Ab Initio Modeling of the Herpesvirus VP26 Core Domain Assessed by CryoEM Density

Efforts in structural biology have targeted the systematic determination of all protein structures through experimental determination or modeling. In recent years, 3-D electron cryomicroscopy (cryoEM) has assumed an increasingly important role in determining the structures of these large macromolecular assemblies to intermediate resolutions (6–10 Å). While these structures provide a snapshot of the assembly and its components in well-defined functional states, the resolution limits the ability to build accurate structural models. In contrast, sequence-based modeling techniques are capable of producing relatively robust structural models for isolated proteins or domains. In this work, we developed and applied a hybrid modeling approach, utilizing cryoEM density and ab initio modeling to produce a structural model for the core domain of a herpesvirus structural protein, VP26. Specifically, this method, first tested on simulated data, utilizes the cryoEM density map as a geometrical constraint in identifying the most native-like models from a gallery of models generated by ab initio modeling. The resulting model for the core domain of VP26, based on the 8.5-Å resolution herpes simplex virus type 1 (HSV-1) capsid cryoEM structure and mutational data, exhibited a novel fold. Additionally, the core domain of VP26 appeared to have a complementary interface to the known upper-domain structure of VP5, its cognate binding partner. While this new model provides for a better understanding of the assembly and interactions of VP26 in HSV-1, the approach itself may have broader applications in modeling the components of large macromolecular assemblies

Identification of structural protein–protein interactions of herpes simplex virus type 1

AbstractIn this study we have defined protein–protein interactions between the structural proteins of herpes simplex virus type 1 (HSV-1) using a LexA yeast two-hybrid system. The majority of the capsid, tegument and envelope proteins of HSV-1 were screened in a matrix approach. A total of 40 binary interactions were detected including 9 out of 10 previously identified tegument–tegument interactions (Vittone, V., Diefenbach, E., Triffett, D., Douglas, M.W., Cunningham, A.L., and Diefenbach, R.J., 2005. Determination of interactions between tegument proteins of herpes simplex virus type 1. J. Virol. 79, 9566–9571). A total of 12 interactions involving the capsid protein pUL35 (VP26) and 11 interactions involving the tegument protein pUL46 (VP11/12) were identified. The most significant novel interactions detected in this study, which are likely to play a role in viral assembly, include pUL35–pUL37 (capsid–tegument), pUL46–pUL37 (tegument–tegument) and pUL49 (VP22)–pUS9 (tegument–envelope). This information will provide further insights into the pathways of HSV-1 assembly and the identified interactions are potential targets for new antiviral drugs

Structure prediction for the helical skeletons detected from the low resolution protein density map

<p>Abstract</p> <p>Background</p> <p>The current advances in electron cryo-microscopy technique have made it possible to obtain protein density maps at about 6-10 Å resolution. Although it is hard to derive the protein chain directly from such a low resolution map, the location of the secondary structures such as helices and strands can be computationally detected. It has been demonstrated that such low-resolution map can be used during the protein structure prediction process to enhance the structure prediction.</p> <p>Results</p> <p>We have developed an approach to predict the 3-dimensional structure for the helical skeletons that can be detected from the low resolution protein density map. This approach does not require the construction of the entire chain and distinguishes the structures based on the conformation of the helices. A test with 35 low resolution density maps shows that the highest ranked structure with the correct topology can be found within the top 1% of the list ranked by the effective energy formed by the helices.</p> <p>Conclusion</p> <p>The results in this paper suggest that it is possible to eliminate the great majority of the bad conformations of the helices even without the construction of the entire chain of the protein. For many proteins, the effective contact energy formed by the secondary structures alone can distinguish a small set of likely structures from the pool.</p

Intensity-Based Skeletonization of CryoEM Gray-Scale Images Using a True Segmentation-Free Algorithm

Cryo-electron microscopy is an experimental technique that is able to produce 3D gray-scale images of protein molecules. In contrast to other experimental techniques, cryo-electron microscopy is capable of visualizing large molecular complexes such as viruses and ribosomes. At medium resolution, the positions of the atoms are not visible and the process cannot proceed. The medium-resolution images produced by cryo-electron microscopy are used to derive the atomic structure of the proteins in de novo modeling. The skeletons of the 3D gray-scale images are used to interpret important information that is helpful in de novo modeling. Unfortunately, not all features of the image can be captured using a single segmentation. In this paper, we present a segmentation-free approach to extract the gray-scale curve-like skeletons. The approach relies on a novel representation of the 3D image, where the image is modeled as a graph and a set of volume trees. A test containing 36 synthesized maps and one authentic map shows that our approach can improve the performance of the two tested tools used in de novo modeling. The improvements were 62 and 13 percent for Gorgon and DP-TOSS, respectively

Determining Alpha-Helix Correspondence for Protein Structure Prediction from Cryo-EM Density Maps, Master\u27s Thesis, May 2007

