Theoretical Model of the Three-dimensional Structure of a Disease Resistance Gene Homolog Encoding Resistance Protein in Vigna mungo

Abstract

Plant disease resistance (R) genes, the key players of innate immunity system in plants encode ‘R’ proteins. ‘R’ protein recognizes product of avirulance gene from the pathogen and activate downstream signaling responses leading to disease resistance. No three dimensional (3D) structural information of any ‘R’ proteins is available as yet. We have reported a ‘R’ gene homolog, the 'VMYR1′, encoding ‘R’ protein in Vigna mungo. Here, we describe the homology modeling of the 'VMYR1′ protein. The model was created by using the 3D structure of an ATP-binding cassette transporter protein from Vibrio cholerae as a template. The strategy for homology modeling was based on the high structural conservation in the superfamily of P-loop containing nucleoside triphosphate hydrolase in which target and template proteins belong. This is the first report of theoretical model structure of any ‘R’ proteins.     

Prediction of 3-dimensional structure of salivary odorant-binding protein-2 of the mosquito Culex quinquefasciatus, the vector of human lymphatic filariasis

Olfaction of insects is currently recognized as the major area of research for developing novel control strategies to prevent mosquito-borne infections. A 3-dimensional model (3D) was developed for the salivary gland odorant-binding protein-2 of the mosquito Culex quinquefasciatus, a major vector of human lymphatic filariasis. A homology modeling method was used for the prediction of the structure. For the modeling, two template proteins were obtained by mGenTHERADER, namely the high-resolution X-ray crystallography structure of a pheromone-binding protein (ASP1) of Apis mellifera L., [1R5R:A] and the aristolochene synthase from Penicillium roqueforti [1DI1:B]. By comparing the template protein a rough model was constructed for the target protein using MODELLER, a program for comparative modelling. The structure of OBP of the mosquito Culex quinquefasciatus resembles the structure of pheromone-binding protein ASP1 of Apis mellifera L., [1R5R:A]. From Ramachandran plot analysis it was found that the portion of residues falling into the most favoured regions was 86.0%. The predicted 3-D model may be further used in characterizing the protein in wet laboratory.     

All are not equal: a benchmark of different homology modeling programs

Modeling a protein structure based on a homologous structure is a standard method in structural biology today. In this process an alignment of a target protein sequence onto the structure of a template(s) is used as input to a program that constructs a 3D model. It has been shown that the most important factor in this process is the correctness of the alignment and the choice of the best template structure(s), while it is generally believed that there are no major differences between the best modeling programs. Therefore, a large number of studies to benchmark the alignment qualities and the selection process have been performed. However, to our knowledge no large-scale benchmark has been performed to evaluate the programs used to transform the alignment to a 3D model. In this study, a benchmark of six different homology modeling programs- Modeller, SegMod/ENCAD, SWISS-MODEL, 3D-JIGSAW, nest, and Builder-is presented. The performance of these programs is evaluated using physiochemical correctness and structural similarity to the correct structure. From our analysis it can be concluded that no single modeling program outperform the others in all tests. However, it is quite clear that three modeling programs, Modeller, nest, and SegMod/ ENCAD, perform better than the others. Interestingly, the fastest and oldest modeling program, SegMod/ ENCAD, performs very well, although it was written more than 10 years ago and has not undergone any development since. It can also be observed that none of the homology modeling programs builds side chains as well as a specialized program (SCWRL), and therefore there should be room for improvement.     

Computational protein structure modeling and analysis of UV-B stress protein in Synechocystis PCC 6803

This study focuses on Ultra Violet stress (UVS) gene product which is a UV stress induced protein from cyanobacteria, Synechocystis PCC 6803. Three dimensional structural modeling of target UVS protein was carried out by homology modeling method. 3F2I pdb from Nostoc sp. PCC 7120 was selected as a suitable template protein structure. Ultimately, the detection of active binding regions was carried out for characterization of functional sites in modeled UV-B stress protein. The top five probable ligand binding sites were predicted and the common binding residues between target and template protein was analyzed. It has been validated for the first time that modeled UVS protein structure from Synechocystis PCC 6803 was structurally and functionally similar to well characterized UVS protein of another cyanobacterial species, Nostoc sp PCC 7120 because of having same structural motif and fold with similar protein topology and function. Investigations revealed that UVS protein from Synechocystis sp. might play significant role during ultraviolet resistance. Thus, it could be a potential biological source for remediation for UV induced stress.     

