Evolutionary Diversification of Host-Targeted Bartonella Effectors Proteins Derived from a Conserved FicTA Toxin-Antitoxin Module.

Proteins containing a FIC domain catalyze AMPylation and other post-translational modifications (PTMs). In bacteria, they are typically part of FicTA toxin-antitoxin modules that control conserved biochemical processes such as topoisomerase activity, but they have also repeatedly diversified into host-targeted virulence factors. Among these, Bartonella effector proteins (Beps) comprise a particularly diverse ensemble of FIC domains that subvert various host cellular functions. However, no comprehensive comparative analysis has been performed to infer molecular mechanisms underlying the biochemical and functional diversification of FIC domains in the vast Bep family. Here, we used X-ray crystallography, structural modelling, and phylogenetic analyses to unravel the expansion and diversification of Bep repertoires that evolved in parallel in three Bartonella lineages from a single ancestral FicTA toxin-antitoxin module. Our analysis is based on 99 non-redundant Bep sequences and nine crystal structures. Inferred from the conservation of the FIC signature motif that comprises the catalytic histidine and residues involved in substrate binding, about half of them represent AMP transferases. A quarter of Beps show a glutamate in a strategic position in the putative substrate binding pocket that would interfere with triphosphate-nucleotide binding but may allow binding of an AMPylated target for deAMPylation or another substrate to catalyze a distinct PTM. The ß-hairpin flap that registers the modifiable target segment to the active site exhibits remarkable structural variability. The corresponding sequences form few well-defined groups that may recognize distinct target proteins. The binding of Beps to promiscuous FicA antitoxins is well conserved, indicating a role of the antitoxin to inhibit enzymatic activity or to serve as a chaperone for the FIC domain before translocation of the Bep into host cells. Taken together, our analysis indicates a remarkable functional plasticity of Beps that is mostly brought about by structural changes in the substrate pocket and the target dock. These findings may guide future structure-function analyses of the highly versatile FIC domains.

SWISS-MODEL: homology modelling of protein structures and complexes.

Homology modelling has matured into an important technique in structural biology, significantly contributing to narrowing the gap between known protein sequences and experimentally determined structures. Fully automated workflows and servers simplify and streamline the homology modelling process, also allowing users without a specific computational expertise to generate reliable protein models and have easy access to modelling results, their visualization and interpretation. Here, we present an update to the SWISS-MODEL server, which pioneered the field of automated modelling 25 years ago and been continuously further developed. Recently, its functionality has been extended to the modelling of homo- and heteromeric complexes. Starting from the amino acid sequences of the interacting proteins, both the stoichiometry and the overall structure of the complex are inferred by homology modelling. Other major improvements include the implementation of a new modelling engine, ProMod3 and the introduction a new local model quality estimation method, QMEANDisCo. SWISS-MODEL is freely available at https://swissmodel.expasy.org.

A computational protocol to evaluate the effects of protein mutants in the kinase gatekeeper position on the binding of ATP substrate analogues.

BACKGROUND: The determination of specific kinase substrates in vivo is challenging due to the large number of protein kinases in cells, their substrate specificity overlap, and the lack of highly specific inhibitors. In the late 90s, Shokat and coworkers developed a protein engineering-based method addressing the question of identification of substrates of protein kinases. The approach was based on the mutagenesis of the gatekeeper residue within the binding site of a protein kinase to change the co-substrate specificity from ATP to ATP analogues. One of the challenges in applying this method to other kinase systems is to identify the optimal combination of mutation in the enzyme and chemical derivative such that the ATP analogue acts as substrate for the engineered, but not the native kinase enzyme. In this study, we developed a computational protocol for estimating the effect of mutations at the gatekeeper position on the accessibility of ATP analogues within the binding site of engineered kinases. RESULTS: We tested the protocol on a dataset of tyrosine and serine/threonine protein kinases from the scientific literature where Shokat's method was applied and experimental data were available. Our protocol correctly identified gatekeeper residues as the positions to mutate within the binding site of the studied kinase enzymes. Furthermore, the approach well reproduced the experimental data available in literature. CONCLUSIONS: We have presented a computational protocol that scores how different mutations at the gatekeeper position influence the accommodation of various ATP analogues within the binding site of protein kinases. We have assessed our approach on protein kinases from the scientific literature and have verified the ability of the approach to well reproduce the available experimental data and identify suitable combinations of engineered kinases and ATP analogues.

