The Hydrophobic Core of Twin-Arginine Signal Sequences Orchestrates Specific Binding to Tat-Pathway Related Chaperones

Redox enzyme maturation proteins (REMPs) bind pre-proteins destined for translocation across the bacterial cytoplasmic membrane via the twin-arginine translocation system and enable the enzymatic incorporation of complex cofactors. Most REMPs recognize one specific pre-protein. The recognition site usually resides in the N-terminal signal sequence. REMP binding protects signal peptides against degradation by proteases. REMPs are also believed to prevent binding of immature pre-proteins to the translocon. The main aim of this work was to better understand the interaction between REMPs and substrate signal sequences. Two REMPs were investigated: DmsD (specific for dimethylsulfoxide reductase, DmsA) and TorD (specific for trimethylamine N-oxide reductase, TorA). Green fluorescent protein (GFP) was genetically fused behind the signal sequences of TorA and DmsA. This ensures native behavior of the respective signal sequence and excludes any effects mediated by the mature domain of the pre-protein. Surface plasmon resonance analysis revealed that these chimeric pre-proteins specifically bind to the cognate REMP. Furthermore, the region of the signal sequence that is responsible for specific binding to the corresponding REMP was identified by creating region-swapped chimeric signal sequences, containing parts of both the TorA and DmsA signal sequences. Surprisingly, specificity is not encoded in the highly variable positively charged N-terminal region of the signal sequence, but in the more similar hydrophobic C-terminal parts. Interestingly, binding of DmsD to its model substrate reduced membrane binding of the pre-protein. This property could link REMP-signal peptide binding to its reported proofreading function

Interactions of chimeric signal sequences with REMPs.

<p>The composition of the signal sequences is shown on the left as a three-letter code. This indicates whether the N-, H-, and C-regions originate from the DmsA (D) or the TorA (T) signal sequence, respectively. For example, DTT represents a signal sequence that consists of the N-region of DmsA followed by the H- and C-regions of TorA. For each chimeric pre-protein the SPR response curve is shown for an injection of a 200 nM solution over immobilized TorD and a DmsD, respectively, as indicated at the top of the graph. The response curves for the wild-type signal sequences and their corresponding REMPs are shown in red. A response curve for 200 nM signal peptide-free Strep-GFP is shown in the bottom panel.</p

The signal sequence ensures specific REMP binding.

<p>Surface plasmon resonance sensorgrams for the injection of various proteins over immobilized TorD (<b>A</b>) and DmsD (<b>B</b>) are shown. The model pre-proteins ssDmsA-GFP (black lines), ssTorA-GFP (red lines) and signal sequence-free GFP (blue lines) were injected for 60 seconds at a concentration of 200 nM, a flow rate of 50 µl/min, and a temperature of 25°C.</p

List of plasmids used in the study.

<p>List of plasmids used in the study.</p

Determination of the dissociation constant for ssTorA-GFP binding to immobilized TorD.

<p>(<b>A</b>) Raw SPR sensorgrams and (<b>B</b>) referenced sensorgrams of ssTorA-GFP binding to immobilized TorD at the following pre-protein concentrations (shown from dark to light grey): 39 nM, 78 nM, 156 nM, 313 nM, 625 nM, 1250 nM. The sensorgram for a buffer injection is shown in black. (<b>C</b>) Equilibrium SPR intensity for binding of ssTorA-GFP to TorD at various concentrations in a Scatchard plot (open symbols, see main text for details). The intensity values used are the average SPR response derived from the shaded area (22–28 s) in panel A. The data are fitted to a straight line (black). (<b>D</b>) The SPR intensity at equilibrium is plotted as a function of pre-protein concentration, for binding to immobilized TorD. The pre-proteins used are ssTorA-GFP (shown in black), ssTorA(RK)-GFP (shown in blue), ssTorA(KR)-GFP (shown in green) and ssTorA(KK)-GFP (shown in red). The best fit of the Langmuir binding isotherm (Equation 1) to the data is shown as a line in the corresponding color.</p

Dissociation constants for TorA signal peptides binding to TorD.

