Disarming Streptococcus mutans in real time: live-cell DARTS uncovers ABC transporter targeting by manool

Disarming Streptococcus mutans in real time: live-cell DARTS uncovers ABC transporter targeting by manool | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Disarming Streptococcus mutans in real time: live-cell DARTS uncovers ABC transporter targeting by manool Giuliana Donadio, Raffaella Nocera, Emanuele Rosa, Valentina Parisi, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7204413/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Antimicrobial resistance poses a significant threat to global health, highlighting the urgent need for novel therapeutic agents. Plant-derived compounds are a promising source of antimicrobial compounds. Given their huge structural variability, they putatively operate through a multiplicity of modes of action, interacting with various targets. The implementation of appropriate approaches aimed at reliably describe the molecular mechanism of these compounds, allows identifying promising hits, and new pharmacologically exploitable proteins. Here, we investigated the antimicrobial activity of manool, a diterpene isolated from Salvia officinalis L. (Lamiaceae), against the dental pathogen Streptococcus mutans . Using compound-centric proteomic techniques, we identified ATP-binding cassette (ABC) transporters as key targets of manool. These proteins are involved in nutrient uptake and in bacterial drug resistance. Implementing metabolomics approaches, we showed that manool inhibits ABCs, thereby impairing energy metabolism and delaying bacterial proliferation, and. enhancing the efficacy of the antibiotic kanamycin. Finally, based on the docking and molecular dynamics results we hypothesized that manool is able to interfere with the activity of various ABCs by occupying their ATP binding domain. This is the first time that ABCs have emerged from a completely untargeted approach as proteins responsible for the bioactivity of an antibacterial agent. Biological sciences/Microbiology/Antimicrobials Biological sciences/Biochemistry/Proteomics Biological sciences/Plant sciences Biological sciences/Drug discovery/Target identification In-cell DARTS natural product antimicrobial target identification Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction The misuse and abuse of antibiotics is leading antimicrobial resistance (AMR) in pathogens to become a dramatic global problem 1 , 2 related to multiple medical, social and economic implications 3 , 4 . Microorganisms have evolved various strategies to reduce their sensitivity to antibiotics, including mutations in drug targets, inhibition of drug entry into the cell, expulsion of the drug through efflux pumps or drug inactivation 5 – 7 . The search for new antibiotics that act through unexploited mechanisms and molecular targets is therefore urgent. Natural scaffolds are a critical basis for drug development. Since plants are intrinsically forced to defend themselves from parasites and predators mainly through their secondary metabolites, they constitute an almost inexhaustible source of bioactive compounds 8 , particularly those inhibiting the growth of bacteria, fungi, and parasites 9 , 10 . Unfortunately, for most compounds the encouraging results obtained in vitro tests have not been confirmed in vivo . The selection of a promising candidate requires protocols that allow to obtain substantial information on the molecular mechanisms underlying their mode of action. In response to evolutionary pressures from parasites and predators, plants have developed an extensive range of secondary metabolites, providing a virtually inexhaustible source of bioactive compounds 10 . Many of these molecules exhibit significant inhibitory activity against bacteria, fungi, and parasites 11 , 12 . However, the translational potential of these compounds is limited, as most in vitro findings have not been validated in vivo. This is often due to a lack of optimal functional characterisation of bioactive compounds, a key step in the research process that impedes a comprehensive understanding of their mechanisms of action and therapeutic applicability. Selecting a promising candidate requires protocols that can identify compounds with robust potency and selectivity profiles while providing detailed insight into their molecular mechanisms of action. To this end, new methods are being implemented, which can be performed under pseudo-physiological conditions and do not require any modification of the studied compounds. These methods provide a comprehensive overview of the interactome of bioactive compounds and often lead to the discovery of new targets. Such findings could be important in the fight against AMR, as the identification of unexploited targets could enable the design of innovative drugs that pathogens cannot escape. Based on these considerations, we investigated the bioactivity of manool (Fig. 1 A), a labdane diterpene from Salvia officinalis L., on gram-positive bacteria. Manool has been shown to have several biological activities 11 , including antimicrobial effects against the dental pathogen Streptococcus mutans 12 . Therefore, we attempted to identify the target(s) of manool in this bacterium. We chose S. mutans for three reasons. First, it has been shown to be susceptibility to manool (MIC 20 µM) 13 . Second, S. mutans can grow in multiple conditions, thus allowing the use of different experimental protocols. Finally, S. mutans is a genetically adaptable and relatively safe organism 14 . To unveil the protein interactors of manool in S. mutans , we used a proteomic-based method, Drug Affinity Responsive Target Stability (DARTS) 15 . DARTS is based on the reduction in susceptibility to protease action observed for proteins upon interaction with a ligand. The main advantage of DARTS is that it can be performed on living cells, allowing the identification of protein targets under pseudo-physiological conditions. However, although it is widely used to identify drug targets in eukaryotic cells 16 , application of DARTS to prokaryotes is limited by the very rapid proliferation times of these organisms and their ability to respond to insults both individually and through cooperative strategies. Indeed, DARTS protocol has so far been carried out in bacteria only using cell lysates, where the proteins are out of their cellular environment and exposed to conditions that do not fully retain natural interactions within an intact cell 17 . To overcome this non-negligible limitation, we decided to implement an in-bacteria DARTS approach to investigate the mode of action of manool in S. mutans . In that aim, we had to modify the classic DARTS protocol to make it suitable for use in bacteria. Among the protein interactors emerged from proteomic analyses, we focused on transporters ATP-binding cassette (ABC), a large superfamily of integral membrane proteins involved nutrients intake and drug resistance. In fact, the inhibition of these proteins by manool may underlay the antimicrobial activity reported for this compound. To validate this hypothesis, we conducted proteomic and metabolomic studies in S. mutans treated or not with manool. Furthermore, we performed docking and molecular dynamic calculation to confirm the direct interaction between the diterpene and the ATP-binding region of the ABCs. Results Determination of Minimum Inhibitory Concentration (MIC) of manool against S. mutans and its effects on the growth of the bacterium. Studies aimed at identifying the molecular target of a bioactive compound should be carried out under experimental conditions allowing the molecule to interact with its partner but producing minimal effects on the treated cells. In that aim, as a first step we measured the MIC of manool against S. mutans through the serial dilution method 18 . Bacteria were incubated with different concentration of manool (from 2.5 µM to 40 µM) or vehicle at 37°C for 24 hours, after which we evaluated the amount of S. mutans in the different conditions by measuring spectrophotometrically (λ = 600 nm) the changes in the optical density (OD) of the medium. The obtained results (Fig. 1 B) showed that at a 10 µM concentration of manool 40% of the bacteria survived, while at 20 µM a 100% inhibition of proliferation was observed (MIC100). Manool cytotoxicity towards eukaryotic cells was evaluated using the MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay, by incubating HaCaT cells (immortalized human keratinocytes) with various concentrations (2.5–160 µM) of the diterpene. The results showed that manool did not exert any cytotoxicity up to a concentration of 80 µM (Fig. S1 ), thus suggesting that the bioactivity of the diterpene is specific towards bacterial species. To describe the effects of manool on S. mutans proliferation, we monitored the bacterial growth for 660 min starting from a bacteria-containing medium with a 0.05 OD/mL, in the absence of manool or in the presence of three concentrations of the diterpene (2.5, 5 and 10 µM) (Fig. 1 C). For the manool free control, we observed a well-defined sigmoidal growth curve, showing a latency phase of about 200 min, an exponential phase with a duration of about 200 min in which the maximum optical density was reached (around 1.6 OD/ml), and finally the stationary phase. Under the explored experimental condition, the cell death phase was not observed. When S. mutans was incubated with manool, the latency phase became longer, being approximatively 300 min when 2.5 µM of manool was used, of 650 min for 5 µM of manool and longer than 660 min for 10 µM of manool. Also, the slope of the exponential phase decreased proportionally to the concentration of manool used. Since manool seemed to mainly affect the lag phase of S. mutans growth, we investigated the effect of the diterpene when it was added to the S. mutans culture during the exponential phase. For this purpose, S. mutans was first diluted from the overnight inoculum to 0.2 OD/ml. Then, once the culture reached 0.5 OD/ml we added manool at the same concentrations described in the previous experiment. Interestingly, in this case the differences in growth parameters between treated and non-treated bacteria were almost negligible (Fig. 1 D). These results suggested that manool is able to affect the proliferation of S. mutans mainly if the bacteria are incubated with diterpene before starting their exponential growth. The effect of manool on S. mutans was also investigated by monitoring by NMR changes in glucose fermentation induced by the incubation of bacteria with the diterpene. S. mutans was incubated with three concentrations of manool (2.5, 5 and 10 µM) and samples were collected every 30 minutes for 11-hours. The NMR spectra analysis focused on measuring the levels of glucose and the fermentative products lactic acid, acetoin and 2-3-butanediol. Based on the 1 H NMR spectra (Fig. S2), isolated and well-resolved signals were selected for peak integration: the doublet at 5.24 ppm (3.7 Hz) for glucose; the multiplet at 4.12 ppm for lactic acid; the doublet at 1.38 ppm (6.8 Hz) for acetoin; and the doublet at 1.13 ppm (5.8 Hz) for 2,3-butanediol. The obtained date demonstrated that treatment with manool induced a dose-dependent reduction of glucose consumption (Fig. 2 A) and increased the release of fermentative products into the growth medium (Fig. 2 B-D). Exploiting Drug Affinity Responsive Target Stability (DARTS) to identify manool partners in S. mutans. To identify the putative targets of manool in S. mutans , DARTS experiments were performed on both protein extracts (peDARTS) and live bacterial cells (lbDARTS). However, to perform lbDARTS, it was necessary to design and set up a specific protocol that takes into account the significant biological, structural, morphological and functional differences between prokaryotic and eukaryotic cells. In particular, the most critical point was to reduce the proteome changes that occur during the incubation of S. mutans cells with manool. Such changes could indeed affect the results of the DARTS. In fact, it would be difficult to understand whether differences observed in the quantity of undigested proteins depend on their protection from proteolysis by manool or on an increase in their level following the treatment of the bacteria with the diterpene. In that aims, we cultured S. mutans in a reduced growth environment M9 medium containing 0.4% glucose, thus slowing down the metabolism of the bacterium, without losing the advantage of studying the interactions between manool and its protein targets inside the living cell. Indeed, although M9 is not the optimal medium for S. mutans proliferation, it allows the bacteria to survive. In addition, as bacteria under restricted growth conditions may express a more selective set of proteins involved in stress responses or ligand interactions, the switch from rich to minimal medium may reduce the complexity of the proteome of the bacterium, making it easier to identify the putative targets of manool. Remarkably, the results obtained using the two approaches were in good agreement. Indeed, in both cases (Table.1 and 2), subunits of the ATP synthase complex were identified as putative manool targets, consistently with previously reported findings 12 . Furthermore, several proteins involved in transmembrane trafficking have emerged as possible interactors of manool most of which belong to the superfamily of ATP-binding cassette (ABC) transporters and to the phosphotransferase system (PTS). However, it has to be underlined that from lbDARTS only emerged membrane proteins, while using the cell lysate some cytosolic proteins were also identified. This difference highlights the importance of being able to conduct experiments on intact cells, in which all proteins have retained their native structure. Overall, the DARTS results shed a new light on the possible molecular mechanism underlying the antiproliferative effect of manool against S. mutans , suggesting that it may depend, at least in part, on the impairment of extracellular transport. ABC transporters, which was the most represented protein group among those emerged from DARTS, play a key role in multiple vital processes for bacteria as they regulate both extrusion of toxic compounds and intake of nutrients 19 , 20 . Therefore, we carried out a series of assays aimed at confirming that manool actually interacts with proteins belonging to this family and evaluating if affecting their activity. Validation of ABC proteins as manool targets. ABCs act as efflux pumps (EPs) in both Gram-positive and Gram-negative bacteria, modulating cellular homeostasis and conferring resistance to antibiotics by expelling drugs and other toxic compounds 21 , 22 . Therefore, as a preliminary step, the effect of manool on S. mutans efflux pumps was examined via an ethidium bromide (EtBr) accumulation assay. The obtained results showed that the addition of manool produced a dose-dependent increase in EtBr fluorescence (Fig. 3 A), thus demonstrating an inhibitory effect of manool on S. mutans EPs. Based on these data, we further investigated the possible effect of manool in reducing the capability of S. mutans to eliminate toxic compounds through ABC-mediated transport. In 2014, Nagayama et al. showed that isogenic mutant strains generated by inactivation of ABC efflux transporters were significantly more sensitive to aminoglycosides and tetracyclines antibiotics 19 . Therefore, to support the hypothesis that manool affects ABCs activity, we evaluated the effect of the diterpene on the antibacterial action of the aminoglycoside drug kanamycin. We measured the MIC100 against S. mutans of kanamycin alone (Fig. 3 B) and in combination with manool (Fig. 3 C) and a significant increase in the antibiotic effect was observed when the bacteria were treated with both compounds. Indeed, the MIC 100 of kanamycin alone on S. mutans was found to be 227 µM while in combination with 10 µM of manool, it became almost 10 times lower (28.4 µM). To assess whether the increase in kanamycin activity was due to an additive or synergistic effect, we calculated the fractional inhibition concentration index (FICI) value for manool and kanamycin (S1 Table). Processing the data in accordance with the criteria described by Cos P 23 , a FICI value of 0.62 was obtained, which is borderline between those associated with additivity and synergism. We supposed that such enhancement of the kanamycin efficacy induced by manool relays on a reduced capacity of ABCs to expel kanamycin from the cell. To confirm this, we evaluated whether the presence of manool influenced the extracellular levels of the antibiotic. Therefore, we measured by LC-MS/MS for 120 min the kanamycin concentration in the medium of S. mutans cultured with kanamycin (28.375 µM) alone or with different concentrations of manool (2.5, 5, 10 µM). The results (Fig. 3 D) showed that the presence of a concentration of manool of 5 or 10 µM strongly reduced kanamycin extrusion. Remarkably, the presence of 10 µM of the diterpene also affected the kinetics of detoxification (Fig. 3 E). In the other tested conditions, the bacterium was able to expel very quickly the antibiotic, which then undergoes a slow consumption; in the presence of 10 µM manool, however, this expulsion seemed to practically not occur, as inferred by the very low levels of kanamycin measured already after 5 min of incubation and which then remained almost constant. As previously stated, the ABC proteins are also responsible for the intake of many nutrients for bacteria 24 , 25 , Therefore, to further validate the DARTS result, we analysed the effect of manool treatment on nutrients trafficking in S. mutans . Since several ABC proteins identified by DARTS are involved in amino acid (AA) transmembrane transport (Tables 1 and 2 ), we monitored the AA uptake in growing bacteria incubated with different concentrations of manool. We measured the changes over time in AAs concentration in the culture medium of S. mutans during growth in the presence of three sub-MIC concentrations of manool (2.5, 5 and 10 µM) or in manool free medium. Obtained results showed that in the manool free medium (Fig. 4 A-E, black line) a decrease of around 30% in the AA concentration took place upon the first 150 min of incubation. Subsequently, the AAs level remained essentially constant. Remarkably, the lag-phase of S. mutans growth lasts exactly 150 min (Fig. 1 C). This result indicated that most of the AA uptake by the bacteria occurs before the exponential growth begins 26 . In the presence of the diterpene, no significant changes in the AAs concentration in the medium was observed for most of the monitored AA (Fig. 4 A-D, red line and Fig. S3A-D.), suggesting manool to prevent the uptake of many AAs by the bacteria. Interestingly, glutamine levels in the medium of treated and untreated cells were comparable (Fig. 4 E and Fig. S3E.). This evidence actually constitutes a further confirmation of our hypothesis. In fact, given the peculiar role played by glutamine as a source and transporter of amino groups, bacterial cells have many systems involved in the transport of this AA unlike the others 27 , 28 . Table 1 Enriched proteins in the manool protein extract DARTS sample. Accession Mass Description Q8DT62 29,9 Putative ABC transporter, glutamine binding protein Q8DW32 28,3 Putative ABC transporter, ATP-binding protein Q8DU84 45 Putative ABC transporter, ATP-binding protein, proline/glycine betaine transport system Q00751 31,6 Multiple sugar-binding transport system permease protein MsmG Q00750 31,9 Multiple sugar-binding transport system permease protein MsmF Q8DW36 27,6 Putative ABC transporter, ATP-binding protein amino acid transport system Q8DTB0 35,9 ABC transporter substrate-binding protein Q8DSC5 17,3 ABC transporter permease Q8DSU1 30,7 Putative branched chain amino acid ABC transporter, permease protein Q8DTY2 23,8 Putative amino acid ABC transporter, permease protein I6L8X6 52,6 Putative PTS system, membrane component possible ribulose-monophosphate PTS pathway enzyme IIC I6L915 35,3 PTS system, sorbitol phosphotransferase enzyme IIBC Q8DWF7 30,3 Putative PTS system, IID component Q8DUI0 45,2 ATP-dependent Clp protease ATP-binding subunit ClpX P95788 32,3 ATP synthase gamma chain Q8DVK4 33,7 Methionyl-tRNA formyltransferase I6L8Z9 20,5 DUF177 domain-containing protein Q93D93 32,7 Protease HtpX homolog Q8DVQ8 15,6 Putative Hit-like protein involved in cell-cycle regulation Q8DUG3 48,4 Putative folyl-polyglutamate synthetase Q8DTK0 28,9 Putative alpha/beta superfamily hydrolase Q8DVH1 38 PDZ domain-containing protein Table 2 Enriched proteins in the manool bacterial cells DARTS sample. Accession Mass Description Q8DUA1 60,8 ABC transporter permease Q8CM14 25,9 Putative ABC transporter ATP-binding protein Q8DTD8 93,2 Putative ABC transporter, membrane protein subunit and ATP-binding protein Q8DUD7 37,7 Putative ABC transporter, periplasmic ferrichrome-binding protein I6L8X8 45,5 Putative polysaccharide ABC transporter, ATP-binding protein Q8DT62 29,9 Putative ABC transporter, glutamine binding protein Q8DUJ5 31,8 Putative amino acid ABC transporter, periplasmic amino acid-binding protein Q8DUT7 80,2 Putative glutamine ABC transporter, permease protein Q8DW22 39,1 Putative oligopeptide ABC transporter, ATP-binding protein OppD Q8DRU8 43,4 Putative osmoprotectant amino acid ABC transporter, ATP-binding protein Q8DTB0 35,9 ABC transporter substrate-binding protein Q8DVL9 27,7 Putative amino acid ABC transporter, ATP-binding protein Q8DUJ2 28,3 Putative amino acid ABC transporter, ATP-binding protein Q8DSC4 35,5 PTS system mannose-specific EIIAB component Q8DSC3 28,1 Putative PTS system, mannose-specific component IIC Q8DS73 15,2 Putative PTS system, sugar-specific enzyme IIA component Q8DWF8 28,2 Putative sorbose PTS system, IIC component Q8DWF7 30,3 Putative PTS system, IID component Q8DS74 18,2 Putative PTS system, mannose-specific IIB component I6L8X9 12,9 Putative PTS system, sorbitol-specific enzyme IIA P95786 20,4 ATP synthase subunit delta P95788 32,3 ATP synthase gamma chain Computational studies for the identification of manool binding mode to ABCs. Manool exhibits inhibition of diverse ABC transporters, likely by engaging conserved ATPbinding domains. Building on its known fit within the ATP site of human ATPsynthase, we computationally assessed its affinity for ABC ATPase subunits. As a model we selected the multiple sugarbinding ABC ATPbinding protein from Streptococcus mutans (Q00752), the only target with a reliable 3D template. A dimeric homology model was generated, validated by a Ramachandran plot (S4 Fig), and refined with a 400 ns moleculardynamics (MD) simulation that stabilized after ~ 150 ns (CαRMSD ≈ 4 Å; Fig. S5). From the last 200 ns we extracted 200 snapshots and docked manool into each using AutoDockGPU, producing 400 poses. RMSDbased clustering (≤ Å, ≥ 10 % poses) yielded four clusters (Fig. S6). Additional 400 ns MD of each complex showed clusters 1 and 3 were stable (mean ligand RMSD 3.0 and 2.3 Å), whereas clusters 2 and 4 were not (8.3 and 6.5 Å; Fig. S7). MMPBSA analysis on the final 350 ns identified cluster 3 as the most favorable binding mode (S2 Table ΔG_bind = − 17.0 kcal mol⁻¹), 7.9 kcal mol⁻¹ better than the next best pose, supporting it as the preferred interaction geometry. Figure 5 illustrates the predicted binding mode of manool from cluster 3. The trimethyldecahydronaphthalene moiety fits into a hydrophobic pocket, interacting with Y13, P14, T46, and I221 of monomer A, likely contributing to ligand stabilization. Meanwhile, the hydroxyl group establishes two stable hydrogen bonds: one with the backbone nitrogen of K213 and another via a water-mediated interaction with the side chain of the same residue (K213). These interactions likely play a role in further anchoring the ligand within the pocket, reinforcing its stability. Interestingly, the second monomer of the dimeric system does not appear to engage in direct stabilizing interactions with the ligand. However, its presence may contribute to the overall binding mode by providing structural constraints that help maintain the proper orientation of the ligand within the binding site. According to MM-PBSA analysis, this binding mode benefits from both hydrophobic and electrostatic interactions, supporting its stability and potential biological relevance. Discussion The search for new antibiotics is being given a significant boost due to the increasingly dramatic problem of antibiotic resistance. In this context, a key role can be played by compounds directed to molecular targets that are still under-exploited. Such molecules have two main advantages: they could be effective against (multi)resistant bacteria and they could enhance the effect of drugs acting on more classical targets. Plants are a rich source of potent antimicrobial compounds, but the lack of information on their mode of action is limiting their use as therapeutic agents. The availability of data on the molecular mechanisms underlying the biological effect of these compounds would allow to fully understand the potential of their use, to evaluate the putative synergism with other drugs and to predict possible undesired or secondary effects. Therefore, the implementation of methods for the reliable identification of the molecular targets of antimicrobial compounds is an urgent need. Such methods may also reveal new druggable proteins in bacteria, paving the way to new therapeutic approaches that overcome antimicrobial resistance. Here we set up a protocol for the trustworthy definition of protein targets of antimicrobial agents, using a combination of DARTS experiments. DARTS is compound-centric proteomic approach widely used in eukaryotic systems (15, 16), which provides reliable results when used on both protein extracts and intact and living cells. Indeed, the first approach allows identifying all the protein showing any affinity towards the investigated compound, but it provides no information on the actual ability of the molecule to cross the bacterial envelope; moreover, the cell lysis procedure, even if optimized to preserve protein native structure, could significantly affect stability of membrane proteins, thus limiting their ability to interact with bioactive compounds. These criticisms are almost completely by-passed using the cell-based assay, which also provides insights into interactions occurring with proteins in their physiological environment. However, the incubation of living cells with a bioactive compound may result in significant changes in the proteome, thus making difficult to correctly identify the proteins protected from proteolysis by a direct interaction with the investigated molecule. This problem is more serious the faster the cells change and may therefore be critic for procaryotic cells. Possibly, this is the reason why other studies have applied DARTS to bacteria only using cell lysates 17 . However, given the complementarity of the two DARTS approaches, we set up optimized conditions allowing to perform the assay also on living bacteria. The results we obtained confirmed the importance of this choice. We used our protocol to investigate the antibiotic effect of the plant diterpene manool, which has promising activity towards gram-positive bacteria, against S. mutans . Interestingly, lbDARTS demonstrated that manool is able to interact only with proteins located on the cell membrane. Obviously, this data could not emerge from peDARTS, in which the accessibility of proteins to manool is not limited by the cellular structure. However, even peDARTS experiments confirmed some of the putative targets identified using living bacteria, but obviously they also suggested some possible interactors that are probably not actually reachable by manool. Among the protein identified by DARTS assays, we focused on the ABC transporters, based on the critical role they play in bacteria and the number of proteins belonging to this family emerged from compound-centric proteomic studies. These ATP-dependent membrane proteins mediate the uptake of many nutrients 29 and the efflux of toxic compounds 30 . Therefore, in order to corroborate and refine the results of DARTS, we performed a set of experiments aimed at evaluating the effects of manool treatment of S. mutans on transmembrane transport of different molecules. The obtained results clearly supported the hypothesis that inhibition of some ABCs by manool underlays the bioactivity of this diterpene. Indeed, incubation of S. mutans with manool under conditions not affecting the bacteria vitality reduced the efficacy of the efflux pump system that mostly consists of ABC proteins. Coherently, manool reduced the extrusion and enhanced the antibacterial action of kanamycin, an aminoglycoside antibiotic the resistance to which is mediated by the ABCs themselves 31 – 33 .While these findings validate the DARTS results, they do not fully explain manool own antiproliferative activity. Nevertheless, ABC transporters play essential roles in nutrient uptake, ion balance and cellular regulation, making them critical for bacterial proliferation. Notably, manool treatment caused a marked decrease in amino acid consumption, particularly during the lag phase, when untreated bacteria typically absorb high levels of amino acids. This evidence may thus explain the prolongation of the lag phase of growth observed when S. mutans bacteria are incubated with manool. Indeed, it is plausible that when the bacteria are treated with manool become unable to take up the metabolites needed to activate cell duplication; therefore, they stay longer in a non-proliferative condition trying to accumulate the required nutrients. This hypothesis is supported by evidence that treatment of S. mutans with manool during the exponential phase of growth produces negligible effects, suggesting that the action of the diterpene is most critical when the bacteria are increasing their intracellular nutrient levels before initiating proliferation. The effects of manool on bacteria metabolism were clearly highlighted by monitoring the variation in glucose concentration in the medium of S. mutans treated or not with manool. Indeed, the NMR-based analysis revealed that manool significantly reduces glycolysis, which is a critical pathway for S. mutans in maintaining its energy production, particularly in the context of dental plaque formation and acid production 34 . This trend was clearly dependent on the concentration of manool, suggesting that incubation with the diterpene inhibits glucose metabolism in S. mutans . However, the interpretation of these results cannot be univocal. On the one hand the variations observed in the glucose consumption depend on the differences in the number of bacterial cells in the different conditions. In fact, the graph of lactic acid over time (Fig. 2 B) is almost superimposable to the growth curves of S. mutans (Fig. 1 C). On the other hand, since among the ABCs emerged from DARTS there was also a monosaccharide transporter, we cannot exclude that the inhibition of glycolysis may depend, at least in part, on the reduction of the efficiency of glucose availability to the bacterium. However, manool interferes with nutrient uptake by inhibiting ABC transporters, thus affecting the essential metabolism of S. mutans , causing stress, delaying adaptation and reducing growth. The dual effect to reduce antibiotic resistance and to inhibit proliferation produced by manool on S. mutans is in agreement with DARTS results, which revealed the ability of the compound to interact with several ABC transporters. This multiplicity of targets of the diterpene is quite surprising since ABCs consist of a structurally heterogenous class of proteins. However, they all intrinsically carry an ATP-binding site, which is generally located in dimeric subunits that can also regulate the activity of different transporters 35 . Based on this information and on the previously reported data supporting the ability of manool to occupy effectively specific ATP-binding pockets 12 , we supposed that manool modulates ABCs activity interacting with the ATP-binding subunit/domain of these proteins. The results of our calculations strongly supported this hypothesis, allowing to describe in detail the interactions stabilizing the manool-protein complex. This binding mode could in fact explain how a single molecule can act as a ligand for numerous proteins, affecting their biological activity. Given the importance of this family of proteins, their number and their abundance in prokaryotic cells, the results we have reported could open the way to the development of new molecules active towards these targets. The opportunity to enhance antibiotic drug efficacy by inhibiting ABC transporters has been previously reported 36 . However, here ABCs emerged from a fully untargeted approach, in which compound-protein interactions have been directly observed under conditions mimicking physiological ones, and in the presence of all the proteins and molecules that could interfere or compete with these interactions. in this perspective, the experimental protocol we used has proven to be a very useful tool both to explain, at least in part, the mechanism of action of manool, and to identify new targets for the development of innovative therapeutic agents. Materials and Methods Reagents and materials. Growth Media Brain Heart Infusion Broth (Oxoid) and M9 Minimal Salts Base (Na 2 HPO 4 , H 2 O, KH 2 PO 4 , NaCl, NH 4 Cl) 5X were used. Solvents: Ultra-pure water (ROMIL-UpsTM Ultra purity), ultra-pure acetonitrile (ROMIL-UpsTM Ultra purity), ultrapure water (18 MΩ), and DMSO (Sigma-Aldrich) were utilized for the preparation of solutions and reagents. Buffers: The following buffers were used: Dulbecco’s Modified Eagle’s Medium (DMEM, Sigma-Aldrich), MOPS, Tris-HCl (1.5 M pH 8.8 and 1.0 M pH 6.8), Laemmli Buffer, TGS (Tris/Glycine/SDS buffer 5X, Bio-Rad), and AMBIC. Reagents: MTT (4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide (Invitrogen) was used for cell viability assays. Other reagents included subtilisin, acrylamide 30% (AppliChem), sodium dodecyl sulfate (SDS), ammonium persulfate (APS), tetra-methylenediamine (TEMED), dithiothreitol (DTT, AppliChem), iodoacetamide (IAA, AppliChem), and trypsin (proteomic grade, 0.0013 µg/µl). Standards: Kanamycin sulfate (ChemCruz), and chlorhexidine (MCE®) were used as standards in the experiments. The manool was previously purified from Salvia. officinalis and was thus already available as a pure molecule. It was solubilized in DMSO at a concentration of 5 mg/ml and stored at -20°C prior to use. Deuterium oxide (D 2 O, 99.90% D), and 3-(trimethylsilyl) propionic-2,2,3,3-d4 acid sodium salt (TSP) and KH 2 PO 4 saltfor NMR analysis were purchased from Sigma-Aldrich Chemical Company (Sigma-Aldrich,Milano, Italy). Bacterial Culture. Streptococcus mutans Clarke NCTC (National Collection of Type Cultures) 10499 was grown in liquid Brain Heart Infusion (BHI) medium at 37°C under aerobic conditions for 18–24 hours. Solid culture was performed on BHI medium with 1.5% agar on a 60 cm² Petri dish (100 x 20 mm) at 37°C for 48 hours. Minimum Inhibitory Concentration (MIC). The minimum inhibitory concentration (MIC) was assessed using the serial dilution method, in accordance with the CLSI protocol 37 Manool concentrations ranging from 40 µM to 2.5 µM were tested on S. mutans . Serial dilutions were performed in a 96-well plate to achieve the desired antimicrobial concentrations (40 µM, 20 µM, 10 µM, 5 µM, 2.5 µM). S. mutans was inoculated into the plate at a density of 1 x 10⁶ CFU/ml. The plate was then incubated at 37°C. After 24 hours, the bacterial growth inhibition values were evaluated using a spectrophotometer at a wavelength of 600 nm. The positive control was performed with the antibiotic chlorhexidine. All tests were performed in triplicate Bacterial Growth Curve. The growth curves of S. mutans were evaluated in both the presence and absence of manool. Cultures were initiated at 0.05 OD600 and then cultivated at 37°C with agitation. Manool was added to three flasks at concentrations of 2.5 µM, 5 µM and 10 µM. Bacterial growth was measured using OD600 readings every 30 minutes for 660 minutes. In a separate experiment, manool was added at an OD600 of 0.5 in cultures that had previously been diluted to 0.2 OD600. Growth was then monitored every 30 minutes for a further 210 minutes Cell Viability Assay (MTT) . The cell viability assay was conducted using the “HaCaT” cell line, immortalized human keratinocytes. The cells were maintained in culture with DMEM 1X (Dulbecco’s Modified Eagle’s Medium) containing 4.5 g/L glucose, 2 mM glutamine, 10% fetal bovine serum (FBS), penicillin (100 units/ml), and streptomycin (100 units/ml) at 37°C in a controlled atmosphere with 5% CO 2 . The MTT colorimetric assay is based on the intracellular reduction of the tetrazolium salt (yellow color) by the mitochondrial enzyme succinate dehydrogenase (SDH) into formazan, which, due to its insolubility in the culture medium, precipitates as dark blue-violet crystals. HaCaT cells (immortalized human keratinocytes) were plated in 96-well plates (5000 cells/well). After 24 hours, they were treated with manool (5-160 µM) for 24 hours, and DMSO at 0.1% was used as the negative control. The MTT assay was performed by incubating the cells with 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) at a final concentration of 1 mg/mL. The plates were incubated at 37°C for 3 hours. Subsequently, a lysis buffer (20% SDS; 50% dimethylformamide, adjusted to pH 4.7 with a mixture of 80% acetic acid and 1 N HCl) was added and incubated for 18 hours. Finally, absorbance values were obtained by reading the spectrophotometer in a wavelength range between 570 and 610 nm. Drug Affinity Responsive Target Stability Assay on protein extract (pe-DARTS). A gel with 12% polyacrylamide concentration was prepared as follows: “Resolving gel 12%” (for a final volume of 10 ml): 3.3 ml distilled H₂O, 4.0 ml 30% acrylamide, 2.5 ml Tris-HCl 1.5 M pH 8.8, 0.1 ml 10% SDS, 0.1 ml 10% ammonium persulfate (APS) (initiator), 0.004 ml TEMED (catalyst); “Stacking gel” (for a final volume of 3 ml): 2.1 ml distilled H₂O, 0.5 ml 30% acrylamide, 0.38 ml Tris-HCl 1.0 M pH 6.8, 0.03 ml 10% SDS, 0.03 ml 10% ammonium persulfate (APS), 0.03 ml TEMED. For sample resuspension and electrophoresis, the following solutions were used: “SDS gel-loading buffer” (Laemmli Buffer): Tris 0.125 M pH 6.8 (for protein denaturation), 4% SDS (w/v), 0.4% bromophenol blue (w/v) (dye), 40% glycerol (v/v) (to increase sample density for loading into wells), 10% β-mercaptoethanol (v/v) (to break disulfide bonds between cysteines); “Running buffer” (for a final volume of 1 L): 800 ml deionized H₂O, 200 ml 5x TGS (Tris/Glycine/SDS buffer). Electrophoresis was performed at 100 V for 20 minutes and continued at 180 V for 40 minutes. After electrophoresis, the proteins were fixed in gel using the fixing solution (50% H₂O, 40% MeOH, 10% CH₃COOH), and 10 bands were excised from each lane and subjected to trypsin digestion. The tryptic digestion selectively cleaves peptide bonds on the carboxyl side of arginine and lysine residues, generating highly characteristic fragments for each protein. Each band was transferred into respective Eppendorf tubes and subjected to a washing step with acetonitrile (ACN) three times to dehydrate the gel fragments. After removing the ACN solution, 0.01 M DTT in 0.1 M ammonium bicarbonate (AMBIC) was added. The reduction reaction was carried out for 60 minutes at 56°C. Then, the supernatant was removed and another three washes with ACN were performed. After removing the ACN, a 0.055 M iodoacetamide (IAA) in AMBIC 0.1 M solution was added. The alkylation reaction was carried out for 30 minutes at room temperature in the dark. After removing the supernatant, the bands were washed again with ACN and dried in a Speed-Vac for 15 minutes. Subsequently, the actual digestion was performed: 30 µl of a trypsin solution (Proteomic grade, 0.0013 µg/µl) in 25 mM AMBIC was added to each band to cover them, and each was incubated at 4°C for 45 minutes to allow the enzyme to penetrate the gel bands. Finally, 20 µl of 25 mM AMBIC was added to completely cover the gel fragments. The reaction was continued overnight at 37°C to optimize enzyme activity. After incubation, peptide extraction was performed. First, ACN was added and the eppendorfs were incubated for 15 minutes at 37°C. After the reaction, the supernatant was recovered and placed in clean Eppendorf tubes. The extraction solution containing the peptides of interest was dried in a Speed-Vac. The dried peptides were resuspended in 1% formic acid (FA) and analyzed by mass spectrometry All obtained data are available in https://zenodo.org/records/15743861 . Drug Affinity Responsive Target Stability Assay on Living Bacterial Cells (lbDARTS). The S. mutans overnight inoculum was centrifuged at 3000 rpm for 15 minutes, and the cells were resuspended in BHI medium to a density of 0.05 OD/ml. The cells were incubated at 37°C and cultured to the established optical densities (0.5 OD/mL and 1 OD/mL). Then cells were centrifuged at 3000 rpm for 15 minutes. After discarding the supernatant, the pellet was resuspended in M9 minimal medium 1X supplemented with 0.4% glucose for both control and treated samples, at a density of 0,5 OD/ml and 1 OD/mL. The treated samples were incubated with manool at 5 µM and 10 µM for 90 minutes. The samples were then centrifuged at 3000 rpm for 10 minutes. After discarding the supernatant, the pellets were resuspended in 25 mM MOPS buffer. The cells were then lysed following the previously described protocol. Efflux pump assay. An ethidium bromide (EtBr) accumulation assay was performed to assess membrane transport activity in S. mutans , following Overnight cultures were washed and resuspended in PBS at a concentration of 0.6 OD600/mL. Manool (0.75–6 µg/mL) and EtBr (2 µg/mL) were added to the wells of a 96-well plate, with DMSO and MeOH (0.5%) serving as controls. Fluorescence was measured every 60 seconds for 60 minutes at 37°C (excitation: 525 nm; emission: 605 nm). Determination of Activity in Combination with other antibiotics. The synergistic effect of manool and kanamycin against S. mutans was evaluated. First, the MIC100 of kanamycin was determined via serial dilution (14.2–227 µM). Subsequently, any synergy between manool and kanamycin was evaluated by using subMIC concentrations of kanamycin, in the presence of a single concentration of manool (10 µM), corresponding to its MIC50.The plate was incubated at 37°C. After 24 hours, the values of bacterial growth inhibition were evaluated using a spectrophotometer at a wavelength of 600 nm. The results were interpreted by calculating the fractional inhibitory concentration (FIC) index for kanamycin and quantifying the nature of the pharmacological interaction in vitro (synergy, additivity, indifference, or antagonism. 23 LC-MS analysis of kanamycin and amino acids. To assess the presence of kanamycin and amino acids in S. mutans culture supernatants, LC-MS analyses were performed using an ABSCIEX API 6500 QTRAP® mass spectrometer coupled to a Nexera X2 UPLC Shimadzu system, operating in positive ion mode. Samples were diluted 1:1000 in ultrapure water to preserve column integrity and avoid signal saturation. For kanamycin, supernatants from cultures treated with kanamycin alone (28.37 and 56.75 µM) and in combination with manool (2.5, 5, and 10 µM) were analyzed. For amino acids, supernatants from untreated and manool-treated cultures (2.5, 5, and 10 µM) were examined. Chromatographic separation was performed on a Luna® Omega column with formic acid in water and organic solvents (methanol or acetonitrile, depending on the analysis) under gradient conditions. Amino acid detection employed Multiple Reaction Monitoring (MRM) transitions based on previously validated methods 38 . Full dataset is available at https://doi.org/10.5281/zenodo.15696464 . NMR sample preparation. NMR sample preparation was performed as previously reported by 39 with slight modifications. Supernatants for NMR analysis were collected as described into paragraph 2.4 and centrifuge at 10000 g for 5 minutes at 4°C to remove the particulate matter. 540 µL of obtained clear supernatants were added to 60 µL of a mono-potassium phosphate solution (90 mM KH 2 PO 4 in D 2 O, pH 6.5) and transferred to 5 mm NMR tubes. Trimethylsilyl propionic-2,2,3,3-d4 acid, sodium salt (TSP-d4 0.01% in D 2 O) was used as an internal reference for alignment of NMR spectra. NMR spectroscopy and processing. The NMR experiments were carried out as previously reported by 40 with slight modifications, optimizing the acquisition parameters. Spectra were acquired on a Bruker Avance 600 spectrometer equipped with a 5 mm ATMA cryo-probe operating at 298 K and a SampleJet changer. TopSpin V3.2 software (Bruker Biospin,Wissembourg, France) was used for NMR data acquisition and processing, and its IconNMR module controlled the automation of acquisition (locking, tuning, matching, and shimming). 1 H NMR spectra were recorded using a 1D-NOESY (noesygppr1d) pulse sequence with water signal suppression 41 . The acquisition parameters were: 19K data points, 2782.7 Hz (11 ppm) spectral width, 4 dummy and 128 scans, a recycle delay of 5 s, and a fixed value for receiver gain for all samples. To achieve a high confidence level of metabolites annotations, 2D NMR experiments (HSQC, HMBC, COSY) and 1D TOCSY were also recorded. Phase corrections and baseline editing were performed manually for all spectra using TOPSPIN version 3.2. NMR data analysis. 1 H NMR spectra were processed using NMRProcFlow 1.4.28 (INRA UMR 1332 BFP, Bordeaux Metabolomics Facility, Villenave d’Ornon, France) 42 . The ppm calibration was made using the internal standard at 0 ppm and the peaks alignment was applied on all 1 H NMR spectra. Variable size bucketing was used to integrate the signals of key metabolites. The data matrix was exported, and the areas obtained were used to determine the level of selected metabolites in bacteria supernatants. The metabolites annotation was achieved using Chenomx NMR-Suite v12 (Chenomx Inc.), online databases (HMDB, SpectraBase) and in-house library. 2D NMR spectra were analysed using TOPSPIN version 3.2. Full dataset is available at https://doi.org/10.5281/zenodo.15696464 . Homology Modeling. All the primary sequences were obtained from the SWISS-PROT protein sequence database 43 . Sequence similarity searches were carried out using Blast. The crystal structure of the multiple sugar-binding protein (6PUW) was taken from the Protein Data Bank. The sequence alignment of the chosen protein was performed by Modeller 10.5 44 with a gap creation penalty of 900 and a gap extension penalty of 50. Five structures were generated by means of the Automodel protocol, as implemented in Modeller, and the best receptor model was chosen on the basis of the Discrete Optimized Protein Energy (DOPE) assessment method and minimized. The backbone conformation of the resulting receptor structures was evaluated by inspection of the Ramachandran plot. The protein was minimized using Amber22 software 45 and ff14SB force field at 300 K. The protein was placed in a rectangular parallelepiped waterbox; the TIP3P explicit solvent model for water was used and the complex was solvated with a 15 Å water cap. Chlorine ions were added as counterions to neutralize the system. Two steps of minimization were then carried out. In the first stage, we kept the protein fixed with a position restraint of 500 kcal/mol·Å 2 and we solely minimized the positions of the water molecules. In the second stage, we minimized the entire system through 5000 steps of steepest descent followed by conjugate gradient (CG) until a convergence of 0.05 kcal/Å mol. MD Simulations. The minimized protein was used as input structures for the MD simulations, which were run using Particle Mesh Ewald (PME) electrostatics, a cutoff of 10 Å for the non-bonded interactions and all the parameters reported above. SHAKE algorithm was used to constrain all bonds involving hydrogen atoms and a time step of 2.0 fs was thus used for the simulation. Initially, a MD heating stage of 50 ns, in which the temperature of the system was raised from 0 to 300 K, was performed using constant-volume periodic boundary conditions. In all these steps all α carbons of the protein were subjected to a harmonic potential of 10 kcal/mol•Å 2 . Finally, a production step of 350 ns was performed maintaining the same temperature and pressure conditions but removing any harmonic restraint, thus leaving the system totally free. In total, the protein was thus subjected to 400 ns of MD simulation. Docking studies. The compound cpd01 was docked into the final 200 conformations of the multiple sugar-binding transport ATP-binding protein using Autodock-GPU 46 with the ADP molecule from 3PUW defining the center of the binding site. For each docking calculation, the following parameters were used: 100 LGA runs with 10000000 score evaluations, 10000000 generations and 500 as population size per run. An RMSD clustering tolerance of 2.0 Å was used. The 400 docking solutions were clustered by using an in-house python script and by considering only clusters with a population of at least 40 docking results. The resulting clusters were then subjected to MD simulations. For each protein-ligand complex, all parameters reported above were used. General Amber force field (GAFF) parameters were used for the ligand, whose partial charges were assigned using the Antechamber suite of Amber22, based on the AM1-BCC method. As reported above, two steps of minimization were then carried out. In the first stage, we kept the protein fixed with a position restraint of 500 kcal/mol·Å 2 and we solely minimized the positions of the water molecules. In the second stage, we minimized the entire system through 5000 steps of steepest descent followed by conjugate gradient (CG) until a convergence of 0.05 kcal/Å·mol. For the MD simulations, a MD heating stage of 50 ns, in which the temperature of the system was raised from 0 to 300 K, was performed using constant-volume periodic boundary conditions with all α carbons of the protein subjected to a harmonic potential of 10 kcal/mol•Å 2 . Then, a production step of 350 ns was performed maintaining the same temperature and pressure conditions. In total, each complex analyzed was thus subjected to 400 ns of MD simulation. The final structure of the protein-ligand complex corresponded to the average of the last 350 ns of MD simulation minimized by the CG method until a convergence of 0.05 kcal/mol•Å 2 . The average structures were obtained using the Cpptraj program implemented in Amber22, which was also used for RMSD and H-bond analyses. Binding Energy Evaluation. The evaluation of the binding energy associated with the four protein-ligand complexes analyzed through MD simulations was carried out using AMBER22, as already reported 47 – 49 .The trajectories relative to the last 350 ns of each simulation were extracted and used for the calculation for a total of 350 snapshots (at time intervals of 1 ns). Van der Waals, electrostatic and internal interactions were calculated with the SANDER module of AMBER22, whereas polar energies were calculated using the Poisson-Boltzman methods with the MM-PBSA module of AMBER22. Dielectric constants of 1 and 80 were used to represent the gas and water phases, respectively. The entropic term was considered as approximately constant in comparison of the ligand-protein energetic interactions Statistical analysis . Data are presented as mean values with error bars representing standard deviation (SD) from at least two or three independent experiments. Significance levels are indicated as follows: ns (not significant), P < 0.01 (* ), P < 0.005 ( ** ), P < 0.001 ( ***), P < 0.0001 (****). T-tests, one-way ANOVA were used for statistical evaluations. Declarations Acknowledgments The authors want to acknowledge Prof.Viviana Izzo for her suggestion and usefuld discussion. The research was partially supported by Project funded under the National Recovery and Resilience Plan (NRRP), Mission 4 Component 2 Investment 1.4 - Call for tender No. 3138 of December 16, 2021, rectified by Decree n.3175 of December 18, 2021 of Italian Ministry of University and Research funded by the European Union – NextGenerationEU; Award Number: Project code CN_00000033, Concession Decree No. 1034 of June 17, 2022 adopted by the Italian Ministry of University and Research, CUP: D43C22001260001, Project title “National Biodiversity Future Center - NBFC”. Competing Interest Statement: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Author Contributions: RN: Microbiology, Data Analysis, Writing-original draft. ER: Mass spectrometry analyses VP: NMR analyses. TT: Computational studies, Writing-original draft . 