemblies. Our approach is aligned with a hierarchical model of large scale molecules. Instead of constantly updating positions of large amounts of atoms, we update the position and rotation of residues, i.e., higher level building blocks of a protein. Residues are represented by one vertex only indicating its position and additional information defining the rotation. The atoms in the residues are generated on-the-fly on the GPU, exploiting the new graphics hardware geometry shader capabilities. Moreover, we represent the atoms by billboards instead of tessellated spheres. Our representation is then significantly faster and pixel precise. We demonstrate the usefulness of our new approach in the context of our collaborative bioinformatics project.

Computational prediction of the binding site of proteinase 3 to the plasma membrane

Proteinase 3 (PR3) is a neutrophil‐derived serine proteinase localized within cytoplasmic granules which can be released upon activation. PR3 is exposed at the neutrophil plasma membrane where it can mediate proinflammatory effects. Moreover, PR3 membrane expression is of special relevance in patients with Wegeners granulomatosis, a systemic vasculitis presenting anticytoplasmic neutrophil autoantibodies (ANCA) against PR3, which can bind to PR3 expressed at the surface of neutrophils and amplify their activation state. Therefore, it is of special relevance to unravel the molecular mechanisms governing its association with the membrane to be able to modulate it. To this end, we performed molecular dynamics (MD) simulations of PR3 with the implicit membrane model IMM1‐GC to identify its interfacial binding site (IBS). Both the energies and structures resulting from the MD suggest that PR3 associates strongly with anionic membranes. We observe a unique IBS consisting of five basic (R177, R186A, R186B, K187, R222) and six hydrophobic (F165, F166, F224, L223, F184, W218) amino acids. The basic residues provide the driving force to orient PR3 at the membrane surface, so that the hydrophobic residues can anchor into the hydrocarbon region. Energy decomposition and in silico mutations show that only a few residues account for the membrane association. Similar calculations with HNE suggest a different membrane‐binding mechanism. Our results agree with previous experimental observations and this work predicts, for the first time, the structural determinants of the binding of PR3 to membranes. Proteins 2008.

Evolution of oligomeric state through allosteric pathways that mimic ligand binding.

Introduction Evolution and design of protein complexes are frequently viewed through the lens of amino acid mutations at protein interfaces, but we showed previously that residues distant from interfaces are also commonly involved in the evolution of alternative quaternary structures. We hypothesized that in these protein families, the difference in oligomeric state is due to a change in intersubunit geometry. The indirect mutations would act by changing protein conformation and dynamics, similar to the way in which allosteric small molecules introduce functional conformational change. We refer to these substitutions as “allosteric mutations.” Allosteric mutations change oligomeric state by employing the same conformational dynamics as ligands. PyrR homologs differ by mutations, all of which are outside the tetrameric interface. A subset of these allosteric mutations can be used to engineer a shift in oligomeric state in the ancestral PyrR. Allosteric mutations act by introducing conformational change in a manner analogous to that of the allosteric ligands. Rationale In this work, we investigate the mechanism of action of allosteric mutations on oligomeric state in the PyrR family of pyrimidine operon attenuators. In this family, an entirely sequence-conserved helix that forms a tetrameric interface in the thermophilic ortholog (BcPyrR) switches to being solvent-exposed in the mesophilic ortholog (BsPyrR). This results in a homodimeric structure in which the two subunits are clearly rotated relative to their orientation in the tetramer. What is the origin of this rotation and the change in quaternary structure? To dissect the role of the 49 substitutions between BsPyrR and BcPyrR, we used ancestral sequence reconstruction in combination with structural and biophysical methods to identify a set of allosteric mutations that are responsible for this shift in conformation. We compared the conformational changes introduced by the mutations to the protein motion during allosteric regulation by guanosine monophosphate (GMP). Results We identified 11 key mutations controlling oligomeric state, all distant from the interfaces and outside ligand-binding pockets. We confirmed the role of these allosteric mutations by engineering a shift in oligomeric state in an inferred ancestral PyrR protein (intermediate in sequence between the extant orthologs). We further used the inferred ancestral states and their mutants to show that the allosteric mutations are part of a downhill adaptation of the PyrR proteins to lower temperatures. We compared the x-ray crystal structures of ancestral and engineered PyrR proteins to the free and GMP-bound structure of the mesophilic BsPyrR, which shifts its equilibrium from dimer to tetramer upon ligand binding. Binding of the allosteric molecule introduces a change in intersubunit geometry that is equivalent to the evolutionary difference in intersubunit geometry between the dimeric and tetrameric homologs. We further find that the difference in oligomeric state is coupled to the difference in intrinsic dynamics of the dimers. Finally, we used the residue-residue contact network approach to show that the residues corresponding to the allosteric mutations undergo large contact rewiring when the intersubunit geometry and, in turn, oligomeric state change, either by GMP binding or by the introduction of allosteric mutations. Conclusion We show that evolution employs the intrinsic dynamics of this protein to toggle a conformational switch in a manner similar to that of small molecules. Shifting the relative populations of different states by subtle modifications is a process central to protein function and, as shown here, also to protein evolution. This suggests that we can learn from evolution and design proteins with multiple conformational states. Evolution and design of protein complexes are almost always viewed through the lens of amino acid mutations at protein interfaces. We showed previously that residues not involved in the physical interaction between proteins make important contributions to oligomerization by acting indirectly or allosterically. In this work, we sought to investigate the mechanism by which allosteric mutations act, using the example of the PyrR family of pyrimidine operon attenuators. In this family, a perfectly sequence-conserved helix that forms a tetrameric interface is exposed as solvent-accessible surface in dimeric orthologs. This means that mutations must be acting from a distance to destabilize the interface. We identified 11 key mutations controlling oligomeric state, all distant from the interfaces and outside ligand-binding pockets. Finally, we show that the key mutations introduce conformational changes equivalent to the conformational shift between the free versus nucleotide-bound conformations of the proteins. Mutations can alter protein conformations in the same way that allosteric small molecules do. Controlling the state of dynamic proteins Small molecules that change the oligomeric state of proteins by binding to a site distant from the interface are called allosteric. They often act by taking advantage of intrinsic protein dynamics and stabilizing a particular conformation of the protein. Perica et al. show that mutations can similarly act at a distance to change protein conformation. They identified 11 mutations in an RNA- binding protein that determine whether it is stable as a dimer or a tetramer. Examination of ancestral sequences showed that the allosteric mutations are part of a downhill adaptation to lower environmental temperatures. This mechanism for modulating the oligomeric state is probably common in evolution. Science, this issue 10.1126/science.1254346

