Accuracy of structure-derived properties in simple comparative models of protein structures

Structure and oligomerization of the periplasmic domain of GspL from the type II secretion system of Pseudomonas aeruginosa

The ability of bacteria to infect a host relies in part on the secretion of molecular virulence factors across the cell envelope. Pseudomonas aeruginosa, a ubiquitous environmental bacterium causing opportunistic infections in humans, employs the type II secretion system (T2SS) to transport effector proteins across its cellular envelope as part of a diverse array of virulence strategies. General secretory pathway protein L (GspL) is an essential inner-membrane component of the T2SS apparatus, and is thought to facilitate transduction of the energy from ATP hydrolysis in the cytoplasm to the periplasmic components of the system. However, our incomplete understanding of the assembly principles of the T2SS machinery prevents the mechanistic deconvolution of T2SS-mediated protein secretion. Here we show via two crystal structures that the periplasmic ferredoxin-like domain of GspL (GspLfld) is a dimer stabilized by hydrophobic interactions, and that this interface may allow significant interdomain plasticity. The general dimerization mode of GspLfld is shared with GspL from Vibrio parahaemolyticus suggesting a conserved oligomerization mode across the GspL family. Furthermore, we identified a tetrameric form of the complete periplasmic segment of GspL (GspLperi) which indicates that GspL may be able to adopt multiple oligomeric states as part of its dynamic role in the T2SS apparatus.

Protein Structure Prediction Using Homology Modeling

Sequence-structure deficit marks one of the critical problems in today's scenario where high-throughput sequencing has resulted in large datasets of protein sequences but their corresponding 3D structures still needs to be determined. Homology modeling, also termed as Comparative modeling refers to modeling of 3D structure of a protein by exploiting structural information from other known protein structures with good sequence similarity. Homology models contain sufficient information about the spatial arrangement of important residues in the protein and are often used in drug design for screening of large libraries by molecular docking techniques. This chapter provides a brief description about protein tertiary structure prediction and Homology modeling. The authors provide a description of the steps involved in homology modeling protocols and provide information on the various resources available for the same.

Human, vector and parasite Hsp90 proteins: A comparative bioinformatics analysis

•

Cytosolic Hsp90s are more conserved than those from mitochondrial and ER.

•

Cell environment plays a role in the overall physicochemical properties of Hsp90s.

•

Serine and tyrosine are favored phosphorylated residues of Hsp90s.

•

Mitochondrial and ER Hsp90s have motifs unique to specific organisms.

The treatment of protozoan parasitic diseases is challenging, and thus identification and analysis of new drug targets is important. Parasites survive within host organisms, and some need intermediate hosts to complete their life cycle. Changing host environment puts stress on parasites, and often adaptation is accompanied by the expression of large amounts of heat shock proteins (Hsps). Among Hsps, Hsp90 proteins play an important role in stress environments. Yet, there has been little computational research on Hsp90 proteins to analyze them comparatively as potential parasitic drug targets. Here, an attempt was made to gain detailed insights into the differences between host, vector and parasitic Hsp90 proteins by large-scale bioinformatics analysis. A total of 104 Hsp90 sequences were divided into three groups based on their cellular localizations; namely cytosolic, mitochondrial and endoplasmic reticulum (ER). Further, the parasitic proteins were divided according to the type of parasite (protozoa, helminth and ectoparasite). Primary sequence analysis, phylogenetic tree calculations, motif analysis and physicochemical properties of Hsp90 proteins suggested that despite the overall structural conservation of these proteins, parasitic Hsp90 proteins have unique features which differentiate them from human ones, thus encouraging the idea that protozoan Hsp90 proteins should be further analyzed as potential drug targets.

Genomics and proteomics of mycobacteriophage patience, an accidental tourist in the Mycobacterium neighborhood

Newly emerging human viruses such as Ebola virus, severe acute respiratory syndrome (SARS) virus, and HIV likely originate within an extant population of viruses in nonhuman hosts and acquire the ability to infect and cause disease in humans. Although several mechanisms preventing viral infection of particular hosts have been described, the mechanisms and constraints on viral host expansion are ill defined. We describe here mycobacteriophage Patience, a newly isolated phage recovered using Mycobacterium smegmatis mc(2)155 as a host. Patience has genomic features distinct from its M. smegmatis host, including a much lower GC content (50.3% versus 67.4%) and an abundance of codons that are rarely used in M. smegmatis. Nonetheless, it propagates well in M. smegmatis, and we demonstrate the use of mass spectrometry to show expression of over 75% of the predicted proteins, to identify new genes, to refine the genome annotation, and to estimate protein abundance. We propose that Patience evolved primarily among lower-GC hosts and that the disparities between its genomic profile and that of M. smegmatis presented only a minimal barrier to host expansion. Rapid adaptions to its new host include recent acquisition of higher-GC genes, expression of out-of-frame proteins within predicted genes, and codon selection among highly expressed genes toward the translational apparatus of its new host.