1<p>Dissociation constants from this work are obtained from SPR data by fitting the Langmuir equation (Equation 1) to the equilibrium SPR response as a function of pre-protein concentration. Errors are standard fitting errors.</p>2<p>ss, signal sequence; GFP, green fluorescent protein; MBP, maltose binding protein; SBP, streptavidin binding peptide.</p

Twin-arginines are not essential for REMP binding.

<p>(<b>A</b>) SPR response curves obtained by injecting solutions containing 100 nM ssTorA-GFP (black line) or 100 nM ssTorA(KKK)-GFP (red line) over immobilized TorD. (<b>B</b>) Response curves obtained by injecting solutions of 100 nM ssDmsA-GFP (black line) or 100 nM ssDmsA(KK)-GFP (red line) over immobilized DmsD.</p

DmsD reduces membrane binding of ssDmsA-GFP.

<p>(<b>A</b>) SPR response curves of various proteins injected over a phospholipid bilayer that mimics the composition of the <i>E. coli</i> inner membrane. Injected solutions contain either 50 nM signal peptide-free Strep-GFP (orange line), 50 nM ssDmsA-GFP (blue line), 50 nM ssDmsA-GFP with 100 nM DmsD (red line), 50 nM ssDmsA-GFP with 200 nM DmsD (green line), 50 nM TorD (grey line), or 500 nM DmsD (black line). The red and green curves were corrected for the jump in refractive index by subtracting the response curves for injections of solutions containing 100 or 200 nM DmsD, respectively. (<b>B</b>) SPR response curve for an experiment in which DmsD was injected over a surface consisting of ssDmsA-GFP bound to a phospholipid bilayer. ssDmsA-GFP (100 nM) was injected over an immobilized phospholipid bilayer for a period of 100 s. The surface was washed with buffer for 500 s to remove weakly bound ssDmsA-GFP. Subsequently, buffer containing 25 nM DmsD was injected.</p

Fragment-based screening in tandem with phenotypic screening provides novel antiparasitic hits

Methods to discover biologically active small molecules include target-based and phenotypic screening approaches. One of the main difficulties in drug discovery is elucidating and exploiting the relationship between drug activity at the protein target and disease modification, a phenotypic endpoint. Fragment-based drug discovery is a target-based approach that typically involves the screening of a relatively small number of fragment-like (molecular weight <300) molecules that efficiently cover chemical space. Here, we report a fragment screening on TbrPDEB1, an essential cyclic nucleotide phosphodiesterase (PDE) from Trypanosoma brucei, and human PDE4D, an off-target, in a workflow in which fragment hits and a series of close analogs are subsequently screened for antiparasitic activity in a phenotypic panel. The phenotypic panel contained T. brucei, Trypanosoma cruzi, Leishmania infantum, and Plasmodium falciparum, the causative agents of human African trypanosomiasis (sleeping sickness), Chagas disease, leishmaniasis, and malaria, respectively, as well as MRC-5 human lung cells. This hybrid screening workflow has resulted in the discovery of various benzhydryl ethers with antiprotozoal activity and low toxicity, representing interesting starting points for further antiparasitic optimization

Fragment-Based Screening in Tandem with Phenotypic Screening Provides Novel Antiparasitic Hits

Methods to discover biologically active small molecules include target-based and phenotypic screening approaches. One of the main difficulties in drug discovery is elucidating and exploiting the relationship between drug activity at the protein target and disease modification, a phenotypic endpoint. Fragment-based drug discovery is a target-based approach that typically involves the screening of a relatively small number of fragment-like (molecular weight <300) molecules that efficiently cover chemical space. Here, we report a fragment screening on TbrPDEB1, an essential cyclic nucleotide phosphodiesterase (PDE) from Trypanosoma brucei, and human PDE4D, an off-target, in a workflow in which fragment hits and a series of close analogs are subsequently screened for antiparasitic activity in a phenotypic panel. The phenotypic panel contained T. brucei, Trypanosoma cruzi, Leishmania infantum, and Plasmodium falciparum, the causative agents of human African trypanosomiasis (sleeping sickness), Chagas disease, leishmaniasis, and malaria, respectively, as well as MRC-5 human lung cells. This hybrid screening workflow has resulted in the discovery of various benzhydryl ethers with antiprotozoal activity and low toxicity, representing interesting starting points for further antiparasitic optimization