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Granchi, C. et al. Design, synthesis and biological evaluation of second-generation benzoylpiperidine derivatives as reversible monoacylglycerol lipase (MAGL) inhibitors. Eur. J. Med. Chem. 209 , 112857 (2021). Di Stefano, M. et al. Machine Learning-Based Virtual Screening for the Identification of Cdk5 Inhibitors. Int. J. Mol. Sci. 23 , 10653 (2022). Additional Declarations There is NO Competing Interest. Supplementary Files SupportinginformationNoceraet.al.docx Supplemental material Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7204413","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":494919763,"identity":"8d5da1a6-2fb1-4a52-aa13-2e664f42bd3f","order_by":0,"name":"Giuliana Donadio","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyUlEQVRIiWNgGAWjYFCCBCBmk2DgB1IHgJiHeC2SDVAtROgBa2FgMDgA5RPUIu+efOzBjzILOeMbuQcP/qhhkLEnpMXwzLN0w55zEsZmN/ISDvMcI8JhhjNyzCR42yQSt93IMTgMdCFxWiT/ArVsnpFjcPDHPyK0yEvkmEmDbNkgkWNwgLeNCC0GPM/SpGWAfpE488bgMG+fBA/PAUK2tCcfk3xTVifH355j/PHHNxt79gZCtqCZKUHIWUBbCJk5CkbBKBgFo4ABALqUObgdCyyCAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0001-9055-731X","institution":"università di Salerno","correspondingAuthor":true,"prefix":"","firstName":"Giuliana","middleName":"","lastName":"Donadio","suffix":""},{"id":494919764,"identity":"4c973f9f-8a3a-49d3-bf9d-f8915dd99db0","order_by":1,"name":"Raffaella Nocera","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Raffaella","middleName":"","lastName":"Nocera","suffix":""},{"id":494919765,"identity":"916964e2-b232-4f66-b67d-d96ee6f1458e","order_by":2,"name":"Emanuele Rosa","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Emanuele","middleName":"","lastName":"Rosa","suffix":""},{"id":494919766,"identity":"2695ae96-056e-4d98-9597-f0c3de1428cf","order_by":3,"name":"Valentina Parisi","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Valentina","middleName":"","lastName":"Parisi","suffix":""},{"id":494919767,"identity":"d9c3621a-30ee-4cb3-90d3-4d97166d7080","order_by":4,"name":"Tiziano Tuccinardi","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Tiziano","middleName":"","lastName":"Tuccinardi","suffix":""},{"id":494919768,"identity":"386d0d08-a2d4-4622-8a16-a43f5bd556ea","order_by":5,"name":"Miriana Di Stefano","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Miriana","middleName":"Di","lastName":"Stefano","suffix":""},{"id":494919769,"identity":"aff0ca2d-1e64-4ed9-a89a-c9b01c62360e","order_by":6,"name":"Fabrizio Dal Piaz","email":"","orcid":"https://orcid.org/0000-0002-8643-5018","institution":"University of Salerno","correspondingAuthor":false,"prefix":"","firstName":"Fabrizio","middleName":"Dal","lastName":"Piaz","suffix":""},{"id":494919770,"identity":"1c1e4581-0a78-4bcc-ba75-97e43e62d672","order_by":7,"name":"Nunziatina De Tommasi","email":"","orcid":"https://orcid.org/0000-0003-1707-4156","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Nunziatina","middleName":"","lastName":"De Tommasi","suffix":""}],"badges":[],"createdAt":"2025-07-24 10:10:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7204413/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7204413/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88355887,"identity":"b1654e31-79bf-4ac1-a410-1f330a3e47e2","added_by":"auto","created_at":"2025-08-05 15:10:09","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":94383,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAntibacterial activity of the labdane diterpene manool and its effect on \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eStreptococcus mutans\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e proliferation\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e(A) Chemical structure of the labdane diterpene manool. (B) Determination of the minimal inhibitory concentration (MIC) of manool against \u003cem\u003eS. mutans.\u003c/em\u003e Bacterial cultures were incubated for 24 hours at 37°C in the presence of increasing concentrations of manool (2.5–40 µM) or vehicle control. Bacterial growth was evaluated by measuring the optical density of the medium at 600 nm (OD\u003csub\u003e600\u003c/sub\u003e). (****p-value\u0026lt; 0,0001; ***p-value\u0026lt; 0,001; **p-value\u0026lt; 0,005). (C) Growth curve of \u003cem\u003eS. mutans\u003c/em\u003e in BHI broth with supplementation of manool (0,2.5,5,10 µM). OD600nm measured every 30 mins. (D) Effect of manool\u003cem\u003e \u003c/em\u003eon\u003cem\u003e S. mutans \u003c/em\u003egrowth when added during the exponential phase of growth\u003cem\u003e.\u003c/em\u003e At 0.5 OD manool was added at concentrations of 2.5, 5, and 10 µM. Bacterial proliferation was monitored by measuring the OD\u003csub\u003e600\u003c/sub\u003e every 30 minutes for 660 minutes. All data calculated from the average of three independent experiments with error bars representing Standard Deviation (SD).\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7204413/v1/02523235784393f8988a6932.png"},{"id":88355885,"identity":"119cfd3d-7482-43ce-ba35-50e9c0ea2fe7","added_by":"auto","created_at":"2025-08-05 15:10:09","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":217065,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eImpact of manool on glucose metabolism and production of fermentative end-products in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eS. mutans\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGlucose (A) levels in the growth medium for the control and the treatments with manool at 2.5, 5 and 10 µM. Results are expressed as a percentage, with 100 indicating the area of the glucose signal in the control group at 0 minutes. Lactic acid (B), acetoin (C) and 2,3-butanediol (D) in the growth medium in the control group and the treatments with manool at 10, 5 and 2.5 µM. Data, after blank (BHI medium) subtraction are expressed as a percentage, indicating 100 as the area of the metabolite signals in the control group in the exponential phase. Data calculated from the average of two independent experiments with error bars representing SD.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7204413/v1/44861ecc72033f923f32c9f4.png"},{"id":88355883,"identity":"8287fdac-aafd-4c40-81c4-a9f0f826cc29","added_by":"auto","created_at":"2025-08-05 15:10:09","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":160644,"visible":true,"origin":"","legend":"\u003cp\u003e(A) An ethidium bromide (EtBr) accumulation assay was performed to evaluate the impact of manool on efflux pump (EP) activity in \u003cem\u003eS. mutans\u003c/em\u003e. EtBr fluorescence intensity was measured in the presence of three concentrations of manool (2.5, 5, and 10 µM). (B) Determination of the MIC\u003csub\u003e100\u003c/sub\u003e of kanamycin alone against \u003cem\u003eS. mutans\u003c/em\u003e by serial dilution (range: 14.2–227 µM), establishing a baseline inhibitory concentration of 227 µM. (C) Evaluation of the synergistic antibacterial effect of kanamycin and manool. Kanamycin was tested at sub-MIC concentrations in the presence of 10 µM manool (the MIC\u003csub\u003e50\u003c/sub\u003e of the diterpene). After a 24-hour incubation period at 37 °C, bacterial growth inhibition was measured spectrophotometrically at 600 nm in a 96 well plate. A borderline synergistic pharmacological interaction was indicated by the fractional inhibitory concentration index (FICI). (D-E). Extracellular kanamycin concentrations in the growth medium over 120 minutes of incubation with \u003cem\u003eS. mutans\u003c/em\u003e and kanamycin (28.375 µM), either alone or in combination with increasing concentrations of manool (2.5, 5 and 10 µM). The residual kanamycin concentration in the culture supernatant was quantified by LC-MS/MS. Data calculated from the average of two independent experiments with error bars representing SD. (ns, not significant,****p-value\u0026lt; 0,0001, ***p-value\u0026lt; 0,001, **p-value \u0026lt; 0,005, *p-value\u0026lt;0,01).\u0026nbsp;\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7204413/v1/2c5ac54c7144bb2486a7785b.png"},{"id":88357177,"identity":"8dbc47d9-8a9f-454c-b52e-c8e95f1a7421","added_by":"auto","created_at":"2025-08-05 15:26:09","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":104032,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eManool reduces amino acid uptake in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eS. mutans\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e by interfering with the import of nutrients via the ABC transporter.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTime course analysis of the concentrations of amino acids (AAs) in the culture medium of \u003cem\u003eS. mutans\u003c/em\u003egrown in the absence (black line) or presence (purple line) of a sub-MIC concentration of Manool (10 µM). AA levels were measured by LC-MS at multiple time points over 150 minutes. (A) Glutamic acid (B) Phenylalanine (C) Tyrosine (D) Glutamine. Data represent the average of two independent experiments; error bars indicate standard deviation. Full data for additional amino acids and different manool concentrations are shown in S3 Fig.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7204413/v1/7907b8239fbbd25df4f744c9.png"},{"id":88356166,"identity":"e9ad0960-fd26-4168-9267-c944ae805515","added_by":"auto","created_at":"2025-08-05 15:18:10","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":243401,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMinimized average structures of manool\u003c/strong\u003e (sky blue) in complex with multiple sugar-binding transport ATP-binding protein. General overview (left) and ligand-binding site interaction analysis (right). The two monomers are coloured pink (monomer A) and green (monomer B). In the general overview, the ligand is shown in green CPK representation. In the binding site view, the protein residues surrounding the ligand, forming the binding site, are shown as pink (monomer A) and green (monomer B) sticks, while hydrogen bonds are represented as black lines.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7204413/v1/8c2957feb3ba322929fafcb9.png"},{"id":104783224,"identity":"94535ee2-a72c-4538-a4f9-84c939be647a","added_by":"auto","created_at":"2026-03-17 07:58:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2119171,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7204413/v1/0d0af16c-5aad-44a0-9272-3c9c3d097889.pdf"},{"id":88356162,"identity":"1fb947c7-71e4-46a4-be1d-7e52f484f1d6","added_by":"auto","created_at":"2025-08-05 15:18:09","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":765775,"visible":true,"origin":"","legend":"Supplemental material","description":"","filename":"SupportinginformationNoceraet.al.docx","url":"https://assets-eu.researchsquare.com/files/rs-7204413/v1/e1649f696719c586186792c7.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Disarming Streptococcus mutans in real time: live-cell DARTS uncovers ABC transporter targeting by manool","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe misuse and abuse of antibiotics is leading antimicrobial resistance (AMR) in pathogens to become a dramatic global problem \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e related to multiple medical, social and economic implications \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Microorganisms have evolved various strategies to reduce their sensitivity to antibiotics, including mutations in drug targets, inhibition of drug entry into the cell, expulsion of the drug through efflux pumps or drug inactivation \u003csup\u003e\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. The search for new antibiotics that act through unexploited mechanisms and molecular targets is therefore urgent. Natural scaffolds are a critical basis for drug development. Since plants are intrinsically forced to defend themselves from parasites and predators mainly through their secondary metabolites, they constitute an almost inexhaustible source of bioactive compounds \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, particularly those inhibiting the growth of bacteria, fungi, and parasites \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Unfortunately, for most compounds the encouraging results obtained \u003cem\u003ein vitro\u003c/em\u003e tests have not been confirmed \u003cem\u003ein vivo\u003c/em\u003e. The selection of a promising candidate requires protocols that allow to obtain substantial information on the molecular mechanisms underlying their mode of action. In response to evolutionary pressures from parasites and predators, plants have developed an extensive range of secondary metabolites, providing a virtually inexhaustible source of bioactive compounds \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Many of these molecules exhibit significant inhibitory activity against bacteria, fungi, and parasites \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. However, the translational potential of these compounds is limited, as most in vitro findings have not been validated in vivo. This is often due to a lack of optimal functional characterisation of bioactive compounds, a key step in the research process that impedes a comprehensive understanding of their mechanisms of action and therapeutic applicability. Selecting a promising candidate requires protocols that can identify compounds with robust potency and selectivity profiles while providing detailed insight into their molecular mechanisms of action. To this end, new methods are being implemented, which can be performed under pseudo-physiological conditions and do not require any modification of the studied compounds. These methods provide a comprehensive overview of the interactome of bioactive compounds and often lead to the discovery of new targets. Such findings could be important in the fight against AMR, as the identification of unexploited targets could enable the design of innovative drugs that pathogens cannot escape. Based on these considerations, we investigated the bioactivity of manool (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA), a labdane diterpene from \u003cem\u003eSalvia officinalis\u003c/em\u003e L., on gram-positive bacteria. Manool has been shown to have several biological activities \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, including antimicrobial effects against the dental pathogen \u003cem\u003eStreptococcus mutans\u003c/em\u003e \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Therefore, we attempted to identify the target(s) of manool in this bacterium. We chose \u003cem\u003eS. mutans\u003c/em\u003e for three reasons. First, it has been shown to be susceptibility to manool (MIC 20 \u0026micro;M) \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Second, \u003cem\u003eS. mutans\u003c/em\u003e can grow in multiple conditions, thus allowing the use of different experimental protocols. Finally, \u003cem\u003eS. mutans\u003c/em\u003e is a genetically adaptable and relatively safe organism \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. To unveil the protein interactors of manool in \u003cem\u003eS. mutans\u003c/em\u003e, we used a proteomic-based method, Drug Affinity Responsive Target Stability (DARTS) \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. DARTS is based on the reduction in susceptibility to protease action observed for proteins upon interaction with a ligand. The main advantage of DARTS is that it can be performed on living cells, allowing the identification of protein targets under pseudo-physiological conditions. However, although it is widely used to identify drug targets in eukaryotic cells \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, application of DARTS to prokaryotes is limited by the very rapid proliferation times of these organisms and their ability to respond to insults both individually and through cooperative strategies. Indeed, DARTS protocol has so far been carried out in bacteria only using cell lysates, where the proteins are out of their cellular environment and exposed to conditions that do not fully retain natural interactions within an intact cell \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. To overcome this non-negligible limitation, we decided to implement an in-bacteria DARTS approach to investigate the mode of action of manool in \u003cem\u003eS. mutans\u003c/em\u003e. In that aim, we had to modify the classic DARTS protocol to make it suitable for use in bacteria. Among the protein interactors emerged from proteomic analyses, we focused on transporters ATP-binding cassette (ABC), a large superfamily of integral membrane proteins involved nutrients intake and drug resistance. In fact, the inhibition of these proteins by manool may underlay the antimicrobial activity reported for this compound. To validate this hypothesis, we conducted proteomic and metabolomic studies in \u003cem\u003eS. mutans\u003c/em\u003e treated or not with manool. Furthermore, we performed docking and molecular dynamic calculation to confirm the direct interaction between the diterpene and the ATP-binding region of the ABCs.