IMPORTANCE

The mycobacteriophage Patience genome has a notably lower GC content (50.3%) than its Mycobacterium smegmatis host (67.4%) and has markedly different codon usage biases. The viral genome has an abundance of codons that are rare in the host and are decoded by wobble tRNA pairing, although the phage grows well and expression of most of the genes is detected by mass spectrometry. Patience thus has the genomic profile of a virus that evolved primarily in one type of host genetic landscape (moderate-GC bacteria) but has found its way into a distinctly different high-GC environment. Although Patience genes are ill matched to the host expression apparatus, this is of little functional consequence and has not evidently imposed a barrier to migration across the microbial landscape. Interestingly, comparison of expression levels and codon usage profiles reveals evidence of codon selection as the genome evolves and adapts to its new environment.

Comparative and genetic analysis of the four sequenced Paenibacillus polymyxa genomes reveals a diverse metabolism and conservation of genes relevant to plant-growth promotion and competitiveness

BACKGROUND

Members of the genus Paenibacillus are important plant growth-promoting rhizobacteria that can serve as bio-reactors. Paenibacillus polymyxa promotes the growth of a variety of economically important crops. Our lab recently completed the genome sequence of Paenibacillus polymyxa CR1. As of January 2014, four P. polymyxa genomes have been completely sequenced but no comparative genomic analyses have been reported.

RESULTS

Here we report the comparative and genetic analyses of four sequenced P. polymyxa genomes, which revealed a significantly conserved core genome. Complex metabolic pathways and regulatory networks were highly conserved and allow P. polymyxa to rapidly respond to dynamic environmental cues. Genes responsible for phytohormone synthesis, phosphate solubilization, iron acquisition, transcriptional regulation, σ-factors, stress responses, transporters and biomass degradation were well conserved, indicating an intimate association with plant hosts and the rhizosphere niche. In addition, genes responsible for antimicrobial resistance and non-ribosomal peptide/polyketide synthesis are present in both the core and accessory genome of each strain. Comparative analyses also reveal variations in the accessory genome, including large plasmids present in strains M1 and SC2. Furthermore, a considerable number of strain-specific genes and genomic islands are irregularly distributed throughout each genome. Although a variety of plant-growth promoting traits are encoded by all strains, only P. polymyxa CR1 encodes the unique nitrogen fixation cluster found in other Paenibacillus sp.

CONCLUSIONS

Our study revealed that genomic loci relevant to host interaction and ecological fitness are highly conserved within the P. polymyxa genomes analysed, despite variations in the accessory genome. This work suggets that plant-growth promotion by P. polymyxa is mediated largely through phytohormone production, increased nutrient availability and bio-control mechanisms. This study provides an in-depth understanding of the genome architecture of this species, thus facilitating future genetic engineering and applications in agriculture, industry and medicine. Furthermore, this study highlights the current gap in our understanding of complex plant biomass metabolism in Gram-positive bacteria.

Ball python nidovirus: a candidate etiologic agent for severe respiratory disease in Python regius

A severe, sometimes fatal respiratory disease has been observed in captive ball pythons (Python regius) since the late 1990s. In order to better understand this disease and its etiology, we collected case and control samples and performed pathological and diagnostic analyses. Electron micrographs revealed filamentous virus-like particles in lung epithelial cells of sick animals. Diagnostic testing for known pathogens did not identify an etiologic agent, so unbiased metagenomic sequencing was performed. Abundant nidovirus-like sequences were identified in cases and were used to assemble the genome of a previously unknown virus in the order Nidovirales. The nidoviruses, which were not previously known to infect nonavian reptiles, are a diverse order that includes important human and veterinary pathogens. The presence of the viral RNA was confirmed in all diseased animals (n = 8) but was not detected in healthy pythons or other snakes (n = 57). Viral RNA levels were generally highest in the lung and other respiratory tract tissues. The 33.5-kb viral genome is the largest RNA genome yet described and shares canonical characteristics with other nidovirus genomes, although several features distinguish this from related viruses. This virus, which we named ball python nidovirus (BPNV), will likely establish a new genus in Torovirinae subfamily. The identification of a novel nidovirus in reptiles contributes to our understanding of the biology and evolution of related viruses, and its association with lung disease in pythons is a promising step toward elucidating an etiology for this long-standing veterinary disease.