The SWISS-MODEL Repository-new features and functionality.

SWISS-MODEL Repository (SMR) is a database of annotated 3D protein structure models generated by the automated SWISS-MODEL homology modeling pipeline. It currently holds >400 000 high quality models covering almost 20% of Swiss-Prot/UniProtKB entries. In this manuscript, we provide an update of features and functionalities which have been implemented recently. We address improvements in target coverage, model quality estimates, functional annotations and improved in-page visualization. We also introduce a new update concept which includes regular updates of an expanded set of core organism models and UniProtKB-based targets, complemented by user-driven on-demand update of individual models. With the new release of the modeling pipeline, SMR has implemented a REST-API and adopted an open licencing model for accessing model coordinates, thus enabling bulk download for groups of targets fostering re-use of models in other contexts. SMR can be accessed at https://swissmodel.expasy.org/repository.

The BID Domain of Type IV Secretion Substrates Forms a Conserved Four-Helix Bundle Topped with a Hook.

The BID (Bep intracellular delivery) domain functions as secretion signal in a subfamily of protein substrates of bacterial type IV secretion (T4S) systems. It mediates transfer of (1) relaxases and the attached DNA during bacterial conjugation, and (2) numerous Bartonella effector proteins (Beps) during protein transfer into host cells infected by pathogenic Bartonella species. Furthermore, BID domains of Beps have often evolved secondary effector functions within host cells. Here, we provide crystal structures for three representative BID domains and describe a novel conserved fold characterized by a compact, antiparallel four-helix bundle topped with a hook. The conserved hydrophobic core provides a rigid scaffold to a surface that, despite a few conserved exposed residues and similarities in charge distribution, displays significant variability. We propose that the genuine function of BID domains as T4S signal may primarily depend on their rigid structure, while the plasticity of their surface may facilitate adaptation to secondary effector functions.

Synthesis of empty african horse sickness virus particles.

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 core-like 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.

Insight into neutral and disease-associated human genetic variants through interpretable predictors.

A variety of methods that predict human nonsynonymous single nucleotide polymorphisms (SNPs) to be neutral or disease-associated have been developed over the last decade. These methods are used for pinpointing disease-associated variants in the many variants obtained with next-generation sequencing technologies. The high performances of current sequence-based predictors indicate that sequence data contains valuable information about a variant being neutral or disease-associated. However, most predictors do not readily disclose this information, and so it remains unclear what sequence properties are most important. Here, we show how we can obtain insight into sequence characteristics of variants and their surroundings by interpreting predictors. We used an extensive range of features derived from the variant itself, its surrounding sequence, sequence conservation, and sequence annotation, and employed linear support vector machine classifiers to enable extracting feature importance from trained predictors. Our approach is useful for providing additional information about what features are most important for the predictions made. Furthermore, for large sets of known variants, it can provide insight into the mechanisms responsible for variants being disease-associated.

The Catalytic Site Atlas 2.0: cataloging catalytic sites and residues identified in enzymes.

Understanding which are the catalytic residues in an enzyme and what function they perform is crucial to many biology studies, particularly those leading to new therapeutics and enzyme design. The original version of the Catalytic Site Atlas (CSA) (http://www.ebi.ac.uk/thornton-srv/databases/CSA) published in 2004, which catalogs the residues involved in enzyme catalysis in experimentally determined protein structures, had only 177 curated entries and employed a simplistic approach to expanding these annotations to homologous enzyme structures. Here we present a new version of the CSA (CSA 2.0), which greatly expands the number of both curated (968) and automatically annotated catalytic sites in enzyme structures, utilizing a new method for annotation transfer. The curated entries are used, along with the variation in residue type from the sequence comparison, to generate 3D templates of the catalytic sites, which in turn can be used to find catalytic sites in new structures. To ease the transfer of CSA annotations to other resources a new ontology has been developed: the Enzyme Mechanism Ontology, which has permitted the transfer of annotations to Mechanism, Annotation and Classification in Enzymes (MACiE) and UniProt Knowledge Base (UniProtKB) resources. The CSA database schema has been re-designed and both the CSA data and search capabilities are presented in a new modern web interface.