Assessing model accuracy using the homology modeling automatically software

Homology modeling is a powerful technique that greatly increases the value of experimental structure determination by using the structural information of one protein to predict the structures of homologous proteins. We have previously described a method of homology modeling by satisfaction of spatial restraints (Li et al., Protein Sci 1997;6:956-970). The Homology Modeling Automatically (HOMA) web site, , is a new tool, using this method to predict 3D structure of a target protein based on the sequence alignment of the target protein to a template protein and the structure coordinates of the template. The user is presented with the resulting models, together with an extensive structure validation report providing critical assessments of the quality of the resulting homology models. The homology modeling method employed by HOMA was assessed and validated using twenty-four groups of homologous proteins. Using HOMA, homology models were generated for 510 proteins, including 264 proteins modeled with correct folds and 246 modeled with incorrect folds. Accuracies of these models were assessed by superimposition on the corresponding experimentally determined structures. A subset of these results was compared with parallel studies of modeling accuracy using several other automated homology modeling approaches. Overall, HOMA provides prediction accuracies similar to other state-of-the-art homology modeling methods. We also provide an evaluation of several structure quality validation tools in assessing the accuracy of homology models generated with HOMA. This study demonstrates that Verify3D (Luthy et al., Nature 1992;356:83-85) and ProsaII (Sippl, Proteins 1993;17:355-362) are most sensitive in distinguishing between homology models with correct or incorrect folds. For homology models that have the correct fold, the steric conformational energy (including primarily the Van der Waals energy), MolProbity clashscore (Word et al., Protein Sci 2000;9:2251-2259), and the PROCHECK G-factors (Laskowski et al., J Biomol NMR 1996;8:477-486) provide sensitive and consistent methods for assessing accuracy and can distinguish between homology models of higher and lower accuracy. As demonstrated in the accompanying paper (Bhattacharya et al., accompanying paper), combinations of these scores for models generated with HOMA provide a basis for distinguishing low from high accuracy models.     

ESyPred3D: Prediction of proteins 3D structures

MOTIVATION: Homology or comparative modeling is currently the most accurate method to predict the three-dimensional structure of proteins. It generally consists in four steps: (1) databanks searching to identify the structural homolog, (2) target-template alignment, (3) model building and optimization, and (4) model evaluation. The target-template alignment step is generally accepted as the most critical step in homology modeling. RESULTS: We present here ESyPred3D, a new automated homology modeling program. The method gets benefit of the increased alignment performances of a new alignment strategy. Alignments are obtained by combining, weighting and screening the results of several multiple alignment programs. The final three-dimensional structure is build using the modeling package MODELLER. ESyPred3D was tested on 13 targets in the CASP4 experiment (Critical Assessment of Techniques for Proteins Structural Prediction). Our alignment strategy obtains better results compared to PSI-BLAST alignments and ESyPred3D alignments are among the most accurate compared to those of participants having used the same template. AVAILABILITY: ESyPred3D is available through its web site at http://www.fundp.ac.be/urbm/bioinfo/esypred/ CONTACT: christophe.lambert@fundp.ac.be; http://www.fundp.ac.be/~lambertc     

Optimizing structural modeling for a specific protein scaffold: knottins or inhibitor cystine knots

Background

Knottins are small, diverse and stable proteins with important drug design potential. They can be classified in 30 families which cover a wide range of sequences (1621 sequenced), three-dimensional structures (155 solved) and functions (> 10). Inter knottin similarity lies mainly between 15% and 40% sequence identity and 1.5 to 4.5 Å backbone deviations although they all share a tightly knotted disulfide core. This important variability is likely to arise from the highly diverse loops which connect the successive knotted cysteines. The prediction of structural models for all knottin sequences would open new directions for the analysis of interaction sites and to provide a better understanding of the structural and functional organization of proteins sharing this scaffold.