Ball pythons are popular pets because of their diverse coloration, generally nonaggressive behavior, and relatively small size. Since the 1990s, veterinarians have been aware of an infectious respiratory disease of unknown cause in ball pythons that can be fatal. We used unbiased shotgun sequencing to discover a novel virus in the order Nidovirales that was present in cases but not controls. While nidoviruses are known to infect a variety of animals, this is the first report of a nidovirus recovered from any reptile. This report will enable diagnostics that will assist in determining the role of this virus in the causation of disease, which would allow control of the disease in zoos and private collections. Given its evolutionary divergence from known nidoviruses and its unique host, the study of reptile nidoviruses may further our understanding of related diseases and the viruses that cause them in humans and other animals.

Complete genome sequences of nine mycobacteriophages

Genome analyses of a large number of mycobacteriophages, bacterial viruses that infect members of the genus Mycobacterium, yielded novel enzymes and tools for the genetic manipulation of mycobacteria. We report here the complete genome sequences of nine mycobacteriophages, including a new singleton, isolated using Mycobacterium smegmatis mc²155 as a host strain.

Preferential packing of acidic glycosidases and proteases into Bacteroides outer membrane vesicles

Outer membrane vesicles (OMV) are spherical membranous structures released from the outer membrane (OM) of Gram-negative bacteria. OMV have been proposed to play several different roles during both pathogenesis and symbiosis. Despite the fact that OMV were described several decades ago, their biogenesis is a poorly characterized process. Whether OMV are produced by an active mechanism or by passive disintegration of the OM is a still matter of controversy. Bacteroides fragilis and Bacteroides thetaiotaomicron are important members of the human microbiota. In this work, we determined and compared the protein compositions of OM and OMV from B. fragilis and B. thetaiotaomicron. SDS-PAGE analysis of both fractions revealed dramatically different protein profiles. Proteomic analysis of OM and OMV in B. fragilis identified more than 40 proteins found exclusively in OMV and more than 30 proteins detectable only in the OM. The OMV-specific proteome showed a high prevalence of glycosidases and proteases, some of which were shown to be active in vitro. Similar results were obtained for B. thetaiotaomicron. Most of the OMV-exclusive proteins were acidic. Based on these results, we propose that these species possess machinery devoted to selectively pack acidic proteins into the OMV. These OMV equipped with hydrolytic enzymes could help in securing nutrients for the benefit of the whole bacterial community present in the microbiota, uncovering a novel function for bacterial OMV. IMPORTANCE The members of genus Bacteroides are key players in the symbiosis between the human host and the gut microbiota. It is known for its ability to degrade a wide variety of glycans that are not substrates for human glycosidases. The cleaved glycans can be utilized by Bacteroides and other microbiota members, resulting in the production of short-chain fatty acids that are beneficial for the host. Although members of the genus Bacteroides are known to secrete different hydrolases, their secretion pathways remain uncharacterized. In this article, we show that B. fragilis and B. thetaiotaomicron preferentially pack a large number of hydrolases in outer membrane vesicles (OMV). Most of these hydrolases are acidic and were detected exclusively in OMV. This suggests the presence of a molecular mechanism in Bacteroides responsible for the selection of OMV proteins based on their charge. We propose that OMV contribute to the establishment and balance of the gut microbiota.

Comparative Modeling of Drug Target Proteins☆

In this perspective, we begin by describing the comparative protein structure modeling technique and the accuracy of the corresponding models. We then discuss the significant role that comparative prediction plays in drug discovery. We focus on virtual ligand screening against comparative models and illustrate the state-of-the-art by a number of specific examples.

Channelrhodopsins: a bioinformatics perspective

Channelrhodopsins are microbial-type rhodopsins that function as light-gated cation channels. Understanding how the detailed architecture of the protein governs its dynamics and specificity for ions is important, because it has the potential to assist in designing site-directed channelrhodopsin mutants for specific neurobiology applications. Here we use bioinformatics methods to derive accurate alignments of channelrhodopsin sequences, assess the sequence conservation patterns and find conserved motifs in channelrhodopsins, and use homology modeling to construct three-dimensional structural models of channelrhodopsins. The analyses reveal that helices C and D of channelrhodopsins contain Cys, Ser, and Thr groups that can engage in both intra- and inter-helical hydrogen bonds. We propose that these polar groups participate in inter-helical hydrogen-bonding clusters important for the protein conformational dynamics and for the local water interactions. This article is part of a Special Issue entitled: Retinal Proteins - You can teach an old dog new tricks.