PDBsum additions.

PDBsum, http://www.ebi.ac.uk/pdbsum, is a website providing numerous pictorial analyses of each entry in the Protein Data Bank. It portrays the structural features of all proteins, DNA and ligands in the entry, as well as depicting the interactions between them. The latest features, described here, include annotation of human protein sequences with their naturally occurring amino acid variants, dynamic graphs showing the relationships between related protein domain architectures, analyses of ligand binding clusters across different experimental determinations of the same protein, analyses of tunnels in proteins and new search options.

Amino acid changes in disease-associated variants differ radically from variants observed in the 1000 genomes project dataset.

The 1000 Genomes Project data provides a natural background dataset for amino acid germline mutations in humans. Since the direction of mutation is known, the amino acid exchange matrix generated from the observed nucleotide variants is asymmetric and the mutabilities of the different amino acids are very different. These differences predominantly reflect preferences for nucleotide mutations in the DNA (especially the high mutation rate of the CpG dinucleotide, which makes arginine mutability very much higher than other amino acids) rather than selection imposed by protein structure constraints, although there is evidence for the latter as well. The variants occur predominantly on the surface of proteins (82%), with a slight preference for sites which are more exposed and less well conserved than random. Mutations to functional residues occur about half as often as expected by chance. The disease-associated amino acid variant distributions in OMIM are radically different from those expected on the basis of the 1000 Genomes dataset. The disease-associated variants preferentially occur in more conserved sites, compared to 1000 Genomes mutations. Many of the amino acid exchange profiles appear to exhibit an anti-correlation, with common exchanges in one dataset being rare in the other. Disease-associated variants exhibit more extreme differences in amino acid size and hydrophobicity. More modelling of the mutational processes at the nucleotide level is needed, but these observations should contribute to an improved prediction of the effects of specific variants in humans.

LigSearch: a knowledge-based web server to identify likely ligands for a protein target.

Identifying which ligands might bind to a protein before crystallization trials could provide a significant saving in time and resources. LigSearch, a web server aimed at predicting ligands that might bind to and stabilize a given protein, has been developed. Using a protein sequence and/or structure, the system searches against a variety of databases, combining available knowledge, and provides a clustered and ranked output of possible ligands. LigSearch can be accessed at http://www.ebi.ac.uk/thornton-srv/databases/LigSearch.

Analysis of SAT type foot-and-mouth disease virus capsid proteins and the identification of putative amino acid residues affecting virus stability.

Foot-and-mouth disease virus (FMDV) initiates infection by adhering to integrin receptors on target cells, followed by cell entry and disassembly of the virion through acidification within endosomes. Mild heating of the virions also leads to irreversible dissociation into pentamers, a characteristic linked to reduced vaccine efficacy. In this study, the structural stability of intra- and inter-serotype chimeric SAT2 and SAT3 virus particles to various conditions including low pH, mild temperatures or high ionic strength, was compared. Our results demonstrated that while both the SAT2 and SAT3 infectious capsids displayed different sensitivities in a series of low pH buffers, their stability profiles were comparable at high temperatures or high ionic strength conditions. Recombinant vSAT2 and intra-serotype chimeric viruses were used to map the amino acid differences in the capsid proteins of viruses with disparate low pH stabilities. Four His residues at the inter-pentamer interface were identified that change protonation states at pH 6.0. Of these, the H145 of VP3 appears to be involved in interactions with A141 in VP3 and K63 in VP2, and may be involved in orientating H142 of VP3 for interaction at the inter-pentamer interfaces.

Current challenges in genome annotation through structural biology and bioinformatics.

With the huge volume in genomic sequences being generated from high-throughout sequencing projects the requirement for providing accurate and detailed annotations of gene products has never been greater. It is proving to be a huge challenge for computational biologists to use as much information as possible from experimental data to provide annotations for genome data of unknown function. A central component to this process is to use experimentally determined structures, which provide a means to detect homology that is not discernable from just the sequence and permit the consequences of genomic variation to be realized at the molecular level. In particular, structures also form the basis of many bioinformatics methods for improving the detailed functional annotations of enzymes in combination with similarities in sequence and chemistry.