Determining protein structure is an important problem for structural biologists, which has received a significant amount of attention in the recent years. In this thesis, we describe a novel, shape-modeling approach as an intermediate step towards recovering 3D protein structures from volumetric images. The input to our method is a sequence of alpha-helices that make up a protein, and a low-resolution volumetric image of the protein where possible locations of alpha-helices have been detected. Our task is to identify the correspondence between the two sets of helices, which will shed light on how the protein folds in space. The central theme of our approach is to cast the correspondence problem as that of shape matching between the 3D volume and the 1D sequence. We model both the shapes as attributed relational graphs, and formulate a constrained inexact graph matching problem. To compute the matching, we developed an optimal algorithm based on the A*-search with several choices of heuristic functions. As demonstrated in a suite of real protein data, the shape-modeling approach is capable of correctly identifying helix correspondences in noise-abundant volumes with minimal or no user intervention

Herpes Simplex Virus Dances with Amyloid Precursor Protein while Exiting the Cell

Herpes simplex type 1 (HSV1) replicates in epithelial cells and secondarily enters local sensory neuronal processes, traveling retrograde to the neuronal nucleus to enter latency. Upon reawakening newly synthesized viral particles travel anterograde back to the epithelial cells of the lip, causing the recurrent cold sore. HSV1 co-purifies with amyloid precursor protein (APP), a cellular transmembrane glycoprotein and receptor for anterograde transport machinery that when proteolyzed produces A-beta, the major component of senile plaques. Here we focus on transport inside epithelial cells of newly synthesized virus during its transit to the cell surface. We hypothesize that HSV1 recruits cellular APP during transport. We explore this with quantitative immuno-fluorescence, immuno-gold electron-microscopy and live cell confocal imaging. After synchronous infection most nascent VP26-GFP-labeled viral particles in the cytoplasm co-localize with APP (72.8+/−6.7%) and travel together with APP inside living cells (81.1+/−28.9%). This interaction has functional consequences: HSV1 infection decreases the average velocity of APP particles (from 1.1+/−0.2 to 0.3+/−0.1 µm/s) and results in APP mal-distribution in infected cells, while interplay with APP-particles increases the frequency (from 10% to 81% motile) and velocity (from 0.3+/−0.1 to 0.4+/−0.1 µm/s) of VP26-GFP transport. In cells infected with HSV1 lacking the viral Fc receptor, gE, an envelope glycoprotein also involved in viral axonal transport, APP-capsid interactions are preserved while the distribution and dynamics of dual-label particles differ from wild-type by both immuno-fluorescence and live imaging. Knock-down of APP with siRNA eliminates APP staining, confirming specificity. Our results indicate that most intracellular HSV1 particles undergo frequent dynamic interplay with APP in a manner that facilitates viral transport and interferes with normal APP transport and distribution. Such dynamic interactions between APP and HSV1 suggest a mechanistic basis for the observed clinical relationship between HSV1 seropositivity and risk of Alzheimer's disease

De Novo Protein Structure Modeling from Cryoem Data Through a Dynamic Programming Algorithm in the Secondary Structure Topology Graph

Proteins are the molecules carry out the vital functions and make more than the half of dry weight in every cell. Protein in nature folds into a unique and energetically favorable 3-Dimensional (3-D) structure which is critical and unique to its biological function. In contrast to other methods for protein structure determination, Electron Cryorricroscopy (CryoEM) is able to produce volumetric maps of proteins that are poorly soluble, large and hard to crystallize. Furthermore, it studies the proteins in their native environment. Unfortunately, the volumetric maps generated by current advances in CryoEM technique produces protein maps at medium resolution about (~5 to 10Å) in which it is hard to determine the atomic-structure of the protein. However, the resolution of the volumetric maps is improving steadily, and recent works could obtain atomic models at higher resolutions (~3Å). De novo protein modeling is the process of building the structure of the protein using its CryoEM volumetric map. Thereupon, the volumetric maps at medium resolution generated by CryoEM technique proposed a new challenge. At the medium resolution, the location and orientation of secondary structure elements (SSE) can be visually and computationally identified. However, the order and direction (called protein topology) of the SSEs detected from the CryoEM volumetric map are not visible. In order to determine the protein structure, the topology of the SSEs has to be figured out and then the backbone can be built. Consequently, the topology problem has become a bottle neck for protein modeling using CryoEM In this dissertation, we focus to establish an effective computational framework to derive the atomic structure of a protein from the medium resolution CryoEM volumetric maps. This framework includes a topology graph component to rank effectively the topologies of the SSEs and a model building component. In order to generate the small subset of candidate topologies, the problem is translated into a layered graph representation. We developed a dynamic programming algorithm (TopoDP) for the new representation to overcome the problem of large search space. Our approach shows the improved accuracy, speed and memory use when compared with existing methods. However, the generating of such set was infeasible using a brute force method. Therefore, the topology graph component effectively reduces the topological space using the geometrical features of the secondary structures through a constrained K-shortest paths method in our layered graph. The model building component involves the bending of a helix and the loop construction using skeleton of the volumetric map. The forward-backward CCD is applied to bend the helices and model the loops

Computational Development for Secondary Structure Detection From Three-Dimensional Images of Cryo-Electron Microscopy