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eDetermination of Minimum Inhibitory Concentration (MIC) of manool against\u003c/b\u003e \u003cb\u003eS. mutans\u003c/b\u003e \u003cb\u003eand its effects on the growth of the bacterium.\u003c/b\u003e Studies aimed at identifying the molecular target of a bioactive compound should be carried out under experimental conditions allowing the molecule to interact with its partner but producing minimal effects on the treated cells. In that aim, as a first step we measured the MIC of manool against \u003cem\u003eS. mutans\u003c/em\u003e through the serial dilution method \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Bacteria were incubated with different concentration of manool (from 2.5 \u0026micro;M to 40 \u0026micro;M) or vehicle at 37\u0026deg;C for 24 hours, after which we evaluated the amount of \u003cem\u003eS. mutans\u003c/em\u003e in the different conditions by measuring spectrophotometrically (λ\u0026thinsp;=\u0026thinsp;600 nm) the changes in the optical density (OD) of the medium. The obtained results (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB) showed that at a 10 \u0026micro;M concentration of manool 40% of the bacteria survived, while at 20 \u0026micro;M a 100% inhibition of proliferation was observed (MIC100). Manool cytotoxicity towards eukaryotic cells was evaluated using the MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay, by incubating HaCaT cells (immortalized human keratinocytes) with various concentrations (2.5\u0026ndash;160 \u0026micro;M) of the diterpene. The results showed that manool did not exert any cytotoxicity up to a concentration of 80 \u0026micro;M (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e), thus suggesting that the bioactivity of the diterpene is specific towards bacterial species. To describe the effects of manool on \u003cem\u003eS. mutans\u003c/em\u003e proliferation, we monitored the bacterial growth for 660 min starting from a bacteria-containing medium with a 0.05 OD/mL, in the absence of manool or in the presence of three concentrations of the diterpene (2.5, 5 and 10 \u0026micro;M) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). For the manool free control, we observed a well-defined sigmoidal growth curve, showing a latency phase of about 200 min, an exponential phase with a duration of about 200 min in which the maximum optical density was reached (around 1.6 OD/ml), and finally the stationary phase. Under the explored experimental condition, the cell death phase was not observed. When \u003cem\u003eS. mutans\u003c/em\u003e was incubated with manool, the latency phase became longer, being approximatively 300 min when 2.5 \u0026micro;M of manool was used, of 650 min for 5 \u0026micro;M of manool and longer than 660 min for 10 \u0026micro;M of manool. Also, the slope of the exponential phase decreased proportionally to the concentration of manool used. Since manool seemed to mainly affect the lag phase of \u003cem\u003eS. mutans\u003c/em\u003e growth, we investigated the effect of the diterpene when it was added to the \u003cem\u003eS. mutans\u003c/em\u003e culture during the exponential phase. For this purpose, \u003cem\u003eS. mutans\u003c/em\u003e was first diluted from the overnight inoculum to 0.2 OD/ml. Then, once the culture reached 0.5 OD/ml we added manool at the same concentrations described in the previous experiment. Interestingly, in this case the differences in growth parameters between treated and non-treated bacteria were almost negligible (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). These results suggested that manool is able to affect the proliferation of \u003cem\u003eS. mutans\u003c/em\u003e mainly if the bacteria are incubated with diterpene before starting their exponential growth. The effect of manool on \u003cem\u003eS. mutans\u003c/em\u003e was also investigated by monitoring by NMR changes in glucose fermentation induced by the incubation of bacteria with the diterpene. \u003cem\u003eS. mutans\u003c/em\u003e was incubated with three concentrations of manool (2.5, 5 and 10 \u0026micro;M) and samples were collected every 30 minutes for 11-hours. The NMR spectra analysis focused on measuring the levels of glucose and the fermentative products lactic acid, acetoin and 2-3-butanediol. Based on the \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003eH NMR spectra (Fig. S2), isolated and well-resolved signals were selected for peak integration: the doublet at 5.24 ppm (3.7 Hz) for glucose; the multiplet at 4.12 ppm for lactic acid; the doublet at 1.38 ppm (6.8 Hz) for acetoin; and the doublet at 1.13 ppm (5.8 Hz) for 2,3-butanediol. The obtained date demonstrated that treatment with manool induced a dose-dependent reduction of glucose consumption (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA) and increased the release of fermentative products into the growth medium (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB-D).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eExploiting Drug Affinity Responsive Target Stability (DARTS) to identify manool partners in\u003c/b\u003e \u003cb\u003eS. mutans.\u003c/b\u003e To identify the putative targets of manool in \u003cem\u003eS. mutans\u003c/em\u003e, DARTS experiments were performed on both protein extracts (peDARTS) and live bacterial cells (lbDARTS). However, to perform lbDARTS, it was necessary to design and set up a specific protocol that takes into account the significant biological, structural, morphological and functional differences between prokaryotic and eukaryotic cells. In particular, the most critical point was to reduce the proteome changes that occur during the incubation of \u003cem\u003eS. mutans\u003c/em\u003e cells with manool. Such changes could indeed affect the results of the DARTS. In fact, it would be difficult to understand whether differences observed in the quantity of undigested proteins depend on their protection from proteolysis by manool or on an increase in their level following the treatment of the bacteria with the diterpene. In that aims, we cultured \u003cem\u003eS. mutans\u003c/em\u003e in a reduced growth environment M9 medium containing 0.4% glucose, thus slowing down the metabolism of the bacterium, without losing the advantage of studying the interactions between manool and its protein targets inside the living cell. Indeed, although M9 is not the optimal medium for \u003cem\u003eS. mutans\u003c/em\u003e proliferation, it allows the bacteria to survive. In addition, as bacteria under restricted growth conditions may express a more selective set of proteins involved in stress responses or ligand interactions, the switch from rich to minimal medium may reduce the complexity of the proteome of the bacterium, making it easier to identify the putative targets of manool. Remarkably, the results obtained using the two approaches were in good agreement. Indeed, in both cases (Table.1 and 2), subunits of the ATP synthase complex were identified as putative manool targets, consistently with previously reported findings \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Furthermore, several proteins involved in transmembrane trafficking have emerged as possible interactors of manool most of which belong to the superfamily of ATP-binding cassette (ABC) transporters and to the phosphotransferase system (PTS). However, it has to be underlined that from lbDARTS only emerged membrane proteins, while using the cell lysate some cytosolic proteins were also identified. This difference highlights the importance of being able to conduct experiments on intact cells, in which all proteins have retained their native structure. Overall, the DARTS results shed a new light on the possible molecular mechanism underlying the antiproliferative effect of manool against \u003cem\u003eS. mutans\u003c/em\u003e, suggesting that it may depend, at least in part, on the impairment of extracellular transport. ABC transporters, which was the most represented protein group among those emerged from DARTS, play a key role in multiple vital processes for bacteria as they regulate both extrusion of toxic compounds and intake of nutrients \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Therefore, we carried out a series of assays aimed at confirming that manool actually interacts with proteins belonging to this family and evaluating if affecting their activity.\u003c/p\u003e\u003cp\u003e\u003cb\u003eValidation of ABC proteins as manool targets.\u003c/b\u003e ABCs act as efflux pumps (EPs) in both Gram-positive and Gram-negative bacteria, modulating cellular homeostasis and conferring resistance to antibiotics by expelling drugs and other toxic compounds \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Therefore, as a preliminary step, the effect of manool on \u003cem\u003eS. mutans\u003c/em\u003e efflux pumps was examined via an ethidium bromide (EtBr) accumulation assay. The obtained results showed that the addition of manool produced a dose-dependent increase in EtBr fluorescence (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA), thus demonstrating an inhibitory effect of manool on \u003cem\u003eS. mutans\u003c/em\u003e EPs. Based on these data, we further investigated the possible effect of manool in reducing the capability of \u003cem\u003eS. mutans\u003c/em\u003e to eliminate toxic compounds through ABC-mediated transport. In 2014, Nagayama et al. showed that isogenic mutant strains generated by inactivation of ABC efflux transporters were significantly more sensitive to aminoglycosides and tetracyclines antibiotics \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Therefore, to support the hypothesis that manool affects ABCs activity, we evaluated the effect of the diterpene on the antibacterial action of the aminoglycoside drug kanamycin. We measured the MIC100 against \u003cem\u003eS. mutans\u003c/em\u003e of kanamycin alone (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB) and in combination with manool (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC) and a significant increase in the antibiotic effect was observed when the bacteria were treated with both compounds. Indeed, the MIC 100 of kanamycin alone on \u003cem\u003eS. mutans\u003c/em\u003e was found to be 227 \u0026micro;M while in combination with 10 \u0026micro;M of manool, it became almost 10 times lower (28.4 \u0026micro;M). To assess whether the increase in kanamycin activity was due to an additive or synergistic effect, we calculated the fractional inhibition concentration index (FICI) value for manool and kanamycin (S1 Table). Processing the data in accordance with the criteria described by Cos P \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e, a FICI value of 0.62 was obtained, which is borderline between those associated with additivity and synergism. We supposed that such enhancement of the kanamycin efficacy induced by manool relays on a reduced capacity of ABCs to expel kanamycin from the cell. To confirm this, we evaluated whether the presence of manool influenced the extracellular levels of the antibiotic. Therefore, we measured by LC-MS/MS for 120 min the kanamycin concentration in the medium of \u003cem\u003eS. mutans\u003c/em\u003e cultured with kanamycin (28.375 \u0026micro;M) alone or with different concentrations of manool (2.5, 5, 10 \u0026micro;M). The results (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD) showed that the presence of a concentration of manool of 5 or 10 \u0026micro;M strongly reduced kanamycin extrusion. Remarkably, the presence of 10 \u0026micro;M of the diterpene also affected the kinetics of detoxification (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE). In the other tested conditions, the bacterium was able to expel very quickly the antibiotic, which then undergoes a slow consumption; in the presence of 10 \u0026micro;M manool, however, this expulsion seemed to practically not occur, as inferred by the very low levels of kanamycin measured already after 5 min of incubation and which then remained almost constant. As previously stated, the ABC proteins are also responsible for the intake of many nutrients for bacteria \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e, Therefore, to further validate the DARTS result, we analysed the effect of manool treatment on nutrients trafficking in \u003cem\u003eS. mutans\u003c/em\u003e. Since several ABC proteins identified by DARTS are involved in amino acid (AA) transmembrane transport (Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), we monitored the AA uptake in growing bacteria incubated with different concentrations of manool. We measured the changes over time in AAs concentration in the culture medium of \u003cem\u003eS. mutans\u003c/em\u003e during growth in the presence of three sub-MIC concentrations of manool (2.5, 5 and 10 \u0026micro;M) or in manool free medium. Obtained results showed that in the manool free medium (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA-E, black line) a decrease of around 30% in the AA concentration took place upon the first 150 min of incubation. Subsequently, the AAs level remained essentially constant. Remarkably, the lag-phase of \u003cem\u003eS. mutans\u003c/em\u003e growth lasts exactly 150 min (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). This result indicated that most of the AA uptake by the bacteria occurs before the exponential growth begins \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. In the presence of the diterpene, no significant changes in the AAs concentration in the medium was observed for most of the monitored AA (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA-D, red line and Fig. S3A-D.), suggesting manool to prevent the uptake of many AAs by the bacteria. Interestingly, glutamine levels in the medium of treated and untreated cells were comparable (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE and Fig. S3E.). This evidence actually constitutes a further confirmation of our hypothesis. In fact, given the peculiar role played by glutamine as a source and transporter of amino groups, bacterial cells have many systems involved in the transport of this AA unlike the others \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eEnriched proteins in the manool protein extract DARTS sample.