Results

We have designed an automated modeling procedure for predicting the three-dimensionnal structure of knottins. The different steps of the homology modeling pipeline were carefully optimized relatively to a test set of knottins with known structures: template selection and alignment, extraction of structural constraints and model building, model evaluation and refinement. After optimization, the accuracy of predicted models was shown to lie between 1.50 and 1.96 Å from native structures at 50% and 10% maximum sequence identity levels, respectively. These average model deviations represent an improvement varying between 0.74 and 1.17 Å over a basic homology modeling derived from a unique template. A database of 1621 structural models for all known knottin sequences was generated and is freely accessible from our web server at http://knottin.cbs.cnrs.fr. Models can also be interactively constructed from any knottin sequence using the structure prediction module Knoter1D3D available from our protein analysis toolkit PAT at http://pat.cbs.cnrs.fr.

Conclusions

This work explores different directions for a systematic homology modeling of a diverse family of protein sequences. In particular, we have shown that the accuracy of the models constructed at a low level of sequence identity can be improved by 1) a careful optimization of the modeling procedure, 2) the combination of multiple structural templates and 3) the use of conserved structural features as modeling restraints.

     

Using molecular dynamics for the refinement of atomistic models of GPCRs by homology modeling

Despite GPCRs sharing a common seven helix bundle, analysis of the diverse crystallographic structures available reveal specific features that might be relevant for ligand design. Despite the number of crystallographic structures of GPCRs steadily increasing, there are still challenges that hamper the availability of new structures. In the absence of a crystallographic structure, homology modeling remains one of the important techniques for constructing 3D models of proteins. In the present study we investigated the use of molecular dynamics simulations for the refinement of GPCRs models constructed by homology modeling. Specifically, we investigated the relevance of template selection, ligand inclusion as well as the length of the simulation on the quality of the GPCRs models constructed. For this purpose we chose the crystallographic structure of the rat muscarinic M3 receptor as reference and constructed diverse atomistic models by homology modeling, using different templates. Specifically, templates used in the present work include the human muscarinic M2; the more distant human histamine H1 and the even more distant bovine rhodopsin as shown in the GPCRs phylogenetic tree. We also investigated the use or not of a ligand in the refinement process. Hence, we conducted the refinement process of the M3 model using the M2 muscarinic as template with tiotropium or NMS docked in the orthosteric site and compared with the results obtained with a model refined without any ligand bound.     

High-quality homology models derived from NMR and X-ray structures of E. coli proteins YgdK and Suf E suggest that all members of the YgdK/Suf E protein family are enhancers of cysteine desulfurases

The structural biology of proteins mediating iron-sulfur (Fe-S) cluster assembly is central for understanding several important biological processes. Here we present the NMR structure of the 16-kDa protein YgdK from Escherichia coli, which shares 35% sequence identity with the E. coli protein SufE. The SufE X-ray crystal structure was solved in parallel with the YdgK NMR structure in the Northeast Structural Genomics (NESG) consortium. Both proteins are (1) key components for Fe-S metabolism, (2) exhibit the same distinct fold, and (3) belong to a family of at least 70 prokaryotic and eukaryotic sequence homologs. Accurate homology models were calculated for the YgdK/SufE family based on YgdK NMR and SufE crystal structure. Both structural templates contributed equally, exemplifying synergy of NMR and X-ray crystallography. SufE acts as an enhancer of the cysteine desulfurase activity of SufS by SufE-SufS complex formation. A homology model of CsdA, a desulfurase encoded in the same operon as YgdK, was modeled using the X-ray structure of SufS as a template. Protein surface and electrostatic complementarities strongly suggest that YgdK and CsdA likewise form a functional two-component desulfurase complex. Moreover, structural features of YgdK and SufS, which can be linked to their interaction with desulfurases, are conserved in all homology models. It thus appears very likely that all members of the YgdK/SufE family act as enhancers of Suf-S-like desulfurases. The present study exemplifies that "refined" selection of two (or more) targets enables high-quality homology modeling of large protein families.     