Comparing the intrinsic dynamics of multiple protein structures using elastic network models

BACKGROUND Elastic network models (ENMs) are based on the simple idea that a protein can be described as a set of particles connected by springs, which can then be used to describe its intrinsic flexibility using, for example, normal mode analysis. Since the introduction of the first ENM by Monique Tirion in 1996, several variants using coarser protein models have been proposed and their reliability for the description of protein intrinsic dynamics has been widely demonstrated. Lately an increasing number of studies have focused on the meaning of slow dynamics for protein function and its potential conservation through evolution. This leads naturally to comparisons of the intrinsic dynamics of multiple protein structures with varying levels of similarity. SCOPE OF REVIEW We describe computational strategies for calculating and comparing intrinsic dynamics of multiple proteins using elastic network models, as well as a selection of examples from the recent literature. MAJOR CONCLUSIONS The increasing interest for comparing dynamics across protein structures with various levels of similarity, has led to the establishment and validation of reliable computational strategies using ENMs. Comparing dynamics has been shown to be a viable way for gaining greater understanding for the mechanisms employed by proteins for their function. Choices of ENM parameters, structure alignment or similarity measures will likely influence the interpretation of the comparative analysis of protein motion. GENERAL SIGNIFICANCE Understanding the relation between protein function and dynamics is relevant to the fundamental understanding of protein structure-dynamics-function relationship. This article is part of a Special Issue entitled Recent developments of molecular dynamics.

Evaluation of Protein Elastic Network Models Based on an Analysis of Collective Motions

Elastic network models (ENMs) are valuable tools for investigating collective motions of proteins, and a rich variety of simple models have been proposed over the past decade. A good representation of the collective motions requires a good approximation of the covariances between the fluctuations of the individual atoms. Nevertheless, most studies have validated such models only by the magnitudes of the single-atom fluctuations they predict. In the present study, we have quantified the agreement between the covariance structure predicted by molecular dynamics (MD) simulations and those predicted by a representative selection of proposed coarse-grained ENMs. We then contrast this approach with the comparison to MD-predicted atomic fluctuations and comparison to crystallographic B-factors. While all the ENMs yield approximations to the MD-predicted covariance structure, we report large and consistent differences between proposed models. We also find that the ability of the ENMs to predict atomic fluctuations is correlated with their ability to capture the covariance structure. In contrast, we find that the models that agree best with B-factors model collective motions less reliably and recommend against using B-factors as a benchmark.