1,000 structures and more from the MCSG.

BACKGROUND: The Midwest Center for Structural Genomics (MCSG) is one of the large-scale centres of the Protein Structure Initiative (PSI). During the first two phases of the PSI the MCSG has solved over a thousand protein structures. A criticism of structural genomics is that target selection strategies mean that some structures are solved without having a known function and thus are of little biomedical significance. Structures of unknown function have stimulated the development of methods for function prediction from structure. RESULTS: We show that the MCSG has met the stated goals of the PSI and use online resources and readily available function prediction methods to provide functional annotations for more than 90% of the MCSG structures. The structure-to-function prediction method ProFunc provides likely functions for many of the MCSG structures that cannot be annotated by sequence-based methods. CONCLUSIONS: Although the focus of the PSI was structural coverage, many of the structures solved by the MCSG can also be associated with functional classes and biological roles of possible biomedical value.

Sequence-based prediction for vaccine strain selection and identification of antigenic variability in foot-and-mouth disease virus.

Identifying when past exposure to an infectious disease will protect against newly emerging strains is central to understanding the spread and the severity of epidemics, but the prediction of viral cross-protection remains an important unsolved problem. For foot-and-mouth disease virus (FMDV) research in particular, improved methods for predicting this cross-protection are critical for predicting the severity of outbreaks within endemic settings where multiple serotypes and subtypes commonly co-circulate, as well as for deciding whether appropriate vaccine(s) exist and how much they could mitigate the effects of any outbreak. To identify antigenic relationships and their predictors, we used linear mixed effects models to account for variation in pairwise cross-neutralization titres using only viral sequences and structural data. We identified those substitutions in surface-exposed structural proteins that are correlates of loss of cross-reactivity. These allowed prediction of both the best vaccine match for any single virus and the breadth of coverage of new vaccine candidates from their capsid sequences as effectively as or better than serology. Sub-sequences chosen by the model-building process all contained sites that are known epitopes on other serotypes. Furthermore, for the SAT1 serotype, for which epitopes have never previously been identified, we provide strong evidence--by controlling for phylogenetic structure--for the presence of three epitopes across a panel of viruses and quantify the relative significance of some individual residues in determining cross-neutralization. Identifying and quantifying the importance of sites that predict viral strain cross-reactivity not just for single viruses but across entire serotypes can help in the design of vaccines with better targeting and broader coverage. These techniques can be generalized to any infectious agents where cross-reactivity assays have been carried out. As the parameterization uses pre-existing datasets, this approach quickly and cheaply increases both our understanding of antigenic relationships and our power to control disease.

Mapping of amino acid residues responsible for adhesion of cell culture-adapted foot-and-mouth disease SAT type viruses.

Foot-and-mouth disease virus (FMDV) infects host cells by adhering to the alpha(V) subgroup of the integrin family of cellular receptors in a Arg-Gly-Asp (RGD) dependent manner. FMD viruses, propagated in non-host cell cultures are reported to acquire the ability to enter cells via alternative cell surface molecules. Sequencing analysis of SAT1 and SAT2 cell culture-adapted variants showed acquisition of positively charged amino acid residues within surface-exposed loops of the outer capsid structural proteins. The fixation of positively charged residues at position 110-112 in the beta F-beta G loop of VP1 of SAT1 isolates is thought to correlate with the acquisition of the ability to utilise alternative glycosaminoglycan (GAG) molecules for cell entry. Similarly, two SAT2 viruses that adapted readily to BHK-21 cells accumulated positively charged residues at positions 83 and 85 of the beta D-beta E loop of VP1. Both regions surround the fivefold axis of the virion. Recombinant viruses containing positively charged residues at position 110 and 112 of VP1 were able to infect CHO-K1 cells (that expresses GAG) and demonstrated increased infectivity in BHK-21 cells. Therefore, recombinant SAT viruses engineered to express substitutions that induce GAG-binding could be exploited in the rational design of vaccine seed stocks with improved growth properties in cell cultures.

