Bacterial infections have been a life threatening problem to the human population throughout the existence of our species. In addition, with the advent of antimicrobial resistance (AMR), this has become an ever-increasing concern, contributing nearly one fifth of total global deaths every year. With a worldwide prevalence of probably five hundred million cases and hundreds of thousands of deaths every year, human salmonellosis or typhoid fever, has become a major cause for concern with the emergence of multidrug-resistance (MDR) serovars and strains of Salmonella enterica (Zaidi et al., 2008). The severity of the disease, depends on host factors and the individual emerged MDR serotype of Salmonella (Neckers and Tatu, 2008). Thus, it has become imperative to replace conventional anti-typhoid treatment strategies with new ones more suitable for drug-resistant pathogens. However, designing novel effective drugs against the most important virulence protein targets, choosing from the whole genome of Salmonella sp., is a highly challenging task.

To encounter the aforementioned threats and challenges of MDR, new strategies like drug repurposing have surfaced as alternative approaches to novel therapeutics (Rangel-Vega et al., 2015). This include computational drug repurposing strategies based on transcriptional signatures, networks, ligands, target structures using chemogenomics, machine learning, and molecular docking techniques (March-Vila et al., 2017). Nevertheless, drug repurposing approach may have some limitations on its successful outcome (Aubé, 2012). For example, the drug might act at the same target but with different outcomes that depend on the new active site of biological action of the repurposed drug (Aubé, 2012). Again, different structure-activity relationship might be possible for old and new drug with different biochemical targets, leading to an obsolete solution to be replaced by further repurposed drugs (Aubé, 2012). However, a screening of drugs identified for repurposing has proven to be useful when used together in combination thereby making it the most competing strategy to adapt the current pharmacopeia for new uses (Aubé, 2012).

To repurpose drug(s) through a network based approach, the technique of computationally analyzing the protein interaction networks for Salmonella could be employed (Pan et al., 2015). This pathogen is found to encode a Type III Secretion System (T3SS) within a pathogenicity island that is essential for virulence (Tucker and Galán, 2000). All T3SSs require the function of a family of low-molecular-weight proteins that aid the secretion process by acting as secretion factors (Tucker and Galán, 2000). One such secretion associated protein is the chaperone SicA, identified as a secretion factor from the network based approach of the protein interactome analysis of Salmonella pathogenicity islands (SPI) and two component signal transduction systems (TCS) (Lahiri et al., 2014). In summary, chaperones aid in folding, packaging, and secretion of synthesized proteins besides inhibiting aggregation due to stress factors like heat shock, thereby striking a balance between refolding and proteolytic degradation (Liberek et al., 2008). The potential of exploiting pathogenic chaperones as drug targets has also been reported (Neckers and Tatu, 2008). Notably, chaperones that support folding of newly synthesized proteins, namely Hsp60, Hsp70, and Hsp90, have distinct mechanisms of action (Fink, 1999). Most of these heat shock proteins (HSP) are constitutively synthesized but are further induced in response to stress conditions, including antibiotic therapies (Zügel and Kaufmann, 1999). In fact, DnaK, the bacterial homolog of human Hsp70, has been found to play an important role in pathogen survival (Chiappori et al., 2015). Moreover, previous work has shown that the chaperone SicA, is auto-regulated and required for the transcription of sigE (Darwin and Miller, 2001). SigE is another Hsp70 molecular chaperone protein required for stabilization of SopB/SigD secretory proteins through prevention of premature association of effectors and their degradation prior to secretion (Darwin et al., 2001). All of these proteins could, therefore, form the new targets for the newly proposed drug for repurposing. Targeting such HSPs may, therefore, help to combat pathogen virulence by reducing its capacity to respond to other treatments (Neckers and Tatu, 2008). Such treatments have been linked to the therapy of inflammatory diseases and cancer which is possible due to the molecular chaperone and antigen-binding properties of the HSPs (Calderwood et al., 2012).

To repurpose drugs through a ligand based approach, a combination of the chemical moieties of individually approved and marketed drugs could be used. Typically, drugs used mostly for treating infectious diseases caused by gram positive pathogens contain phenalenone moieties (March-Vila et al., 2017). Again, furanone moiety-based drugs have gained attention for treating other infectious (Chrystal et al., 2007). To address the pressing need for better treatment alternatives for MDR Salmonella, here we have used a combined phenaleno-furanone moiety-based ligand XR770, which was previously shown to be more preferable in performing as dual TCS inhibitor against the catalytic domain of the histidine kinase BaeS and the dimerization domain of the response regulator BaeR (Sivakumar et al., 2013). In summary, using molecular dynamics simulation, we have screened current typhoid drugs, non-typhoidal drugs and Hsp70 modulators to propose XR770 as a drug candidate against plausible chaperone protein targets, namely SicA, DnaK, and SigE compared to our reference TCS protein pairs, SsrA/SsrB and OmpR/EnvZ of the T3SS. We anticipate that targeting such molecular chaperones might help in the rational development of effective drugs for salmonellosis and thus, future control of the pathogenic bacterial growth, in an era of rapidly increasing antibiotic resistance. Furthermore, our combined-moiety ligand-based molecular docking approach via indispensable targets, will likely provide new opportunities of drug repurposing for MDR Salmonella.