The impact of extremophiles on structural genomics (and vice versa)

The advent of the complete genome sequences of various organisms in the mid-1990s raised the issue of how one could determine the function of hypothetical proteins. While insight might be obtained from a 3D structure, the chances of being able to predict such a structure is limited for the deduced amino acid sequence of any uncharacterized gene. A template for modeling is required, but there was only a low probability of finding a protein closely-related in sequence with an available structure. Thus, in the late 1990s, an international effort known as structural genomics (SG) was initiated, its primary goal to “fill sequence-structure space” by determining the 3D structures of representatives of all known protein families. This was to be achieved mainly by X-ray crystallography and it was estimated that at least 5,000 new structures would be required. While the proteins (genes) for SG have subsequently been derived from hundreds of different organisms, extremophiles and particularly thermophiles have been specifically targeted due to the increased stability and ease of handling of their proteins, relative to those from mesophiles. This review summarizes the significant impact that extremophiles and proteins derived from them have had on SG projects worldwide. To what extent SG has influenced the field of extremophile research is also discussed.     

Insights from molecular modeling and dynamics simulation of pathogen resistance (R) protein from brinjal

Resistance (R) protein recognizes molecular signature of pathogen infection and activates downstream hypersensitive response signalling in plants. R protein works as a molecular switch for pathogen defence signalling and represent one of the largest plant gene family. Hence, understanding molecular structure and function of R proteins has been of paramount importance for plant biologists. The present study is aimed at predicting structure of R proteins signalling domains (CC-NBS) by creating a homology model, refining and optimising the model by molecular dynamics simulation and comparing ADP and ATP binding. Based on sequence similarity with proteins of known structures, CC-NBS domains were initially modelled using CED- 4 (cell death abnormality protein) and APAF-1 (apoptotic protease activating factor) as multiple templates. The final CC-NBS structural model was built and optimized by molecular dynamic simulation for 5 nanoseconds (ns). Docking of ADP and ATP at active site shows that both ligand bind specifically with same residues and with minor difference (1 Kcal/mol) in binding energy. Sharing of binding site by ADP and ATP and low difference in their binding site makes CC-NBS suitable for working as molecular switch. Furthermore, structural superimposition elucidate that CC-NBS and CARD (caspase recruitment domains) domain of CED-4 have low RMSD value of 0.9 A° Availability of 3D structural model for both CC and NBS domains will . help in getting deeper insight in these pathogen defence genes.     

bfr1+, a novel gene of Schizosaccharomyces pombe which confers brefeldin A resistance, is structurally related to the ATP-binding cassette superfamily.

We have isolated a Schizosaccharomyces pombe gene, bfr1+, which on a multicopy plasmid vector, pDB248', confers resistance to brefeldin A (BFA), an inhibitor of intracellular protein transport. This gene encodes a novel protein of 1,531 amino acids with an intramolecular duplicated structure, each half containing a single ATP-binding consensus sequence and a set of six transmembrane sequences. This structural characteristic of bfr1+ protein resembles that of mammalian P-glycoprotein, which, by exporting a variety of anticancer drugs, has been shown to be responsible for multidrug resistance in tumor cells. Consistent with this is that S. pombe cells harboring bfr1+ on pDB248' are resistant to actinomycin D, cerulenin, and cytochalasin B, as well as to BFA. The relative positions of the ATP-binding sequences and the clusters of transmembrane sequences within the bfr1+ protein are, however, transposed in comparison with those in P-glycoprotein; the bfr1+ protein has N-terminal ATP-binding sequence followed by transmembrane segments in each half of the molecule. The bfr1+ protein exhibited significant homology in primary and secondary structures with two recently identified multidrug resistance gene products of Saccharomyces cerevisiae, Snq2 and Sts1/Pdr5/Ydr1. The bfr1+ gene is not essential for cell growth or mating, but a delta bfr1 mutant exhibited hypersensitivity to BFA. We propose that the bfr1+ protein is another member of the ATP-binding cassette superfamily and serves as an efflux pump of various antibiotics.     