The malarial drug target Plasmodium falciparum 1-deoxy-D-xylulose-5-phosphate reductoisomerase (PfDXR): development of a 3-D model for identification of novel, structural and functional features and for inhibitor screening.

A three-dimensional model of the malarial drug target protein PfDXR was generated, and validated using structure-checking programs and protein docking studies. Structural and functional features unique to PfDXR were identified using the model and comparative sequence analyses with apicomplexan and non-apicomplexan DXR proteins. Furthermore, we have used the model to develop an efficient approach to screen for potential tool compounds for use in the rational design of novel DXR inhibitors.

Discovery: an interactive resource for the rational selection and comparison of putative drug target proteins in malaria.

BACKGROUND: Up to half a billion human clinical cases of malaria are reported each year, resulting in about 2.7 million deaths, most of which occur in sub-Saharan Africa. Due to the over-and misuse of anti-malarials, widespread resistance to all the known drugs is increasing at an alarming rate. Rational methods to select new drug target proteins and lead compounds are urgently needed. The Discovery system provides data mining functionality on extensive annotations of five malaria species together with the human and mosquito hosts, enabling the selection of new targets based on multiple protein and ligand properties. METHODS: A web-based system was developed where researchers are able to mine information on malaria proteins and predicted ligands, as well as perform comparisons to the human and mosquito host characteristics. Protein features used include: domains, motifs, EC numbers, GO terms, orthologs, protein-protein interactions, protein-ligand interactions and host-pathogen interactions among others. Searching by chemical structure is also available. RESULTS: An in silico system for the selection of putative drug targets and lead compounds is presented, together with an example study on the bifunctional DHFR-TS from Plasmodium falciparum. CONCLUSION: The Discovery system allows for the identification of putative drug targets and lead compounds in Plasmodium species based on the filtering of protein and chemical properties.

Structure-function study of a Plasmodium falciparum Hsp70 using three dimensional modelling and in vitro analyses.

The spatial orientation of domains of the heat shock protein 70 from Plasmodium falciparum (PfHsp70) were mapped based on a three-dimensional model of the protein. Purified PfHsp70 displayed chaperone activity in vitro. Amino acid substitutions introduced in the chaperone's substrate binding cavity compromised the protein's chaperone function.

Elucidation of sulfadoxine resistance with structural models of the bifunctional Plasmodium falciparum dihydropterin pyrophosphokinase-dihydropteroate synthase.

Resistance of the most virulent human malaria parasite, Plasmodium falciparum, to antifolates is spreading with increasing speed, especially in Africa. Antifolate resistance is mainly caused by point mutations in the P. falciparum dihydropteroate synthase (DHPS) and dihydrofolate reductase (DHFR) target proteins. Homology models of the bifunctional P. falciparum dihydropterin pyrophosphokinase-dihydropteroate synthase (PPPK-DHPS) enzyme as well as the separate domains complete with bound substrates were constructed using the crystal structures of Saccharomyces cerevisiae (PPPK-DHPS), Mycobacterium tuberculosis (DHPS), Bacillus anthracis (DHPS), and Escherichia coli (PPPK) as templates. The resulting structures were subsequently solvated and refined using molecular dynamics. The active site residues of DHPS are highly conserved in S. cerevisiae, M. tuberculosis, E. coli, S. aureus, and B. anthracis, an attribute also shared by P. falciparum DHPS. Sulfadoxine was superimposed into the equivalent position of the p-aminobenzoic acid substrate and its binding parameters were refined using minimization and molecular dynamics. Sulfadoxine appears to interact mainly with P. falciparum DHPS mainly through hydrophobic interactions. Rational explanations are provided by the model for the sulfadoxine resistance-causing effects of four of the five known mutations in P. falciparum DHPS. A possible structure for the bifunctional PPPK-DHPS was derived from the structure from the S. cerevisiae bifunctional enzyme. The active site residues of P. falciparum PPPK are also conserved when compared to S. cerevisiae, Haemophilus influenzae, and E. coli. The informative nature of these models opens up avenues for structure-based drug design approaches toward the development of alternative and more effective inhibitors of P. falciparum PPPK-DHPS.