Fractal nature of protein surface roughness: a note on quantification of change of surface roughness in active sites, before and after binding

Year 2010 marked the 25th year since we came to know that roughness of a protein surface has fractal symmetry. Ever since the publication of Lewis and Rees' paper, hundreds of works from a spectrum of perspectives have established that fractal dimension (FD) can be considered as a reliable marker that describes roughness of protein surface objectively. In this article, we introduce readers to the fundamentals of fractals and present categorical biophysical and geometrical reasons as to why FD-based constructs can describe protein surface roughness more accurately. We then review the commonality (and the lack of it) between numerous approaches that have attempted to investigate protein surface with fractal measures, before exploring the patterns in the results that they have produced. Apart from presenting the genealogy of approaches and results, we present an analysis that quantifies the difference in surface roughness in stretches of protein surface containing the active site, before and after binding to ligands, to underline the utility of FD-based measures further. It has been found that surface stretches containing the active site, in general, undergo a significant increment in its roughness after binding. After presenting the entire repertoire of FD-based surface roughness studies, we talk about two yet-unexplored problems where application of FD-based techniques can help in deciphering underlying patterns of surface interactions. Finally, we list the limitations of FD-based constructs and put down several precautions that one must take while working with them.

Protein structure prediction: challenging targets for CASP10

Functional characterization of proteins being one of the major issues in molecular biology is still unsolved due to several resource and technical limitations of experimental structure determination methods. A suitable methodology for accurate prediction of protein confirmations simply from sequence is therefore emerging as the primary modeling goal of researchers today. Global blind protein structure prediction summit, entitled Critical Assessment of Structure Prediction (CASP), critically assesses the modeling methodologies, to track our algorithmic path development. But our success is still impeded by incompetent modeling methodologies and several key technical lacunas. There is still a great need to focus some key issues for bridging the major though considered trivial gaps, in the upcoming CASP to pave and demarcate our correct way of developing a consistently accurate prediction methodology in the near future. Major problems resulting in divergence of our predicted models from their actual native states are thus highlighted with suggested more stringent and reliable assessment considerations in the CASP test.

A fast and precise approach for computational saturation mutagenesis and its experimental validation by using an artificial (βα)8-barrel protein

We present a computational saturation mutagenesis protocol (CoSM) that predicts the impact on stability of all possible amino acid substitutions for a given site at an internal protein interface. CoSM is an efficient algorithm that uses a combination of rotamer libraries, side-chain flips, energy minimization, and molecular dynamics equilibration. Because CoSM considers full side-chain and backbone flexibility in the local environment of the mutated position, amino acids larger than the wild-type residue are also modeled in a proper manner. To assess the performance of CoSM, the effect of point mutations on the stability of an artificial (βα)(8)-barrel protein that has been designed from identical (βα)(4)-half barrels, was studied. In this protein, position 234(N) is a previously identified stability hot-spot that is located at the interface of the two half barrels. By using CoSM, changes in protein stability were predicted for all possible single point mutations replacing wild-type Val234(N). In parallel, the stabilities of 14 representative mutants covering all amino acid classes were experimentally determined. A linear correlation of computationally and experimentally determined energy values yielded an R(2) value of 0.90, which is statistically significant. This degree of coherence is stronger than the ones we obtained for established computational methods of mutational analysis.

Systematic assessment of accuracy of comparative model of proteins belonging to different structural fold classes

In the absence of experimental structures, comparative modeling continues to be the chosen method for retrieving structural information on target proteins. However, models lack the accuracy of experimental structures. Alignment error and structural divergence (between target and template) influence model accuracy the most. Here, we examine the potential additional impact of backbone geometry, as our previous studies have suggested that the structural class (all-α, αβ, all-β) of a protein may influence the accuracy of its model. In the twilight zone (sequence identity ≤ 30%) and at a similar level of target-template divergence, the accuracy of protein models does indeed follow the trend all-α > αβ > all-β. This is mainly because the alignment accuracy follows the same trend (all-α > αβ > all-β), with backbone geometry playing only a minor role. Differences in the diversity of sequences belonging to different structural classes leads to the observed accuracy differences, thus enabling the accuracy of alignments/models to be estimated a priori in a class-dependent manner. This study provides a systematic description of and quantifies the structural class-dependent effect in comparative modeling. The study also suggests that datasets for large-scale sequence/structure analyses should have equal representations of different structural classes to avoid class-dependent bias.

