GP0.4 from bacteriophage T7: in silico characterisation of its structure and interaction with E. coli FtsZ
© The Author(s) 2016
Received: 21 January 2016
Accepted: 6 July 2016
Published: 13 July 2016
Proteins produced by bacteriophages can have potent antimicrobial activity. The study of phage-host interactions can therefore inform small molecule drug discovery by revealing and characterising new drug targets. Here we characterise in silico the predicted interaction of gene protein 0.4 (GP0.4) from the Escherichia coli (E. coli) phage T7 with E. coli filamenting temperature-sensitive mutant Z division protein (FtsZ). FtsZ is a tubulin homolog which plays a key role in bacterial cell division and that has been proposed as a drug target.
Using ab initio, fragment assembly structure modelling, we predicted the structure of GP0.4 with two programs. A structure similarity-based network was used to identify a U-shaped helix-turn-helix candidate fold as being favoured. ClusPro was used to dock this structure prediction to a homology model of E. coli FtsZ resulting in a favourable predicted interaction mode. Alternative docking methods supported the proposed mode which offered an immediate explanation for the anti-filamenting activity of GP0.4. Importantly, further strong support derived from a previously characterised insertion mutation, known to abolish GP0.4 activity, that is positioned in close proximity to the proposed GP0.4/FtsZ interface.
The mode of interaction predicted by bioinformatics techniques strongly suggests a mechanism through which GP0.4 inhibits FtsZ and further establishes the latter’s druggable intrafilament interface as a potential drug target.
Resistance to antibiotics has become a source of great public concern recently, compounded by the slow emergence of new antibiotics . One possible solution may be phage therapy. Bacteriophages (referred to hereafter as phages) are among the simplest and most abundant types of microorganisms , and have been used therapeutically for close to a century. With the advent of antibiotics, the use of phages therapeutically has decreased in the western world. However, as resistance to antibiotics becomes a pressing issue, phages are once again being seen as a way to combat disease [3, 4].
There are several advantages to the therapeutic use of phages; they affect highly specific targets that minimise collateral damage , they can target bacterial strains resistant to antibiotics, and they can be used to supplement the effects of antibiotics . Phages are, however, not without problems. For example, the delivery of phages is a major challenge, with the immune system presenting a large hurdle  and the use of phages as a delivery method requires accurate diagnosis of the disease-causing bacteria and therefore slows down treatment.
Study of phage-host interaction can also inform small molecule drug discovery by revealing new drug targets and pinpointing their weaknesses. Proteins in phages have naturally evolved to find effective methods to disrupt bacteria. Furthermore, in multi-protein complexes involved in processes such as cell regulation, small numbers of amino acids form hotspots which contribute most of the free energy during interactions . By studying how phage proteins disrupt the protein–protein interfaces, we can identify potential hotspots and target them when designing drugs. Such drugs would dispense with the specificity limitation of the original phage since they can be designed to target broadly conserved bacterial mechanisms potentially rendering unnecessary the diagnosis of the specific pathogenic bacterium [8, 9].
Upon infection of bacteria, phages take over the host resources through the actions of proteins expressed early in the infection. One such protein from the Escherichia coli phage T7 is gene protein (GP) 0.4. GP0.4 directly inhibits the filamenting temperature-sensitive mutant Z division protein (FtsZ) of E. coli by preventing its assembly into protofilaments both in vivo and in vitro .
FtsZ is a tubulin homologue that plays a key role in the division of bacteria cells [11–13]. Much like tubulin, purified FtsZ binds and hydrolyses GTP . GTP binding induces the FtsZ to polymerise into one of two polar protofilament conformations; straight or gently curved [11–15]. Between FtsZ monomers, an active site is formed which hydrolyses the GTP, and remains accessible to the GTP-rich cytoplasm [13, 15]. Therefore GTP binding can be rapidly restored allowing protofilaments to consist of mostly FtsZ-GTP subunits resistant to depolymerisation . The FtsZ protofilaments associate laterally to form bundles or sheets [11, 13]. As the protofilaments bundle together they form the Z ring at the site of cytokinesis. Once assembled, the Z ring plays a crucial role in recruiting downstream proteins essential for cell division [12, 13]. Therefore the inhibition of FtsZ polymerisation prevents the division of the bacteria .
The exact mechanism through which GP0.4 interacts with FtsZ is unknown. However, a mutation in FtsZ that introduced a six nucleotide insertion (TCGGCG) overcame the toxicity of GP0.4 . Here, using a suite of structural bioinformatics methods, we predict the structure of GP0.4 ab initio and determine a mode of interaction with FtsZ in accord with available data. The results suggest that the FtsZ protofilament interface is targeted in different ways by phage proteins for antimicrobial purposes or by the bacteria’s own proteins for regulatory purposes. These results add weight to the notion that this pocket is a druggable interface.
BLAST  was used with the GP0.4 and FtsZ sequences to identify homologous proteins in the UniProt database  and to search for any homologues already structurally characterised in the Protein Data Bank (PDB) . The HHPred server was used to confirm that the structure of GP0.4 could not be inferred by distant homology to any known structure.
GP0.4 ab initio modelling
To elucidate a structure for GP0.4, ROSETTA 3.5 AbinitioRelax modelling [19–24] was used. The AbinitioRelax application consists of two steps; the first step is a coarse-grained fragment-based search for conformation that uses a score function which favours protein-like features (Abinitio). The second step is an all atom refinement using the Rosetta full-atom force field (Relax). The Robetta server [22, 25] was used to generate the required fragments and the PSIPRED  secondary structure predictions used by ROSETTA.