Multidrug resistance has increased dramatically in the last two decades. Therefore, drug repurposing, is gaining in importance. The analysis and prediction of the activity of existing and novel drug ligands for new protein targets is based on the concept that similar compounds tend to have similar biological properties. Similarly, incorporating a structure based approach focusses on obtaining proteins likely to have similar functions and/or to recognize similar ligands. Thus, in the field of drug repurposing, protein comparison is used as a method to identify secondary targets of an approved drug. To hypothesize a new target for treating MDR Salmonella, we have explored the results of a network based approach (Lahiri et al., 2014) to identify the most indispensable proteins important for available as well as next generation drugs. The present study further develops this work at a structural level.

Furthermore, recent progress in proteomics has significantly increased the plausible number of macromolecular targets as candidates for drug discovery. Molecular docking studies have been successfully exploited in drug repurposing. Such techniques are used to predict the geometry and binding energy of the interaction of a protein in complex with a small-molecule ligand. Therefore, the method can be used to predict if a given drug is potentially able to bind other targets. The ability of such target proteins to be bound by the approved drugs shows the druggability of these proteins and indicates their potential as drug targets for the treatment of disease. Additionally, the binding between these proteins and the drugs could also probably indicate their involvement in the mechanism of action of the drugs. Such mechanism might entail inhibition of the drugs, which is exhibited computationally through the efficiency of docking between proteins and ligands, and largely depends upon the binding energy. Through molecular simulation studies, we have observed the stability in the binding energy of the target-ligand complexes and consistency of their interacting residues.

We therefore gain an insight into the ligand specificity of a protein which depends on the consistently binding active site residues of the target proteins. Thus, the homology models of SicA, DnaK, SigE, SsrA, SsrB, EnvZ, and OmpR were used for further docking studies (Table 1). Among the selected drugs viz. 19 typhoid related, 15 non-typhoidal, and 7 Hsp70 modulators, some do not obey Lipinski's rule of 5 but are still in the market and thus, were further considered for drug repositioning (Tables 2, 3). Blind docking was performed for all the chaperones and TCS proteins. This was done to avoid any bias of predictive binding sites of homology modeled proteins and yet, eventually confirm the binding pockets through the same binding residues of each different ligands at the same site, yielding good binding energy against each chaperone and TCS protein. To confirm the binding pocket with the same residues of interaction, loop docking was performed with 35 conformations. To this end, structural alignment of the pockets was also performed for chaperone and TCS proteins against the selected pockets (Supplementary Figure 1). The structural alignment results showed the proper fitting of the pockets as each protein has the same binding site, though the sequence length varies from protein to protein. However, the docking sites of each proteins are different, making it difficult to interpret the difference between them emerging from the structural alignment of the proteins (Supplementary Figure 1).

To have an insight of the same, the most effective conformation, with the highest binding energy for every ligand, was chosen from 30 assigned iterations with the formation of hydrogen bonds between the ligand and protein. Our docking results with XR770 showed hydrogen bond formation with Lys143 of SicA having −9.78 kcal/mol binding energy. Moreover, hydrogen bonds with Lys55 and Gly197 of DnaK (−8.76 kcal/mol) and those with Arg84 and Thr69 of SigE (−11.48 kcal/mol) were observed in S. Typhimurium (Figure 3). Similarly, S. Typhi showed hydrogen bond interactions with Arg61, Gln86, and Lys89 of SicA, Arg167, Asp388, and Ile418 of DnaK and Ala74 of SigE, with respective binding energies of −9.85, −9.57, and −7.35 kcal/mol (Tables 4, 5). These interacting residues showed consistency and thus, ligand specificity, conferring highest binding energy from the available conformations. Notably, XR770, Sitafloxacin and Compound 1 topped the best in the individual set amongst the three sets of drugs i.e., 19 typhoid related, 15 non-typhoidal, and 7 Hsp70 modulators, respectively. Again, XR587 showed comparatively slightly less binding energy than XR770, which has the probability to show better results if explored against different selected targets. Even though functions of some of the non-typhoidal drugs are unknown (Supplementary Table 2), they show interaction against the selected proteins with lower binding energies compared to XR770. We have also incorporated pharmacophore based prediction to analyse the common features that reveal the activity of the drugs. However, pharmacophore based screening was not performed because our objective was to check the available marketed typhoidal and non-typhoidal drugs against the target proteins selected i.e., chaperone and TCS. The common pharmacophore features for the best binding drugs are shown in Supplementary Figure 6. These observations might help us to delineate the broader perspective of typhoid drug repositioning by either considering XR770 with the fused phenaleno-furanone moiety as the repurposed ligand or the chaperone proteins like SicA, DnaK, and /or SigE as the network based new targets and pose them for experimental studies for revealing potential side-effects, if any.