Beyond the Twilight Zone: Automated prediction of structural properties of proteins by recursive neural networks and remote homology information

The prediction of 1D structural properties of proteins is an important step toward the prediction of protein structure and function, not only in the ab initio case but also when homology information to known structures is available. Despite this the vast majority of 1D predictors do not incorporate homology information into the prediction process. We develop a novel structural alignment method, SAMD, which we use to build alignments of putative remote homologues that we compress into templates of structural frequency profiles. We use these templates as additional input to ensembles of recursive neural networks, which we specialise for the prediction of query sequences that show only remote homology to any Protein Data Bank structure. We predict four 1D structural properties – secondary structure, relative solvent accessibility, backbone structural motifs, and contact density. Secondary structure prediction accuracy, tested by five‐fold cross‐validation on a large set of proteins allowing less than 25% sequence identity between training and test set and query sequences and templates, exceeds 82%, outperforming its ab initio counterpart, other state‐of‐the‐art secondary structure predictors (Jpred 3 and PSIPRED) and two other systems based on PSI‐BLAST and COMPASS templates. We show that structural information from homologues improves prediction accuracy well beyond the Twilight Zone of sequence similarity, even below 5% sequence identity, for all four structural properties. Significant improvement over the extraction of structural information directly from PDB templates suggests that the combination of sequence and template information is more informative than templates alone. Proteins 2009. © 2009 Wiley‐Liss, Inc.     

Improvement of comparative modeling by the application of conserved motifs amongst distantly related proteins as additional restraints

Protein comparative modeling has useful applications in large-scale structural initiatives and in rational design of drug targets in medicinal chemistry. The reliability of a homology model is dependent on the sequence identity between the query and the structural homologue used as a template for modeling. Here, we present a method for the utilization and conservation of important structural features of template structures by providing additional spatial restraints in comparative modeling programs like MODELLER. We show that root mean square deviation at C(alpha) positions between the model and the corresponding experimental structure and the quality of the models can be significantly improved for distantly related systems by utilizing additional spatial restraints of the template structures. We demonstrate the influence of such approaches to homology modeling during distant relationships in understanding functional properties of protein such as ligand binding using cytochrome P450 as an example.     

Homology modeling, comparative genomics and functional annotation of Mycoplasma genitalium hypothetical protein MG_237

Mycoplasma genitalium is a human pathogen associated with several sexually transmitted diseases. The complete genome of M. genitalium G37 has been sequenced and provides an opportunity to understand the pathogenesis and identification of therapeutic targets. However, complete understanding of bacterial function requires proper annotation of its proteins. The genome of M. genitalium consists of 475 proteins. Among these, 94 are without any known function and are described as 'hypothetical proteins'. We selected MG_237 for sequence and structural analysis using a bioinformatics approach. Primary and secondary structure analysis suggested that MG_237 is a hydrophilic protein containing a significant proportion of alpha helices, and subcellular localization predictions suggested it is a cytoplasmic protein. Homology modeling was used to define the three-dimensional (3D) structure of MG-237. A search for templates revealed that MG_237 shares 63% homology to a hypothetical protein of Mycoplasma pneumoniae, indicating this protein is evolutionary conserved. The refined 3D model was generated using (PS)(2)-v2 sever that incorporates MODELLER. Several quality assessment and validation parameters were computed and indicated that the homology model is reliable. Furthermore, comparative genomics analysis suggested MG_237 as non-homologous protein and involved in four different metabolic pathways. Experimental validation will provide more insight into the actual function of this protein in microbial pathways.     

Structural modeling of ataxin-3 reveals distant homology to adaptins

Spinocerebellar ataxia type 3 (SCA3) is a polyglutamine disorder caused by a CAG repeat expansion in the coding region of a gene encoding ataxin-3, a protein of yet unknown function. Based on a comprehensive computational analysis, we propose a structural model and structure-based functions for ataxin-3. Our predictive strategy comprises the compilation of multiple sequence and structure alignments of carefully selected proteins related to ataxin-3. These alignments are consistent with additional information on sequence motifs, secondary structure, and domain architectures. The application of complementary methods revealed the homology of ataxin-3 to ENTH and VHS domain proteins involved in membrane trafficking and regulatory adaptor functions. We modeled the structure of ataxin-3 using the adaptin AP180 as a template and assessed the reliability of the model by comparison with known sequence and structural features. We could further infer potential functions of ataxin-3 in agreement with known experimental data. Our database searches also identified an as yet uncharacterized family of proteins, which we named josephins because of their pronounced homology to the Josephin domain of ataxin-3.     