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAccession\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMass\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDescription\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ8DT62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e29,9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePutative ABC transporter, glutamine binding protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ8DW32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e28,3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePutative ABC transporter, ATP-binding protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ8DU84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePutative ABC transporter, ATP-binding protein, proline/glycine betaine transport system\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ00751\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e31,6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMultiple sugar-binding transport system permease protein MsmG\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ00750\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e31,9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMultiple sugar-binding transport system permease protein MsmF\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ8DW36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e27,6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePutative ABC transporter, ATP-binding protein amino acid transport system\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ8DTB0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e35,9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eABC transporter substrate-binding protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ8DSC5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e17,3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eABC transporter permease\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ8DSU1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e30,7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePutative branched chain amino acid ABC transporter, permease protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ8DTY2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e23,8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePutative amino acid ABC transporter, permease protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eI6L8X6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e52,6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePutative PTS system, membrane component possible ribulose-monophosphate PTS pathway enzyme IIC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eI6L915\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e35,3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePTS system, sorbitol phosphotransferase enzyme IIBC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ8DWF7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e30,3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePutative PTS system, IID component\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ8DUI0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45,2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eATP-dependent Clp protease ATP-binding subunit ClpX\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eP95788\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e32,3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eATP synthase gamma chain\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ8DVK4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e33,7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMethionyl-tRNA formyltransferase\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eI6L8Z9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e20,5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDUF177 domain-containing protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ93D93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e32,7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eProtease HtpX homolog\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ8DVQ8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e15,6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePutative Hit-like protein involved in cell-cycle regulation\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ8DUG3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e48,4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePutative folyl-polyglutamate synthetase\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ8DTK0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e28,9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePutative alpha/beta superfamily hydrolase\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ8DVH1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePDZ domain-containing protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eEnriched proteins in the manool bacterial cells DARTS sample.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAccession\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMass\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDescription\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ8DUA1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e60,8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eABC transporter permease\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ8CM14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e25,9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePutative ABC transporter ATP-binding protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ8DTD8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e93,2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePutative ABC transporter, membrane protein subunit and ATP-binding protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ8DUD7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e37,7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePutative ABC transporter, periplasmic ferrichrome-binding protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eI6L8X8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45,5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePutative polysaccharide ABC transporter, ATP-binding protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ8DT62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e29,9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePutative ABC transporter, glutamine binding protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ8DUJ5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e31,8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePutative amino acid ABC transporter, periplasmic amino acid-binding protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ8DUT7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e80,2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePutative glutamine ABC transporter, permease protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ8DW22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e39,1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePutative oligopeptide ABC transporter, ATP-binding protein OppD\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ8DRU8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e43,4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePutative osmoprotectant amino acid ABC transporter, ATP-binding protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ8DTB0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e35,9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eABC transporter substrate-binding protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ8DVL9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e27,7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePutative amino acid ABC transporter, ATP-binding protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ8DUJ2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e28,3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePutative amino acid ABC transporter, ATP-binding protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ8DSC4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e35,5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePTS system mannose-specific EIIAB component\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ8DSC3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e28,1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePutative PTS system, mannose-specific component IIC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ8DS73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e15,2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePutative PTS system, sugar-specific enzyme IIA component\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ8DWF8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e28,2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePutative sorbose PTS system, IIC component\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ8DWF7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e30,3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePutative PTS system, IID component\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ8DS74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e18,2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePutative PTS system, mannose-specific IIB component\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eI6L8X9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e12,9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePutative PTS system, sorbitol-specific enzyme IIA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eP95786\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e20,4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eATP synthase subunit delta\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eP95788\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e32,3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eATP synthase gamma chain\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eComputational studies for the identification of manool binding mode to ABCs.\u003c/b\u003e Manool exhibits inhibition of diverse ABC transporters, likely by engaging conserved ATPbinding domains. Building on its known fit within the ATP site of human ATPsynthase, we computationally assessed its affinity for ABC ATPase subunits. As a model we selected the multiple sugarbinding ABC ATPbinding protein from \u003cem\u003eStreptococcus mutans\u003c/em\u003e (Q00752), the only target with a reliable 3D template. A dimeric homology model was generated, validated by a Ramachandran plot (S4 Fig), and refined with a 400 ns moleculardynamics (MD) simulation that stabilized after ~\u0026thinsp;150 ns (CαRMSD\u0026thinsp;\u0026asymp;\u0026thinsp;4 \u0026Aring;; Fig. S5). From the last 200 ns we extracted 200 snapshots and docked manool into each using AutoDockGPU, producing 400 poses. RMSDbased clustering (\u0026le; \u0026Aring;, \u0026ge; 10 % poses) yielded four clusters (Fig. S6). Additional 400 ns MD of each complex showed clusters 1 and 3 were stable (mean ligand RMSD 3.0 and 2.3 \u0026Aring;), whereas clusters 2 and 4 were not (8.3 and 6.5 \u0026Aring;; Fig. S7). MMPBSA analysis on the final 350 ns identified cluster 3 as the most favorable binding mode (S2 Table ΔG_bind = \u0026minus;\u0026thinsp;17.0 kcal mol⁻\u0026sup1;), 7.9 kcal mol⁻\u0026sup1; better than the next best pose, supporting it as the preferred interaction geometry. Figure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e illustrates the predicted binding mode of manool from cluster 3. The trimethyldecahydronaphthalene moiety fits into a hydrophobic pocket, interacting with Y13, P14, T46, and I221 of monomer A, likely contributing to ligand stabilization. Meanwhile, the hydroxyl group establishes two stable hydrogen bonds: one with the backbone nitrogen of K213 and another via a water-mediated interaction with the side chain of the same residue (K213). These interactions likely play a role in further anchoring the ligand within the pocket, reinforcing its stability. Interestingly, the second monomer of the dimeric system does not appear to engage in direct stabilizing interactions with the ligand. However, its presence may contribute to the overall binding mode by providing structural constraints that help maintain the proper orientation of the ligand within the binding site. According to MM-PBSA analysis, this binding mode benefits from both hydrophobic and electrostatic interactions, supporting its stability and potential biological relevance.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe search for new antibiotics is being given a significant boost due to the increasingly dramatic problem of antibiotic resistance. In this context, a key role can be played by compounds directed to molecular targets that are still under-exploited. Such molecules have two main advantages: they could be effective against (multi)resistant bacteria and they could enhance the effect of drugs acting on more classical targets. Plants are a rich source of potent antimicrobial compounds, but the lack of information on their mode of action is limiting their use as therapeutic agents. The availability of data on the molecular mechanisms underlying the biological effect of these compounds would allow to fully understand the potential of their use, to evaluate the putative synergism with other drugs and to predict possible undesired or secondary effects. Therefore, the implementation of methods for the reliable identification of the molecular targets of antimicrobial compounds is an urgent need. Such methods may also reveal new druggable proteins in bacteria, paving the way to new therapeutic approaches that overcome antimicrobial resistance. Here we set up a protocol for the trustworthy definition of protein targets of antimicrobial agents, using a combination of DARTS experiments. DARTS is compound-centric proteomic approach widely used in eukaryotic systems (15, 16), which provides reliable results when used on both protein extracts and intact and living cells. Indeed, the first approach allows identifying all the protein showing any affinity towards the investigated compound, but it provides no information on the actual ability of the molecule to cross the bacterial envelope; moreover, the cell lysis procedure, even if optimized to preserve protein native structure, could significantly affect stability of membrane proteins, thus limiting their ability to interact with bioactive compounds. These criticisms are almost completely by-passed using the cell-based assay, which also provides insights into interactions occurring with proteins in their physiological environment. However, the incubation of living cells with a bioactive compound may result in significant changes in the proteome, thus making difficult to correctly identify the proteins protected from proteolysis by a direct interaction with the investigated molecule. This problem is more serious the faster the cells change and may therefore be critic for procaryotic cells. Possibly, this is the reason why other studies have applied DARTS to bacteria only using cell lysates \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. However, given the complementarity of the two DARTS approaches, we set up optimized conditions allowing to perform the assay also on living bacteria. The results we obtained confirmed the importance of this choice. We used our protocol to investigate the antibiotic effect of the plant diterpene manool, which has promising activity towards gram-positive bacteria, against \u003cem\u003eS. mutans\u003c/em\u003e. Interestingly, lbDARTS demonstrated that manool is able to interact only with proteins located on the cell membrane. Obviously, this data could not emerge from peDARTS, in which the accessibility of proteins to manool is not limited by the cellular structure. However, even peDARTS experiments confirmed some of the putative targets identified using living bacteria, but obviously they also suggested some possible interactors that are probably not actually reachable by manool. Among the protein identified by DARTS assays, we focused on the ABC transporters, based on the critical role they play in bacteria and the number of proteins belonging to this family emerged from compound-centric proteomic studies. These ATP-dependent membrane proteins mediate the uptake of many nutrients \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e and the efflux of toxic compounds \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Therefore, in order to corroborate and refine the results of DARTS, we performed a set of experiments aimed at evaluating the effects of manool treatment of \u003cem\u003eS. mutans\u003c/em\u003e on transmembrane transport of different molecules. The obtained results clearly supported the hypothesis that inhibition of some ABCs by manool underlays the bioactivity of this diterpene. Indeed, incubation of \u003cem\u003eS. mutans\u003c/em\u003e with manool under conditions not affecting the bacteria vitality reduced the efficacy of the efflux pump system that mostly consists of ABC proteins. Coherently, manool reduced the extrusion and enhanced the antibacterial action of kanamycin, an aminoglycoside antibiotic the resistance to which is mediated by the ABCs themselves \u003csup\u003e\u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e.While these findings validate the DARTS results, they do not fully explain manool own antiproliferative activity. Nevertheless, ABC transporters play essential roles in nutrient uptake, ion balance and cellular regulation, making them critical for bacterial proliferation. Notably, manool treatment caused a marked decrease in amino acid consumption, particularly during the lag phase, when untreated bacteria typically absorb high levels of amino acids. This evidence may thus explain the prolongation of the lag phase of growth observed when \u003cem\u003eS. mutans\u003c/em\u003e bacteria are incubated with manool. Indeed, it is plausible that when the bacteria are treated with manool become unable to take up the metabolites needed to activate cell duplication; therefore, they stay longer in a non-proliferative condition trying to accumulate the required nutrients. This hypothesis is supported by evidence that treatment of \u003cem\u003eS. mutans\u003c/em\u003e with manool during the exponential phase of growth produces negligible effects, suggesting that the action of the diterpene is most critical when the bacteria are increasing their intracellular nutrient levels before initiating proliferation. The effects of manool on bacteria metabolism were clearly highlighted by monitoring the variation in glucose concentration in the medium of \u003cem\u003eS. mutans\u003c/em\u003e treated or not with manool. Indeed, the NMR-based analysis revealed that manool significantly reduces glycolysis, which is a critical pathway for \u003cem\u003eS. mutans\u003c/em\u003e in maintaining its energy production, particularly in the context of dental plaque formation and acid production \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. This trend was clearly dependent on the concentration of manool, suggesting that incubation with the diterpene inhibits glucose metabolism in \u003cem\u003eS. mutans\u003c/em\u003e. However, the interpretation of these results cannot be univocal. On the one hand the variations observed in the glucose consumption depend on the differences in the number of bacterial cells in the different conditions. In fact, the graph of lactic acid over time (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB) is almost superimposable to the growth curves of \u003cem\u003eS. mutans\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). On the other hand, since among the ABCs emerged from DARTS there was also a monosaccharide transporter, we cannot exclude that the inhibition of glycolysis may depend, at least in part, on the reduction of the efficiency of glucose availability to the bacterium. However, manool interferes with nutrient uptake by inhibiting ABC transporters, thus affecting the essential metabolism of \u003cem\u003eS. mutans\u003c/em\u003e, causing stress, delaying adaptation and reducing growth. The dual effect to reduce antibiotic resistance and to inhibit proliferation produced by manool on \u003cem\u003eS. mutans\u003c/em\u003e is in agreement with DARTS results, which revealed the ability of the compound to interact with several ABC transporters. This multiplicity of targets of the diterpene is quite surprising since ABCs consist of a structurally heterogenous class of proteins. However, they all intrinsically carry an ATP-binding site, which is generally located in dimeric subunits that can also regulate the activity of different transporters \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Based on this information and on the previously reported data supporting the ability of manool to occupy effectively specific ATP-binding pockets \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e, we supposed that manool modulates ABCs activity interacting with the ATP-binding subunit/domain of these proteins. The results of our calculations strongly supported this hypothesis, allowing to describe in detail the interactions stabilizing the manool-protein complex. This binding mode could in fact explain how a single molecule can act as a ligand for numerous proteins, affecting their biological activity. Given the importance of this family of proteins, their number and their abundance in prokaryotic cells, the results we have reported could open the way to the development of new molecules active towards these targets. The opportunity to enhance antibiotic drug efficacy by inhibiting ABC transporters has been previously reported \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. However, here ABCs emerged from a fully untargeted approach, in which compound-protein interactions have been directly observed under conditions mimicking physiological ones, and in the presence of all the proteins and molecules that could interfere or compete with these interactions. in this perspective, the experimental protocol we used has proven to be a very useful tool both to explain, at least in part, the mechanism of action of manool, and to identify new targets for the development of innovative therapeutic agents.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cb\u003eReagents and materials.\u003c/b\u003e Growth Media Brain Heart Infusion Broth (Oxoid) and M9 Minimal Salts Base (Na\u003csub\u003e2\u003c/sub\u003eHPO\u003csub\u003e4\u003c/sub\u003e, H\u003csub\u003e2\u003c/sub\u003eO, KH\u003csub\u003e2\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e, NaCl, NH\u003csub\u003e4\u003c/sub\u003eCl) 5X were used. Solvents: Ultra-pure water (ROMIL-UpsTM Ultra purity), ultra-pure acetonitrile (ROMIL-UpsTM Ultra purity), ultrapure water (18 MΩ), and DMSO (Sigma-Aldrich) were utilized for the preparation of solutions and reagents. Buffers: The following buffers were used: Dulbecco\u0026rsquo;s Modified Eagle\u0026rsquo;s Medium (DMEM, Sigma-Aldrich), MOPS, Tris-HCl (1.5 M pH 8.8 and 1.0 M pH 6.8), Laemmli Buffer, TGS (Tris/Glycine/SDS buffer 5X, Bio-Rad), and AMBIC. Reagents: MTT (4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide (Invitrogen) was used for cell viability assays. Other reagents included subtilisin, acrylamide 30% (AppliChem), sodium dodecyl sulfate (SDS), ammonium persulfate (APS), tetra-methylenediamine (TEMED), dithiothreitol (DTT, AppliChem), iodoacetamide (IAA, AppliChem), and trypsin (proteomic grade, 0.0013 \u0026micro;g/\u0026micro;l). Standards: Kanamycin sulfate (ChemCruz), and chlorhexidine (MCE\u0026reg;) were used as standards in the experiments. The manool was previously purified from \u003cem\u003eSalvia. officinalis\u003c/em\u003e and was thus already available as a pure molecule. It was solubilized in DMSO at a concentration of 5 mg/ml and stored at -20\u0026deg;C prior to use. Deuterium oxide (D\u003csub\u003e2\u003c/sub\u003eO, 99.90% D), and 3-(trimethylsilyl) propionic-2,2,3,3-d4 acid sodium salt (TSP) and KH\u003csub\u003e2\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e saltfor NMR analysis were purchased from Sigma-Aldrich Chemical Company (Sigma-Aldrich,Milano, Italy).\u003c/p\u003e\u003cp\u003e\u003cb\u003eBacterial Culture.\u003c/b\u003e \u003cem\u003eStreptococcus mutans\u003c/em\u003e Clarke NCTC (National Collection of Type Cultures) 10499 was grown in liquid Brain Heart Infusion (BHI) medium at 37\u0026deg;C under aerobic conditions for 18\u0026ndash;24 hours. Solid culture was performed on BHI medium with 1.5% agar on a 60 cm\u0026sup2; Petri dish (100 x 20 mm) at 37\u0026deg;C for 48 hours.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMinimum Inhibitory Concentration (MIC).\u003c/b\u003e The minimum inhibitory concentration (MIC) was assessed using the serial dilution method, in accordance with the CLSI protocol \u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e Manool concentrations ranging from 40 \u0026micro;M to 2.5 \u0026micro;M were tested on \u003cem\u003eS. mutans\u003c/em\u003e. Serial dilutions were performed in a 96-well plate to achieve the desired antimicrobial concentrations (40 \u0026micro;M, 20 \u0026micro;M, 10 \u0026micro;M, 5 \u0026micro;M, 2.5 \u0026micro;M). \u003cem\u003eS. mutans\u003c/em\u003e was inoculated into the plate at a density of 1 x 10⁶ CFU/ml. The plate was then incubated at 37\u0026deg;C. After 24 hours, the bacterial growth inhibition values were evaluated using a spectrophotometer at a wavelength of 600 nm. The positive control was performed with the antibiotic chlorhexidine. All tests were performed in triplicate\u003c/p\u003e\u003cp\u003e\u003cb\u003eBacterial Growth Curve.\u003c/b\u003e The growth curves of \u003cem\u003eS. mutans\u003c/em\u003e were evaluated in both the presence and absence of manool. Cultures were initiated at 0.05 OD600 and then cultivated at 37\u0026deg;C with agitation. Manool was added to three flasks at concentrations of 2.5 \u0026micro;M, 5 \u0026micro;M and 10 \u0026micro;M. Bacterial growth was measured using OD600 readings every 30 minutes for 660 minutes. In a separate experiment, manool was added at an OD600 of 0.5 in cultures that had previously been diluted to 0.2 OD600. Growth was then monitored every 30 minutes for a further 210 minutes\u003c/p\u003e\u003cp\u003e\u003cb\u003eCell Viability Assay (MTT)\u003c/b\u003e. The cell viability assay was conducted using the \u0026ldquo;HaCaT\u0026rdquo; cell line, immortalized human keratinocytes. The cells were maintained in culture with DMEM 1X (Dulbecco\u0026rsquo;s Modified Eagle\u0026rsquo;s Medium) containing 4.5 g/L glucose, 2 mM glutamine, 10% fetal bovine serum (FBS), penicillin (100 units/ml), and streptomycin (100 units/ml) at 37\u0026deg;C in a controlled atmosphere with 5% CO\u003csub\u003e2\u003c/sub\u003e. The MTT colorimetric assay is based on the intracellular reduction of the tetrazolium salt (yellow color) by the mitochondrial enzyme succinate dehydrogenase (SDH) into formazan, which, due to its insolubility in the culture medium, precipitates as dark blue-violet crystals. HaCaT cells (immortalized human keratinocytes) were plated in 96-well plates (5000 cells/well). After 24 hours, they were treated with manool (5-160 \u0026micro;M) for 24 hours, and DMSO at 0.1% was used as the negative control. The MTT assay was performed by incubating the cells with 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) at a final concentration of 1 mg/mL. The plates were incubated at 37\u0026deg;C for 3 hours. Subsequently, a lysis buffer (20% SDS; 50% dimethylformamide, adjusted to pH 4.7 with a mixture of 80% acetic acid and 1 N HCl) was added and incubated for 18 hours. Finally, absorbance values were obtained by reading the spectrophotometer in a wavelength range between 570 and 610 nm.\u003c/p\u003e\u003cp\u003e\u003cb\u003eDrug Affinity Responsive Target Stability Assay on protein extract (pe-DARTS).\u003c/b\u003e A gel with 12% polyacrylamide concentration was prepared as follows: \u0026ldquo;Resolving gel 12%\u0026rdquo; (for a final volume of 10 ml): 3.3 ml distilled H₂O, 4.0 ml 30% acrylamide, 2.5 ml Tris-HCl 1.5 M pH 8.8, 0.1 ml 10% SDS, 0.1 ml 10% ammonium persulfate (APS) (initiator), 0.004 ml TEMED (catalyst); \u0026ldquo;Stacking gel\u0026rdquo; (for a final volume of 3 ml): 2.1 ml distilled H₂O, 0.5 ml 30% acrylamide, 0.38 ml Tris-HCl 1.0 M pH 6.8, 0.03 ml 10% SDS, 0.03 ml 10% ammonium persulfate (APS), 0.03 ml TEMED. For sample resuspension and electrophoresis, the following solutions were used: \u0026ldquo;SDS gel-loading buffer\u0026rdquo; (Laemmli Buffer): Tris 0.125 M pH 6.8 (for protein denaturation), 4% SDS (w/v), 0.4% bromophenol blue (w/v) (dye), 40% glycerol (v/v) (to increase sample density for loading into wells), 10% β-mercaptoethanol (v/v) (to break disulfide bonds between cysteines); \u0026ldquo;Running buffer\u0026rdquo; (for a final volume of 1 L): 800 ml deionized H₂O, 200 ml 5x TGS (Tris/Glycine/SDS buffer). Electrophoresis was performed at 100 V for 20 minutes and continued at 180 V for 40 minutes. After electrophoresis, the proteins were fixed in gel using the fixing solution (50% H₂O, 40% MeOH, 10% CH₃COOH), and 10 bands were excised from each lane and subjected to trypsin digestion. The tryptic digestion selectively cleaves peptide bonds on the carboxyl side of arginine and lysine residues, generating highly characteristic fragments for each protein. Each band was transferred into respective Eppendorf tubes and subjected to a washing step with acetonitrile (ACN) three times to dehydrate the gel fragments. After removing the ACN solution, 0.01 M DTT in 0.1 M ammonium bicarbonate (AMBIC) was added. The reduction reaction was carried out for 60 minutes at 56\u0026deg;C. Then, the supernatant was removed and another three washes with ACN were performed. After removing the ACN, a 0.055 M iodoacetamide (IAA) in AMBIC 0.1 M solution was added. The alkylation reaction was carried out for 30 minutes at room temperature in the dark. After removing the supernatant, the bands were washed again with ACN and dried in a Speed-Vac for 15 minutes. Subsequently, the actual digestion was performed: 30 \u0026micro;l of a trypsin solution (Proteomic grade, 0.0013 \u0026micro;g/\u0026micro;l) in 25 mM AMBIC was added to each band to cover them, and each was incubated at 4\u0026deg;C for 45 minutes to allow the enzyme to penetrate the gel bands. Finally, 20 \u0026micro;l of 25 mM AMBIC was added to completely cover the gel fragments. The reaction was continued overnight at 37\u0026deg;C to optimize enzyme activity. After incubation, peptide extraction was performed. First, ACN was added and the eppendorfs were incubated for 15 minutes at 37\u0026deg;C. After the reaction, the supernatant was recovered and placed in clean Eppendorf tubes. The extraction solution containing the peptides of interest was dried in a Speed-Vac. The dried peptides were resuspended in 1% formic acid (FA) and analyzed by mass spectrometry All obtained data are available in \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://zenodo.org/records/15743861\u003c/span\u003e\u003cspan address=\"https://zenodo.org/records/15743861\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cb\u003eDrug Affinity Responsive Target Stability Assay on Living Bacterial Cells (lbDARTS).\u003c/b\u003e The \u003cem\u003eS. mutans\u003c/em\u003e overnight inoculum was centrifuged at 3000 rpm for 15 minutes, and the cells were resuspended in BHI medium to a density of 0.05 OD/ml. The cells were incubated at 37\u0026deg;C and cultured to the established optical densities (0.5 OD/mL and 1 OD/mL). Then cells were centrifuged at 3000 rpm for 15 minutes. After discarding the supernatant, the pellet was resuspended in M9 minimal medium 1X supplemented with 0.4% glucose for both control and treated samples, at a density of 0,5 OD/ml and 1 OD/mL. The treated samples were incubated with manool at 5 \u0026micro;M and 10 \u0026micro;M for 90 minutes. The samples were then centrifuged at 3000 rpm for 10 minutes. After discarding the supernatant, the pellets were resuspended in 25 mM MOPS buffer. The cells were then lysed following the previously described protocol.\u003c/p\u003e\u003cp\u003e\u003cb\u003eEfflux pump assay.\u003c/b\u003e An ethidium bromide (EtBr) accumulation assay was performed to assess membrane transport activity in \u003cem\u003eS. mutans\u003c/em\u003e, following Overnight cultures were washed and resuspended in PBS at a concentration of 0.6 OD600/mL. Manool (0.75\u0026ndash;6 \u0026micro;g/mL) and EtBr (2 \u0026micro;g/mL) were added to the wells of a 96-well plate, with DMSO and MeOH (0.5%) serving as controls. Fluorescence was measured every 60 seconds for 60 minutes at 37\u0026deg;C (excitation: 525 nm; emission: 605 nm).\u003c/p\u003e\u003cp\u003e\u003cb\u003eDetermination of Activity in Combination with other antibiotics.\u003c/b\u003e The synergistic effect of manool and kanamycin against \u003cem\u003eS. mutans\u003c/em\u003e was evaluated. First, the MIC100 of kanamycin was determined via serial dilution (14.2\u0026ndash;227 \u0026micro;M). Subsequently, any synergy between manool and kanamycin was evaluated by using subMIC concentrations of kanamycin, in the presence of a single concentration of manool (10 \u0026micro;M), corresponding to its MIC50.The plate was incubated at 37\u0026deg;C. After 24 hours, the values of bacterial growth inhibition were evaluated using a spectrophotometer at a wavelength of 600 nm. The results were interpreted by calculating the fractional inhibitory concentration (FIC) index for kanamycin and quantifying the nature of the pharmacological interaction in vitro (synergy, additivity, indifference, or antagonism. \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eLC-MS analysis of kanamycin and amino acids.