Analysis of galactosemia-linked mutations of GALT enzyme using a computational biology approach

We describe the prediction of the structural and functional effects of mutations on the enzyme galactose-1-phosphate uridyltransferase related to the genetic disease galactosemia, using a fully computational approach. One hundred and seven single-point mutants were simulated starting from the structural model of the enzyme obtained by homology modeling methods. Several bioinformatics programs were then applied to each resulting mutant protein to analyze the effect of the mutations. The mutations have a direct effect on the active site, or on the dimer assembly and stability, or on the monomer stability. We describe how mutations may exert their effect at a molecular level by altering H-bonds, salt bridges, secondary structure or surface features. The alteration of protein stability, at level of monomer and/or dimer, is the main effect observed. We found an agreement between our results and the functional experimental data available in literature for some mutants. The data and analyses for all the mutants are fully available in the web-accessible database hosted at http://bioinformatica.isa.cnr.it/GALT.

A study of interface roughness of heteromeric obligate and non-obligate protein-protein complexes

A number of studies aimed to distinguish the structural patterns at the interfaces of obligate and non-obligate protein-protein complexes. These studies revealed better geometric complementarity of protomers in obligate complexes over non-obligates. We showed that protein surface roughness can be used to explain this observation. Using smoothened atomic fractal dimension (SAFD) as a descriptor, this work investigates the role of interface roughness in the molecular recognition of these two types of protein-protein complexes. We studied 52 obligate and 62 nonobligate heteromeric high quality crystal structures from benchmark data sets. We found that distribution of interface roughness values obligate and non-obligates are quite similar. However, we observed a distinct preference for obligate protomers to complex with chains having similar roughness. The roughness pairing is correlated in obligates only. The later indicates, an increase/decrease of roughness in one chain causes a proportional change in roughness in its binding partner. Based on these observations we proposed that similar and correlated roughness pairing leads to more interdigitation and contacts at the interface leading to better geometric fit in obligates. We propose that roughness information can find useful application in improving machine learning based complex type classifiers and filtering protein-protein docking solutions.

A novel method for predicting and using distance constraints of high accuracy for refining protein structure prediction

The principal bottleneck in protein structure prediction is the refinement of models from lower accuracies to the resolution observed by experiment. We developed a novel constraints-based refinement method that identifies a high number of accurate input constraints from initial models and rebuilds them using restrained torsion angle dynamics (rTAD). We previously created a Bayesian statistics-based residue-specific all-atom probability discriminatory function (RAPDF) to discriminate native-like models by measuring the probability of accuracy for atom type distances within a given model. Here, we exploit RAPDF to score (i.e., filter) constraints from initial predictions that may or may not be close to a native-like state, obtain consensus of top scoring constraints amongst five initial models, and compile sets with no redundant residue pair constraints. We find that this method consistently produces a large and highly accurate set of distance constraints from which to build refinement models. We further optimize the balance between accuracy and coverage of constraints by producing multiple structure sets using different constraint distance cutoffs, and note that the cutoff governs spatially near versus distant effects in model generation. This complete procedure of deriving distance constraints for rTAD simulations improves the quality of initial predictions significantly in all cases evaluated by us. Our procedure represents a significant step in solving the protein structure prediction and refinement problem, by enabling the use of consensus constraints, RAPDF, and rTAD for protein structure modeling and refinement.

Structural adaptation of serine hydroxymethyltransferase to low temperatures

Structural adaptation of serine hydroxymethyltransferase (SHMT), a pyridoxal-5'-phosphate dependent enzyme that catalyzes the reversible conversion of l-serine and tetrahydropteroylglutamate to glycine and 5,10-methylene-tetrahydropteroylglutamate, synthesized by microorganisms adapted to low temperatures has been analyzed using a comparative approach. The variations of amino acid properties and frequencies among three temperature populations (psychrophilic, mesophilic, hyper- and thermophilic) of SHMT sequences have been tested. SHMTs display a general increase of polarity specially in the core, a more negatively charged surface, and enhanced flexibility. Subunit interface is more hydrophilic and less compact. Electrostatic potential of the tetrahydrofolate binding site has been compared. The enzyme from Psychromonas ingrahamii, the organism with the lowest adaptation temperatures, displayed the most positive potential. In general, the property variations show a coherent opposite trend in the hyperthermophilic population: in particular, increase of hydrophobicity, packing and decrease of flexibility was observed.

