Advances in Homology Protein Structure Modeling

Xiang, Zhaoyin

doi:10.2174/138920306777452312

Cited by 426 publications

(259 citation statements)

References 144 publications

Supporting

Mentioning

243

Contrasting

Unclassified

Order By: Relevance

“…A marked structural resemblance exists in the overall architecture of the major core proteins and core particles of these two related orbiviruses (Burroughs et al, 1994;Basak et al, 1996Basak et al, , 1997Manole et al, 2012), as well as acceptable phylogenetic relationships between their VP3 or VP7 proteins. The amino acid sequence identity shared between VP3 of AHSV-9 and BTV-1 was 57.5%, while their VP7 proteins shared 42.8% identity, thus exceeding the 30% cut-off value for homology modeling (Xiang, 2006). The overall root mean squared distance (RMSD) for the entire heteromultimeric complex was 6.5 Å which, considering the complex size and the number of flexible loops, is good.…”

Section: Engineering and Assembly Of Mutant Ahsv Clpsmentioning

confidence: 97%

Synthesis of empty african horse sickness virus particles

Maree

Putterill

et al. 2016

Virus Research

View full text Add to dashboard Cite

As a means to develop African horse sickness (AHS) vaccines that are safe and DIVA compliant, we investigated the synthesis of empty African horse sickness virus (AHSV) particles. The emphasis of this study was on the assembly of the major viral core (VP3 and VP7) and outer capsid proteins (VP2 and VP5) into architecturally complex, heteromultimeric nanosized particles. The production of fully assembled corelike particles (CLPs) was accomplished in vivo by baculovirus-mediated co-synthesis of VP3 and VP7. The two different outer capsid proteins were capable of associating independently of each other with preformed cores to yield partial virus-like particles (VLPs). Complete VLPs were synthesized, albeit with a low yield. Crystalline formation of AHSV VP7 trimers is thought to impede high-level CLP production. Consequently, we engineered and co-synthesized VP3 with a more hydrophilic mutant VP7, resulting in an increase in the turnover of CLPs.

show abstract

Section: Engineering and Assembly Of Mutant Ahsv Clpsmentioning

confidence: 97%

Synthesis of empty african horse sickness virus particles

Maree

Putterill

et al. 2016

Virus Research

View full text Add to dashboard Cite

show abstract

“…The homology modeling procedure consists of four steps (Xiang 2006): Fig. 1 Eleven G protein-coupled receptor templates and three olfactory receptor multiple sequence alignments.…”

Section: Homology Modelingmentioning

confidence: 99%

Modeling of mammalian olfactory receptors and docking of odorants

et al. 2012

View full text Add to dashboard Cite

Olfactory receptors (ORs) belong to the superfamily of G protein-coupled receptors (GPCRs), the second largest class of genes after those related to immunity, and account for about 3 % of mammalian genomes. ORs are present in all multicellular organisms and represent more than half the GPCRs in mammalian species (e.g., the mouse OR repertoire contains >1,000 functional genes). ORs are mainly expressed in the olfactory epithelium where they detect odorant molecules, but they are also expressed in a number of other cells, such as sperm cells, although their functions in these cells remain mostly unknown. It has recently been reported that ORs are present in tumoral tissues where they are expressed at different levels than in healthy tissues. A specific OR is overexpressed in prostate cancer cells, and activation of this OR has been shown to inhibit the proliferation of these cells. Odorant stimulation of some of these receptors results in inhibition of cell proliferation. Even though their biological role has not yet been elucidated, these receptors might constitute new targets for diagnosis and therapeutics. It is important to understand the activation mechanism of these receptors at the molecular level, in particular to be able to predict which ligands are likely to activate a particular receptor ('deorphanization') or to design antagonists for a given receptor. In this review, we describe the in silico methodologies used to model the three-dimensional (3D) structure of ORs (in the more general framework of GPCR modeling) and to dock ligands into these 3D structures.

show abstract

“…The protein structures are being determined with the help of experimental methods including X-ray crystallography [16], NMR spectroscopy [17], electron microscopy [18], and (more recently) by application of computational approaches such as homology modelling [19,20]. The most popular method, which accounts for approximately 86% of the solved and deposited protein structures, is the X-ray crystallography; see Figure 1.…”

Section: X-ray Crystallography and Protein Crystallizationmentioning

confidence: 99%

Sequence-Based Protein Crystallization Propensity Prediction for Structural Genomics: Review and Comparative Analysis

Kurgan

Mizianty²

2009

View full text Add to dashboard Cite

Structural genomics (SG) is an international effort that aims at solving three-dimensional shapes of important biological macro-molecules with primary focus on proteins. One of the main bottlenecks in SG is the ability to produce diffraction quality crystals for X-ray crystallography based protein structure determination. SG pipelines allow for certain flexibility in target selection which motivates development of insilico methods for sequence-based prediction/ assessment of the protein crystallization propensity. We overview existing SG databanks that are used to derive these predictive models and we discuss analytical results concerning protein sequence properties that were discovered to correlate with the ability to form crystals. We also contrast and empirically compare modern sequence-based predictors of crystallization propensity including OB-Score, ParCrys, XtalPred and CRYSTALP2. Our analysis shows that these methods provide useful and complimentary predictions. Although their average accuracy is similar at around 70%, we show that application of a simple majority-vote based ensemble improves accuracy to almost 74%. The best improvements are achieved by combining XtalPred with CRYSTALP2 while OB-Score and ParCrys methods overlap to a larger extend, although they still complement the other two predictors. We also demonstrate that 90% of the protein chains can be correctly predicted by at least one of these methods, which suggests that more accurate ensembles could be built in the future. We believe that current protein crystallization propensity predictors could provide useful input for the target selection procedures utilized by the SG centers.

show abstract

Advances in Homology Protein Structure Modeling

Cited by 426 publications

References 144 publications

Synthesis of empty african horse sickness virus particles

Synthesis of empty african horse sickness virus particles

Modeling of mammalian olfactory receptors and docking of odorants

Sequence-Based Protein Crystallization Propensity Prediction for Structural Genomics: Review and Comparative Analysis

Contact Info

Product

Resources

About