Electron cryo-microscopy (cryo-EM) as a cutting edge technology has carved a niche for itself in the study of large-scale protein complex. Although the protein backbone of complexes cannot be derived directly from the medium resolution (5-10 Å) of amino acids from three-dimensional (3D) density images, secondary structure elements (SSEs) such as alpha-helices and beta-sheets can still be detected. The accuracy of SSE detection from the volumetric protein density images is critical for ab initio backbone structure derivation in cryo-EM. So far it is challenging to detect the SSEs automatically and accurately from the density images at these resolutions. This dissertation presents four computational methods - SSEtracer, SSElearner, StrandTwister and StrandRoller for solving this critical problem. An effective approach, SSEtracer, is presented to automatically identify helices and β- sheets from the cryo-EM three-dimensional maps at medium resolutions. A simple mathematical model is introduced to represent the β-sheet density. The mathematical model can be used for β-strand detection from medium resolution density maps. A machine learning approach, SSElearner, has also been developed to automatically identify helices and β-sheets by using the knowledge from existing volumetric maps in the Electron Microscopy Data Bank (EMDB). The approach has been tested using simulated density maps and experimental cryo-EM maps of EMDB. The results of SSElearner suggest that it is effective to use one cryo-EM map for learning in order to detect the SSE in another cryo-EM map of similar quality. Major secondary structure elements such as a-helices and β-sheets can be computationally detected from cryo-EM density maps with medium resolutions of 5-10Å. However, a critical piece of information for modeling atomic structures is missing, since there are no tools to detect β-strands from cryo-EM maps at medium resolutions. A new method, StrandTwister, has been proposed to detect the traces of β-strands through the analysis of twist, an intrinsic nature of β-sheet. StrandTwister has been tested using 100 β-sheets simulated at 10Å resolution and 39 β-sheets computationally detected from cryoEM density maps at 4.4-7.4Å resolutions. StrandTwister appears to detect the traces of β-strands on major β-sheets quite accurately, particularly at the central area of a β-sheet. β-barrel is a structure feature that is formed by multiple β-strands in a barrel shape. There is no existing method to derive the β-strands from the 3D image of β-barrel. A new method, StrandRoller, has been proposed to generate small sets of possible β-traces from the density images at medium resolutions of 5-10Å. The results of StrandRoller suggest that it is possible to derive a small set of possible β-traces from the β-barrel cryo-EM image at medium resolutions even when it is not possible to visualize the separation of β-strands

La protéine majeure de la capside de l’HSV-1 est ubiquitinée

Le virus de l’Herpès simplex de type 1 (HSV-1) est le pathogène humain responsable des lésions herpétiques labiales, plus communément appelé « feux sauvages ». Annuellement, il est responsable de plusieurs cas d’encéphalites et d’infections de l’appareil visuel qui sont la principale cause de cécité en Amérique du Nord. Bien qu’il existe quelques traitements antiviraux, aucun vaccin ou médicament ne permet de prévenir ou de guérir les infections causées par ce virus. Aujourd’hui, les infections produites par l’HSV-1 sont présentes partout sur la planète. Récemment, une étude en protéomique effectuée sur les virus matures extracellulaires a permis d’identifier la présence d’ubiquitines libres et d’enzymes reliées à la machinerie d’ubiquitination dans le virus. De plus, le virus exploite cette machinerie au cours de l’infection. Il est connu que certaines protéines virales sont ubiquitinées durant une infection et que le virus imite même certaines enzymes d’ubiquitination. Nous avons donc entrepris des recherches afin d’identifier des protéines virales ubiquitinées qui pourraient être présentes dans les virus matures ainsi que leurs rôles potentiels. La protéine majeure de la capside, VP5, un constituant très important du virus, a été identifiée. Nos recherches nous ont permis de caractériser le type d’ubiquitination, une monoubiquitination sur les lysines K810 et/ou K1275 de VP5. Le rôle que pourrait jouer l’ubiquitination de VP5 dans le cycle de réplication virale et dans les virus matures n’est toutefois pas encore connu.Herpes simplex virus type 1 (HSV-1) is the human pathogen responsible for herpetic lesion such as cold sores. On a yearly basis, it is responsible for many cases of encephalitis and infections of the eye that are the most common cause of blindness in North America. Antiviral treatments exist, but no vaccines or drugs are able to prevent or cure the diseases caused by this virus. Today, infections caused by HSV-1 are present all around the world. Recently a proteomics approach was used to study mature extracellular viruses. This study highlighted the presence in the virus of free ubiquitin and ubiquitin related enzymes. Furthermore, the virus exploits this machinery during the course of infection. Also, it is known that certain virally encoded proteins are ubiquitinated and that the virus mimics some ubiquitin related enzymes. Our researches focused on identifying ubiquitinated viral proteins that could be present in mature extracellular viruses and their potential roles. The major capsid protein, VP5, an important virus component, was identified. We characterised the type of ubiquitination, a monoubiquitination of lysine K810 and/or K1275 of VP5. The role that could play the ubiquitination of VP5 in the viral cell cycle and in mature virions has yet to be identified