Substrate specificity of plant UDP-dependent glycosyltransferases predicted from crystal structures and homology modeling

Plant family 1 UDP-dependent glycosyltransferases (UGTs) catalyze the glycosylation of a plethora of bioactive natural products. In Arabidopsis thaliana, 120 UGT encoding genes have been identified. The crystal-based 3D structures of four plant UGTs have recently been published. Despite low sequence conservation, the UGTs show a highly conserved secondary and tertiary structure. The sugar acceptor and sugar donor substrates of UGTs are accommodated in the cleft formed between the N- and C-terminal domains. Several regions of the primary sequence contribute to the formation of the substrate binding pocket including structurally conserved domains as well as loop regions differing both with respect to their amino acid sequence and sequence length. In this review we provide a detailed analysis of the available plant UGT crystal structures to reveal structural features determining substrate specificity. The high 3D structural conservation of the plant UGTs render homology modeling an attractive tool for structure elucidation. The accuracy and utility of UGT structures obtained by homology modeling are discussed and quantitative assessments of model quality are performed by modeling of a plant UGT for which the 3D crystal structure is known. We conclude that homology modeling offers a high degree of accuracy. Shortcomings in homology modeling are also apparent with modeling of loop regions remaining as a particularly difficult task.

Systematic analysis of the effect of multiple templates on the accuracy of comparative models of protein structure

Background

Although multiple templates are frequently used in comparative modeling, the effect of inclusion of additional template(s) on model accuracy (when compared to that of corresponding single-template based models) is not clear. To address this, we systematically analyze two-template models, the simplest case of multiple-template modeling. For an existing target-template pair (single-template modeling), a two-template based model of the target sequence is constructed by including an additional template without changing the original alignment to measure the effect of the second template on model accuracy.

Results

Even though in a large number of cases a two-template model showed higher accuracy than the corresponding one-template model, over the entire dataset only a marginal improvement was observed on average, as there were many cases where no change or the reverse change was observed. The increase in accuracy due to the structural complementarity of the templates increases at higher alignment accuracies. The combination of templates showing the highest potential for improvement is that where both templates share similar and low (less than 30%) sequence identity with the target, as well as low sequence identity with each other. The structural similarity between the templates also helps in identifying template combinations having a higher chance of resulting in an improved model.

Conclusion

Inclusion of additional template(s) does not necessarily improve model quality, but there are distinct combinations of the two templates, which can be selected a priori, that tend to show improvement in model quality over the single template model. The benefit derived from the structural complementarity is dependent on the accuracy of the modeling alignment. The study helps to explain the observation that a careful selection of templates together with an accurate target:template alignment are necessary to the benefit from using multiple templates in comparative modeling and provides guidelines to maximize the benefit from using multiple templates. This enables formulation of simple template selection rules to rank targets of a protein family in the context of structural genomics.

Electrostatic and functional analysis of the seven-bladed WD beta-propellers

beta-propeller domains composed of WD repeats are highly ubiquitous and typically used as multi-site docking platforms to coordinate and integrate the activities of groups of proteins. Here, we have used extensive homology modelling of the WD40-repeat family of seven-bladed beta-propellers coupled with subsequent structural classification and clustering of these models to define subfamilies of beta-propellers with common structural, and probable, functional characteristics. We show that it is possible to assign seven-bladed WD beta-propeller proteins into functionally different groups based on the information gained from homology modelling. We examine general structural diversity within the WD40-repeat family of seven-bladed beta-propellers and demonstrate that seven-bladed beta-propellers composed of WD-repeats are structurally distinct from other seven-bladed beta-propellers. We further provide some insights into the multifunctional diversity of the seven-bladed WD beta-propeller surfaces. This report once again reinforces the importance of structural data and the usefulness of homology models in functional classification.

Improving the accuracy of template-based predictions by mixing and matching between initial models

BACKGROUND

Comparative modeling is a technique to predict the three dimensional structure of a given protein sequence based primarily on its alignment to one or more proteins with experimentally determined structures. A major bottleneck of current comparative modeling methods is the lack of methods to accurately refine a starting initial model so that it approaches the resolution of the corresponding experimental structure. We investigate the effectiveness of a graph-theoretic clique finding approach to solve this problem.