\u003c/b\u003e To assess the presence of kanamycin and amino acids in \u003cem\u003eS. mutans\u003c/em\u003e culture supernatants, LC-MS analyses were performed using an ABSCIEX API 6500 QTRAP\u0026reg; mass spectrometer coupled to a Nexera X2 UPLC Shimadzu system, operating in positive ion mode. Samples were diluted 1:1000 in ultrapure water to preserve column integrity and avoid signal saturation. For kanamycin, supernatants from cultures treated with kanamycin alone (28.37 and 56.75 \u0026micro;M) and in combination with manool (2.5, 5, and 10 \u0026micro;M) were analyzed. For amino acids, supernatants from untreated and manool-treated cultures (2.5, 5, and 10 \u0026micro;M) were examined. Chromatographic separation was performed on a Luna\u0026reg; Omega column with formic acid in water and organic solvents (methanol or acetonitrile, depending on the analysis) under gradient conditions. Amino acid detection employed Multiple Reaction Monitoring (MRM) transitions based on previously validated methods \u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. Full dataset is available at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5281/zenodo.15696464\u003c/span\u003e\u003cspan address=\"10.5281/zenodo.15696464\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cb\u003eNMR sample preparation.\u003c/b\u003e NMR sample preparation was performed as previously reported by \u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e with slight modifications. Supernatants for NMR analysis were collected as described into paragraph 2.4 and centrifuge at 10000 g for 5 minutes at 4\u0026deg;C to remove the particulate matter. 540 \u0026micro;L of obtained clear supernatants were added to 60 \u0026micro;L of a mono-potassium phosphate solution (90 mM KH\u003csub\u003e2\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e in D\u003csub\u003e2\u003c/sub\u003eO, pH 6.5) and transferred to 5 mm NMR tubes. Trimethylsilyl propionic-2,2,3,3-d4 acid, sodium salt (TSP-d4 0.01% in D\u003csub\u003e2\u003c/sub\u003eO) was used as an internal reference for alignment of NMR spectra.\u003c/p\u003e\u003cp\u003e\u003cb\u003eNMR spectroscopy and processing.\u003c/b\u003e The NMR experiments were carried out as previously reported by\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e with slight modifications, optimizing the acquisition parameters. Spectra were acquired on a Bruker Avance 600 spectrometer equipped with a 5 mm ATMA cryo-probe operating at 298 K and a SampleJet changer. TopSpin V3.2 software (Bruker Biospin,Wissembourg, France) was used for NMR data acquisition and processing, and its IconNMR module controlled the automation of acquisition (locking, tuning, matching, and shimming). \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003eH NMR spectra were recorded using a 1D-NOESY (noesygppr1d) pulse sequence with water signal suppression \u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. The acquisition parameters were: 19K data points, 2782.7 Hz (11 ppm) spectral width, 4 dummy and 128 scans, a recycle delay of 5 s, and a fixed value for receiver gain for all samples. To achieve a high confidence level of metabolites annotations, 2D NMR experiments (HSQC, HMBC, COSY) and 1D TOCSY were also recorded. Phase corrections and baseline editing were performed manually for all spectra using TOPSPIN version 3.2.\u003c/p\u003e\u003cp\u003e\u003cb\u003eNMR data analysis.\u003c/b\u003e \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003eH NMR spectra were processed using NMRProcFlow 1.4.28 (INRA UMR 1332 BFP, Bordeaux Metabolomics Facility, Villenave d\u0026rsquo;Ornon, France) \u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. The ppm calibration was made using the internal standard at 0 ppm and the peaks alignment was applied on all \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003eH NMR spectra. Variable size bucketing was used to integrate the signals of key metabolites. The data matrix was exported, and the areas obtained were used to determine the level of selected metabolites in bacteria supernatants. The metabolites annotation was achieved using Chenomx NMR-Suite v12 (Chenomx Inc.), online databases (HMDB, SpectraBase) and in-house library. 2D NMR spectra were analysed using TOPSPIN version 3.2. Full dataset is available at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5281/zenodo.15696464\u003c/span\u003e\u003cspan address=\"10.5281/zenodo.15696464\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cb\u003eHomology Modeling.\u003c/b\u003e All the primary sequences were obtained from the SWISS-PROT protein sequence database \u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. Sequence similarity searches were carried out using Blast. The crystal structure of the multiple sugar-binding protein (6PUW) was taken from the Protein Data Bank. The sequence alignment of the chosen protein was performed by Modeller 10.5\u003csup\u003e44\u003c/sup\u003e with a gap creation penalty of 900 and a gap extension penalty of 50. Five structures were generated by means of the Automodel protocol, as implemented in Modeller, and the best receptor model was chosen on the basis of the Discrete Optimized Protein Energy (DOPE) assessment method and minimized. The backbone conformation of the resulting receptor structures was evaluated by inspection of the Ramachandran plot. The protein was minimized using Amber22 software\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e and ff14SB force field at 300 K. The protein was placed in a rectangular parallelepiped waterbox; the TIP3P explicit solvent model for water was used and the complex was solvated with a 15 \u0026Aring; water cap. Chlorine ions were added as counterions to neutralize the system. Two steps of minimization were then carried out. In the first stage, we kept the protein fixed with a position restraint of 500 kcal/mol\u0026middot;\u0026Aring;\u003csup\u003e2\u003c/sup\u003e and we solely minimized the positions of the water molecules. In the second stage, we minimized the entire system through 5000 steps of steepest descent followed by conjugate gradient (CG) until a convergence of 0.05 kcal/\u0026Aring; mol.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMD Simulations.\u003c/b\u003e The minimized protein was used as input structures for the MD simulations, which were run using Particle Mesh Ewald (PME) electrostatics, a cutoff of 10 \u0026Aring; for the non-bonded interactions and all the parameters reported above. SHAKE algorithm was used to constrain all bonds involving hydrogen atoms and a time step of 2.0 fs was thus used for the simulation. Initially, a MD heating stage of 50 ns, in which the temperature of the system was raised from 0 to 300 K, was performed using constant-volume periodic boundary conditions. In all these steps all α carbons of the protein were subjected to a harmonic potential of 10 kcal/mol\u0026bull;\u0026Aring;\u003csup\u003e2\u003c/sup\u003e. Finally, a production step of 350 ns was performed maintaining the same temperature and pressure conditions but removing any harmonic restraint, thus leaving the system totally free. In total, the protein was thus subjected to 400 ns of MD simulation.\u003c/p\u003e\u003cp\u003e\u003cb\u003eDocking studies.\u003c/b\u003e The compound cpd01 was docked into the final 200 conformations of the multiple sugar-binding transport ATP-binding protein using Autodock-GPU \u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e with the ADP molecule from 3PUW defining the center of the binding site. For each docking calculation, the following parameters were used: 100 LGA runs with 10000000 score evaluations, 10000000 generations and 500 as population size per run. An RMSD clustering tolerance of 2.0 \u0026Aring; was used. The 400 docking solutions were clustered by using an in-house python script and by considering only clusters with a population of at least 40 docking results. The resulting clusters were then subjected to MD simulations. For each protein-ligand complex, all parameters reported above were used. General Amber force field (GAFF) parameters were used for the ligand, whose partial charges were assigned using the Antechamber suite of Amber22, based on the AM1-BCC method. As reported above, two steps of minimization were then carried out. In the first stage, we kept the protein fixed with a position restraint of 500 kcal/mol\u0026middot;\u0026Aring;\u003csup\u003e2\u003c/sup\u003e and we solely minimized the positions of the water molecules. In the second stage, we minimized the entire system through 5000 steps of steepest descent followed by conjugate gradient (CG) until a convergence of 0.05 kcal/\u0026Aring;\u0026middot;mol. For the MD simulations, a MD heating stage of 50 ns, in which the temperature of the system was raised from 0 to 300 K, was performed using constant-volume periodic boundary conditions with all α carbons of the protein subjected to a harmonic potential of 10 kcal/mol\u0026bull;\u0026Aring;\u003csup\u003e2\u003c/sup\u003e. Then, a production step of 350 ns was performed maintaining the same temperature and pressure conditions. In total, each complex analyzed was thus subjected to 400 ns of MD simulation. The final structure of the protein-ligand complex corresponded to the average of the last 350 ns of MD simulation minimized by the CG method until a convergence of 0.05 kcal/mol\u0026bull;\u0026Aring;\u003csup\u003e2\u003c/sup\u003e. The average structures were obtained using the Cpptraj program implemented in Amber22, which was also used for RMSD and H-bond analyses.\u003c/p\u003e\u003cp\u003e\u003cb\u003eBinding Energy Evaluation.\u003c/b\u003e The evaluation of the binding energy associated with the four protein-ligand complexes analyzed through MD simulations was carried out using AMBER22, as already reported \u003csup\u003e\u003cspan additionalcitationids=\"CR48\" citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e.The trajectories relative to the last 350 ns of each simulation were extracted and used for the calculation for a total of 350 snapshots (at time intervals of 1 ns). Van der Waals, electrostatic and internal interactions were calculated with the SANDER module of AMBER22, whereas polar energies were calculated using the Poisson-Boltzman methods with the MM-PBSA module of AMBER22. Dielectric constants of 1 and 80 were used to represent the gas and water phases, respectively. The entropic term was considered as approximately constant in comparison of the ligand-protein energetic interactions\u003c/p\u003e\u003cp\u003e\u003cb\u003eStatistical analysis\u003c/b\u003e. Data are presented as mean values with error bars representing standard deviation (SD) from at least two or three independent experiments. Significance levels are indicated as follows: \u003cem\u003ens\u003c/em\u003e (not significant), \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01 (*\u003cem\u003e), P\u0026thinsp;\u0026lt;\u0026thinsp;0.005 (\u003c/em\u003e**\u003cem\u003e), P\u0026thinsp;\u0026lt;\u0026thinsp;0.001 (\u003c/em\u003e***), \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001 (****). T-tests, one-way ANOVA were used for statistical evaluations.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u0026nbsp;\u003c/strong\u003eThe authors want to acknowledge Prof.Viviana Izzo for her suggestion and usefuld discussion.\u003c/p\u003e\n\u003cp\u003eThe research was partially supported by Project funded under the National Recovery and Resilience Plan (NRRP), Mission 4 Component 2 Investment 1.4 - Call for tender No. 3138 of December 16, 2021, rectified by Decree n.3175 of December 18, 2021 of Italian Ministry of University and Research funded by the European Union \u0026ndash; NextGenerationEU; Award Number: Project code CN_00000033, Concession Decree No. 1034 of June 17, 2022 adopted by the Italian Ministry of University and Research, CUP: D43C22001260001, Project title \u0026ldquo;National Biodiversity Future Center - NBFC\u0026rdquo;.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eCompeting Interest Statement:\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions: \u003cstrong\u003eRN:\u003c/strong\u003e\u003c/strong\u003e Microbiology, Data Analysis, Writing-original draft. \u003cstrong\u003eER:\u003c/strong\u003e Mass spectrometry analyses VP: NMR analyses.\u003cstrong\u003e\u0026nbsp;TT:\u003c/strong\u003e Computational studies, Writing-original draft\u003cstrong\u003e. \u003cstrong\u003eGD:\u003c/strong\u003e\u003c/strong\u003e Project administration, Data analysis, Writing-original draft, Conceptualization\u003cstrong\u003e\u0026nbsp;FDP:\u003c/strong\u003e Writing review \u0026amp; editing, Supervision, Conceptualization.\u003cstrong\u003e\u0026nbsp;NDT:\u003c/strong\u003e Writing, review \u0026amp; editing, Funding acquisition. All authors reviewed the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAkram, F., Imtiaz, M. \u0026amp; Haq, I. ul. Emergent crisis of antibiotic resistance: A silent pandemic threat to 21st century. \u003cem\u003eMicrob. Pathog.\u003c/em\u003e \u003cstrong\u003e174\u003c/strong\u003e, 1\u0026ndash;13 (2023).\u003c/li\u003e\n\u003cli\u003eAslam, B. \u003cem\u003eet al.\u003c/em\u003e Antibiotic Resistance: One Health One World Outlook. \u003cem\u003eFront. Cell. Infect. Microbiol.\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, 1\u0026ndash;20 (2021).\u003c/li\u003e\n\u003cli\u003eChhajer, R. \u0026amp; Ali, N. Genetically modified organisms and visceral leishmaniasis. \u003cem\u003eFront. Immunol.\u003c/em\u003e \u003cstrong\u003e5\u003c/strong\u003e, 1\u0026ndash;10 (2014).\u003c/li\u003e\n\u003cli\u003eDadgostar, P. 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Chem.\u003c/em\u003e \u003cstrong\u003e209\u003c/strong\u003e, 112857 (2021).\u003c/li\u003e\n\u003cli\u003eDi Stefano, M. \u003cem\u003eet al.\u003c/em\u003e Machine Learning-Based Virtual Screening for the Identification of Cdk5 Inhibitors. \u003cem\u003eInt. J. Mol. Sci.\u003c/em\u003e \u003cstrong\u003e23\u003c/strong\u003e, 10653 (2022).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"In-cell DARTS, natural product, antimicrobial, target identification","lastPublishedDoi":"10.21203/rs.3.rs-7204413/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7204413/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAntimicrobial resistance poses a significant threat to global health, highlighting the urgent need for novel therapeutic agents. Plant-derived compounds are a promising source of antimicrobial compounds. Given their huge structural variability, they putatively operate through a multiplicity of modes of action, interacting with various targets. The implementation of appropriate approaches aimed at reliably describe the molecular mechanism of these compounds, allows identifying promising hits, and new pharmacologically exploitable proteins. Here, we investigated the antimicrobial activity of manool, a diterpene isolated from \u003cem\u003eSalvia officinalis\u003c/em\u003e L. (Lamiaceae), against the dental pathogen \u003cem\u003eStreptococcus mutans\u003c/em\u003e. Using compound-centric proteomic techniques, we identified ATP-binding cassette (ABC) transporters as key targets of manool. These proteins are involved in nutrient uptake and in bacterial drug resistance. Implementing metabolomics approaches, we showed that manool inhibits ABCs, thereby impairing energy metabolism and delaying bacterial proliferation, and. enhancing the efficacy of the antibiotic kanamycin. Finally, based on the docking and molecular dynamics results we hypothesized that manool is able to interfere with the activity of various ABCs by occupying their ATP binding domain. This is the first time that ABCs have emerged from a completely untargeted approach as proteins responsible for the bioactivity of an antibacterial agent.\u003c/p\u003e","manuscriptTitle":"Disarming Streptococcus mutans in real time: live-cell DARTS uncovers ABC transporter targeting by manool","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-05 15:10:05","doi":"10.21203/rs.3.rs-7204413/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"cb8405b7-8b7f-4ea2-abd6-9cf4a884eeb5","owner":[],"postedDate":"August 5th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":52559552,"name":"Biological sciences/Microbiology/Antimicrobials"},{"id":52559553,"name":"Biological sciences/Biochemistry/Proteomics"},{"id":52559554,"name":"Biological sciences/Plant sciences"},{"id":52559555,"name":"Biological sciences/Drug discovery/Target identification"}],"tags":[],"updatedAt":"2026-03-16T12:37:05+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-05 15:10:05","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7204413","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7204413","identity":"rs-7204413","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}