Evidence of salicylic acid pathway with EDS1 and PAD4 proteins by molecular dynamics simulation for grape improvement

Biotic stress is a major cause of heavy loss in grape productivity. In order to develop biotic stress-resistant grape varieties, the key defense genes along with its pathway have to be deciphered. In angiosperm plants, lipase-like protein phytoalexin deficient 4 (PAD4) is well known to be essential for systemic resistance against biotic stress. PAD4 functions together with its interacting partner protein enhanced disease susceptibility 1 (EDS1) to promote salicylic acid (SA)-dependent and SA-independent defense pathway. Existence and structure of key protein of systemic resistance EDS1 and PAD4 are not known in grapes. Before SA pathway studies are taken in grape, molecular evidence of EDS1: PAD4 complex is to be established. To establish this, EDS1 protein sequence was retrieved from NCBI and homologous PAD4 protein was generated using Arabidopsis thaliana as template and conserved domains were confirmed. In this study, computational methods were used to model EDS1 and PAD4 and simulated the interactions of EDS1 and PAD4. Since no structural details of the proteins were available, homology modeling was employed to construct three-dimensional structures. Further, molecular dynamic simulations were performed to study the dynamic behavior of the EDS1 and PAD4. The modeled proteins were validated and subjected to molecular docking analysis. Molecular evidence of stable complex of EDS1:PAD4 in grape supporting SA defense pathway in response to biotic stress is reported in this study. If SA defense pathway genes are explored, then markers of genes involved can play pivotal role in grape variety development especially against biotic stress leading to higher productivity.     

On the accuracy of homology modeling and sequence alignment methods applied to membrane proteins

In this study, we investigate the extent to which techniques for homology modeling that were developed for water-soluble proteins are appropriate for membrane proteins as well. To this end we present an assessment of current strategies for homology modeling of membrane proteins and introduce a benchmark data set of homologous membrane protein structures, called HOMEP. First, we use HOMEP to reveal the relationship between sequence identity and structural similarity in membrane proteins. This analysis indicates that homology modeling is at least as applicable to membrane proteins as it is to water-soluble proteins and that acceptable models (with C alpha-RMSD values to the native of 2 A or less in the transmembrane regions) may be obtained for template sequence identities of 30% or higher if an accurate alignment of the sequences is used. Second, we show that secondary-structure prediction algorithms that were developed for water-soluble proteins perform approximately as well for membrane proteins. Third, we provide a comparison of a set of commonly used sequence alignment algorithms as applied to membrane proteins. We find that high-accuracy alignments of membrane protein sequences can be obtained using state-of-the-art profile-to-profile methods that were developed for water-soluble proteins. Improvements are observed when weights derived from the secondary structure of the query and the template are used in the scoring of the alignment, a result which relies on the accuracy of the secondary-structure prediction of the query sequence. The most accurate alignments were obtained using template profiles constructed with the aid of structural alignments. In contrast, a simple sequence-to-sequence alignment algorithm, using a membrane protein-specific substitution matrix, shows no improvement in alignment accuracy. We suggest that profile-to-profile alignment methods should be adopted to maximize the accuracy of homology models of membrane proteins.     

Online homology modelling as a means of bridging the sequence-structure gap

For even the best-studied species, there is a large gap in their representation in the protein databank (PDB) compared to within sequence databases. Typically, less than 2% of sequences are represented in the PDB. This is partly due to the considerable experimental challenge and manual inputs required to solve three dimensional structures by methods such as X-ray diffraction and multi-dimensional nuclear magnetic resonance (NMR) spectroscopy in comparison to high-throughput sequencing. This gap is made even wider by the high level of redundancy within the PDB and under-representation of some protein categories such as membrane-associated proteins which comprise approximately 25% of proteins encoded in genomes. A traditional route to closing the sequence-structure gap is offered by homology modelling whereby the sequence of a target protein is modelled on a template represented in the PDB using in silico energy minimisation approaches. More recently, online homology servers have become available which automatically generate models from proffered sequences. However, many online servers give little indication of the structural plausibility of the generated model. In this paper, the online homology server Geno3D will be described. This server uses similar software to that used in modelling structures during structure determination and thus generates data allowing determination of the structural plausibility of models. For illustration, modelling of a chemotaxis protein (CheY) from Pseudomononas entomophila L48 (accession YP_609298) on a template (PDB id. 1mvo), the phosphorylation domain of an outer membrane protein PhoP from Bacillus subtilis, will be described.