RESULTS

Our method takes into account the information presented in multiple templates/alignments at the three-dimensional level by mixing and matching regions between different initial comparative models. This method enables us to obtain an optimized conformation ensemble representing the best combination of secondary structures, resulting in the refined models of higher quality. In addition, the process of mixing and matching accumulates near-native conformations, resulting in discriminating the native-like conformation in a more effective manner. In the seventh Critical Assessment of Structure Prediction (CASP7) experiment, the refined models produced are more accurate than the starting initial models.

CONCLUSION

This novel approach can be applied without any manual intervention to improve the quality of comparative predictions where multiple template/alignment combinations are available for modeling, producing conformational models of higher quality than the starting initial predictions.

An efficient conformational sampling method for homology modeling

The structural refinement of protein models is a challenging problem in protein structure prediction (Moult et al., Proteins 2003;53(Suppl 6):334-339). Most attempts to refine comparative models lead to degradation rather than improvement in model quality, so most current comparative modeling procedures omit the refinement step. However, it has been shown that even in the absence of alignment errors and using optimal templates, methods based on a single template have intrinsic limitations, and that refinement is needed to improve model accuracy. It is thought that failure of current methods originates on one hand from the inaccuracy of the effective free energy functions adopted, which do not represent properly the energetic balance in the native state, and on the other hand from the difficulty to sample the high dimensional and rugged free energy landscape of protein folding, in the search for the global minimum. Here, we address this second issue. We define the evolutionary and vibrational armonics subspace (EVA), a reduced sampling subspace that consists of a combination of evolutionarily favored directions, defined by the principal components of the structural variation within a homologous family, plus topologically favored directions, derived from the low frequency normal modes of the vibrational dynamics, up to 50 dimensions. This subspace is accurate enough so that the cores of most proteins can be represented within 1 A accuracy, and reduced enough so that Replica Exchange Monte Carlo (Hukushima and Nemoto, J Phys Soc Jpn 1996;65:1604-1608; Hukushima et al., Int J Mod Phys C: Phys Comput 1996;7:337-344; Mitsutake et al., J Chem Phys 2003;118:6664-6675; Mitsutake et al., J Chem Phys 2003;118:6676-6688) (REMC) can be applied. REMC is one of the best sampling methods currently available, but its applicability is restricted to spaces of small dimensionality. We show that the combination of the EVA subspace and REMC can essentially solve the optimization problem for backbone atoms in the reduced sampling subspace, even for rather rugged free energy landscapes. Applications and limitations of this methodology are finally discussed.

Preservation of protein clefts in comparative models

BACKGROUND

Comparative, or homology, modelling of protein structures is the most widely used prediction method when the target protein has homologues of known structure. Given that the quality of a model may vary greatly, several studies have been devoted to identifying the factors that influence modelling results. These studies usually consider the protein as a whole, and only a few provide a separate discussion of the behaviour of biologically relevant features of the protein. Given the value of the latter for many applications, here we extended previous work by analysing the preservation of native protein clefts in homology models. We chose to examine clefts because of their role in protein function/structure, as they are usually the locus of protein-protein interactions, host the enzymes' active site, or, in the case of protein domains, can also be the locus of domain-domain interactions that lead to the structure of the whole protein.

RESULTS

We studied how the largest cleft of a protein varies in comparative models. To this end, we analysed a set of 53507 homology models that cover the whole sequence identity range, with a special emphasis on medium and low similarities. More precisely we examined how cleft quality - measured using six complementary parameters related to both global shape and local atomic environment, depends on the sequence identity between target and template proteins. In addition to this general analysis, we also explored the impact of a number of factors on cleft quality, and found that the relationship between quality and sequence identity varies depending on cleft rank amongst the set of protein clefts (when ordered according to size), and number of aligned residues.

CONCLUSION

We have examined cleft quality in homology models at a range of seq.id. levels. Our results provide a detailed view of how quality is affected by distinct parameters and thus may help the user of comparative modelling to determine the final quality and applicability of his/her cleft models. In addition, the large variability in model quality that we observed within each sequence bin, with good models present even at low sequence identities (between 20% and 30%), indicates that properly developed identification methods could be used to recover good cleft models in this sequence range.

Pspace: a program that assesses protein space

Background

We describe a computer program named Pspace designed to a) obtain a reliable basis for the description of three-dimensional structures of a given protein family using homology modeling through selection of an optimal subset of the protein family whose structure would be determined experimentally; and b) aid in the search of orthologs by matching two sets of sequences in three different ways.