To determine the efficacy of inhibition, a comparative account of the aforementioned binding patterns of XR770 showed it to be conferring the greatest binding affinity among the selected anti-typhoid drugs, like Amoxicillin and Ciprofloxacin (Table 2). In fact, resistance to the approved drugs, like Amoxicillin and Ciprofloxacin, in systemic infection, has been known in patients with typhoid and diarrhea (Cui et al., 2008). Besides, these drugs are also known to cause many unpleasant side effects, such as stomach pain, nausea, vomiting, vaginal itching or discharge, headache etc. (Leegaard et al., 1996). The toxicity for patients against typhoidal and non-typhoidal drugs is given in Supplementary Tables 3, 4.

Notably, XR770 in comparison to other drugs in this study showed more consistent amino acid residues and highest binding affinity toward the target proteins. Moreover, the greater number of hydrogen bonding formed suggests more stability of the binding interactions as are also conceived through molecular dynamics simulation. Furthermore, in order to address the issue about specificity, the parameters like relatively high difference in binding energy and binding to specific active site residues in the protein has been considered to project XR770 as the potential candidate.

Pertaining to the above results observed, thus, proving the effectiveness of the aforementioned selected proteins as drug targets could be the real challenge. To cater to this need, we have incorporated other known virulent TCS proteins of Salmonella to be compared with the chaperones. In all the cases, XR770 turned out to be the promising chemical ligand in inhibiting the selected targets viz. SicA, DnaK, SigE, SsrA, SsrB, EnvZ, and OmpR. Based on the least energy score, best docked complex was compared with the interaction pattern of XR770. Comparative study of docking interaction pattern of the above listed proteins was also performed in Salmonella typhi as well as shown in Supplementary Table 1 which revealed similar results.

Potency of a drug does not depend solely on its overall binding affinity with the target(s). On the contrary, it is a result of the complex interaction of the drug binding efficacy, namely the ability of the drug to exhibit a biological response upon interaction with the target protein. This interaction may be an agonist or antagonist depending on the physiological response. Based on the docking energy scores and ADME properties, it was found that XR770 has lower energy scores revealing higher binding affinity toward the active site. The binding follows Lipinski's rule of five with a little higher molecular weight which is acceptable when compared to several marketed drugs.

The binding free energies for the stable protein-ligand complexes with XR770 for SicA, DnaK, and SigE were −2301.36, −2263.78, and −2298.245 kJ mol⁻¹, which also denote stability with respect to temperature and pressure (Supplementary Figure 5 and Table 7). The results of the MD simulation run clearly indicated that these protein-ligand complexes were held together by strong intermolecular non-covalent forces. These strong binding interactions between the XR770 and chaperone proteins make the complexes highly stable and fit for possible involvement in various reactions (Supplementary Figure 4).

Despite having such exemplary computational binding activities against the chaperone and TCS proteins, it is worthwhile to mention that XR770 has been reported to have only inhibitory effect on NRII (or NtrB) histidine kinase from E. coli but no effect is reported for the whole cell bacteria (Chrystal et al., 2007; Bem et al., 2014). However, in the absence of proper knowledge of the assay done to check for the activity of XR770, it can be considered as the main caveat of this study.

From our study, chaperone proteins SicA, DnaK, and SigE along with the TCS proteins SsrA SsrB, EnvZ, and OmpR have been demonstrated to be potential druggable targets for the new phenaleno-furanone based ligand XR770.Thus, XR770 confers high binding affinity toward all the target proteins with a binding affinity comparable to the approved drugs. Hence, XR770 might prove to be potent inhibitor for the chaperone proteins. However, pharmacological studies are required to confirm the inhibitory activity of XR770 against the chaperones as effective drug targets.

CL conceived the concepts, planned, and designed the layout of the work. The work was conducted by SM under the primary supervision of CL with additional supervisory input from DG. Figures were created by SM. SM wrote the paper, with textual revisions by CL and DG.