Using ROSETTA, 10,000 ab initio models (or decoys) were produced for GP0.4 and clustered using default protocols on a Linux workstation. Representatives of the largest ten resulting clusters were considered as candidate fold predictions. This process was repeated for four homologues identified in the BLAST search. In addition to ROSETTA, GP0.4 and each homologous sequence was submitted to the QUARK ab initio server . QUARK is an ab initio modelling method conceptually similar to ROSETTA. The server yielded a further ten models (representatives of the ten largest clusters) for each of the proteins.
Validation and comparison of GP0.4 models
GROMACS 5.0.1 molecular dynamics [28–32] was used to test the stability of the models over a period of 5 ns using a cubic box filled with water as the solvent, chloride as the counterions, and the AMBER99SB-ILDN force field . ProSA [34, 35] and QMEAN [36–39] were used to obtain protein structure quality measurements.
The top ten models produced for each protein by ROSETTA and QUARK were submitted to the ProCKSI comparative server  to assess any structural similarity between them by producing a matrix of template modelling (TM) scores . This matrix was visualised using CLuster ANalysis of Sequences (CLANS)  to cluster the models with an attraction value of >0.6.
FtsZ comparative modelling
ROSETTA comparative modelling (RosettaCM)  was used to make ten models of E. coli FtsZ based on ten homologues (2VAW, 2VXY, 4M8I, 1RQ2, 1OFU, 1W5F, 2VAP, 2R75, 3J4S and 4B45) obtained from HHPred [43–45]. RosettaCM optimises an all-atom energy function over the conformational space defined by homologue structures to produce models with more accurate side chain and backbone conformations than previously available. In order to select the best model produced, the inbuilt RosettaCM scoring system was used in combination with the model quality assessment program ProSA [34, 35].
Four servers that performed well in the most recent CAPRI (Critical Assessment of PRediction of Interactions) competition  were used to predict how models of FtsZ and GP0.4 might interact—ClusPro [47–50], Swarmdock [51–53], Dock/PIERR  and GRAMM-X .
The final putative GP0.4 binding site was assessed for drugability with two complementary servers (DoGsiteScorer  and FTMap [57–59]) and its conservation between FtsZ sequences quantified with ConSurf [60–63].
Results and discussion
ab initio modelling of GP0.4
RosettaCM  was used to produce ten models of E.coli FtsZ using homologous structures from P. aeruginosa (1ofu, 2vaw), M. tuberculosis (1rq2), T. maritima (1w5f), A. aeolicus (2r75), M. jannaschii (2vap), B.subtilis (2vxy), B. thuringiensis (3j4 s), H. volcanii (4b45) and S. epidermidis (4m8i) as templates. FtsZ has a well conserved core domain followed by a variable C-terminal domain (Additional file 1: Figure S1). Indeed the ten models produced were very similar apart from that variable C-terminal domain which adopted a wide variety of poorly packed conformations. Previous studies of FtsZ–FtsZ interaction found that the C-terminal domain was not required for the assembly of protofilaments, but was essential for interaction with other membrane associated cell division proteins . Since our focus here was on the inter-subunit interface of the protofilament targeted by GP0.4, the C-terminal region was eliminated and RosettaCM energy scores and ProSA [34, 35] scores were used to identify the most favoured model of the core domain.
Mutant Ftsz modelling
Interestingly, MciZ, a developmental regulator of bacterial cell division was found to inhibit FtsZ polymerisation by targeting the same region of the intrafilament FtsZ interface as GP0.4 whilst binding to the opposite face of the FtsZ monomer , as shown in Fig. 6.
Characteristics of the predicted GP0.4 binding site
In order to assess whether the druggable predicted GP0.4 binding site is conserved among bacteria, we mapped sequence conservation of 150 FtsZ sequences onto the FtsZ structure using the ConSurf server. Figure 8 shows that the area the ‘U’ model bound to was well conserved. This provides evidence that a GP0.4 like protein or small molecule targeted to its binding site might be effective against FtsZ in other bacteria including pathogenic species: indeed, GP0.4 homologues were identified in phages for Yersinia and Salmonella supporting this idea.
The FtsZ filament interface targeted by GP0.4 has previously been highlighted as a possible target for small molecule targeting. However, there are concerns over targeting the GTP-binding site due to a risk of poisoning the eukaryotic homologue, tubulin . Nevertheless, our results emphasise the druggable nature of a larger interface including the pocket targeted by GP0.4 They therefore encourage further efforts at exploiting the interface for small molecule drug design as well as offering possible routes forward for peptidomimetic inhibition.
Characterising the targets and inhibitory mechanisms of phage proteins is a valuable route to the discovery and validation of new potential drug targets. Here we bring a range of structural bioinformatics methods to bear on the interaction between phage GP0.4 and its bacterial target FtsZ. We provide evidence that GP0.4 adopts a ‘U’ shaped conformation that inserts into a cleft between helices 1, 5 and 7 on FtsZ. The hypothesis is strongly supported by data obtained for a GP0.4-resistant FtsZ mutation . The presence of GP0.4 bound to this region, as shown in Fig. 6, would physically interfere with assembly of the FtsZ filament. The importance of this FtsZ–FtsZ interface was further demonstrated by MciZ, a regulatory protein that binds to the opposite side of the interface to inhibit bacterial cell division. The druggable nature of the broad intrafilament FtsZ interface should encourage future drug design.
AJS carried out the experiments. DJR conceived and supervised the work. Both authors read and approved the final manuscript.
The authors declare that they have no competing interests.
Availability of data and material
Modelled structures are available on request from the authors.
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