Methods

The prioritization is established dynamically as new sequences and new structures are becoming available through ranking proteins by their value in providing structural information about the rest of the family set. The matching can give a list of potential orthologs or it can deduce an overall optimal matching of two sets of sequences.

Results

The various covering strategies and ortholog searches are tested on the bromodomain family.

Conclusion

The possibility of extending this approach to the space of all proteins is discussed.

Comparative Modeling of Drug Target Proteins

In this perspective, we begin by describing the comparative protein structure modeling technique and the accuracy of the corresponding models. We then discuss the significant role that comparative prediction plays in drug discovery. We focus on virtual ligand screening against comparative models and illustrate the state of the art by a number of specific examples.

Understanding the cell in terms of structure and function: insights from structural genomics

Structural genomics programs are only now moving into the large-scale production phase, yet have already produced around 2000 protein structures. Through a widespread if not exclusive emphasis on structural novelty, our knowledge of the protein fold universe is improving rapidly. With this information comes the challenge of structure-based function annotation for the many target proteins about which little or nothing is known. Recent years have therefore seen the emergence of impressively diverse bioinformatics approaches to predict the function of a protein structure. Attention is now turning to means of combining these predictions with information from various other sources.

Local binding with globally distributed changes in a small protease inhibitor upon enzyme binding

Complexation of the small serine protease inhibitor Schistocerca gregaria chymotrypsin inhibitor (SGCI), a member of the pacifastin inhibitor family, with bovine chymotrypsin was followed by NMR spectroscopy. (1)H-(15)N correlation (HSQC) spectra of the inhibitor with increasing amounts of the enzyme reveal tight and specific binding in agreement with biochemical data. Unexpectedly, and unparalleled among canonical serine protease inhibitors, not only residues in the protease-binding loop of the inhibitor, but also some segments of it located spatially far from the substrate-binding cleft of the enzyme were affected by complexation. However, besides changes, some of the dynamical features of the free inhibitor are retained in the complex. Comparison of the free and complexed inhibitor structures revealed that most, but not all, of the observed chemical shift changes can be attributed to minor structural transitions. We suggest that the classical 'scaffold + binding loop' model of canonical inhibitors might not be fully valid for the inhibitor family studied. In our view, this feature allows for the emergence of both taxon-specific and nontaxon-specific inhibitors in this group of small proteins.

Comparative modeling for protein structure prediction

With the progression of structural genomics projects, comparative modeling remains an increasingly important method of choice. It helps to bridge the gap between the available sequence and structure information by providing reliable and accurate protein models. Comparative modeling based on more than 30% sequence identity is now approaching its natural template-based limits and further improvements require the development of effective refinement techniques capable of driving models toward native structure. For difficult targets, for which the most significant progress in recent years has been observed, optimal template selection and alignment accuracy are still the major problems.

Mode of action and biochemical characterization of REP8839, a novel inhibitor of methionyl-tRNA synthetase

Aminoacyl-tRNA synthetases have attracted interest as essential and novel targets involved in bacterial protein synthesis. REP8839 is a potent inhibitor of MetS, the methionyl-tRNA synthetase in Staphylococcus aureus, including methicillin-resistant S. aureus (MRSA), and in Streptococcus pyogenes. The biochemical activity of REP8839 was shown by specific inhibition of purified S. aureus MetS (50% inhibitory concentration, <1.9 nM). Target specificity was confirmed by overexpression of the metS gene in S. aureus, resulting in an eightfold increase in the MIC for REP8839. Macromolecular synthesis assays in the presence of REP8839 demonstrated a dose-dependent inhibition of protein synthesis and RNA synthesis in S. pneumoniae R6, but only protein synthesis was affected in an isogenic rel mutant deficient in the stringent response. Strains with reduced susceptibility to REP8839 were generated by selection of strains with spontaneous mutations and through serial passages. Point mutations within the metS gene were mapped, leading to a total of 23 different amino acid substitutions within MetS that were located around the modeled active site. The most frequent MetS mutations were I57N, leading to a shift in the MIC from 0.06 microg/ml to 4 microg/ml, and G54S, resulting in a MIC of 32 microg/ml that was associated with a reduced growth rate. The mutation prevention concentration was 32 microg/ml in four S. aureus strains (methicillin-sensitive S. aureus and MRSA), which is well below the drug concentration of 2% (20,000 microg/ml) in a topical formulation. In conclusion, we demonstrate by biochemical, physiologic, and genetic mode-of-action studies that REP8839 exerts its antibacterial activity through specific inhibition of MetS, a novel target.