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Metabolites 13 (2): 151 (2023)
Brown, Jennifer I.
Wang, Peng
Wong, Alan Y. L.
Petrova, Boryana
Persaud, Rosanne
Soukhtehzari, Sepideh
Lopez McDonald, Melanie
Hanke, Danielle
Christensen, Josephine
Iliev, Petar
Wang, Weiyuan
Everton, Daniel K.
Williams, Karla C.
Frank, David A.
Kanarek, Naama
Page, Brent D. G.
Dihydrofolate reductase (DHFR) is an established anti-cancer drug target whose inhibition disrupts folate metabolism and STAT3-dependent gene expression. Cycloguanil was proposed as a DHFR inhibitor in the 1950s and is the active metabolite of clinically approved plasmodium DHFR inhibitor Proguanil. The Cycloguanil scaffold was explored to generate potential cancer therapies in the 1970s. Herein, current computational and chemical biology techniques were employed to re-investigate the anti-cancer activity of Cycloguanil and related compounds. In silico modeling was employed to identify promising Cycloguanil analogues from NCI databases, which were cross-referenced with NCI-60 Human Tumor Cell Line Screening data. Using target engagement assays, it was found that these compounds engage DHFR in cells at sub-nanomolar concentrations; however, growth impairments were not observed until higher concentrations. Folinic acid treatment rescues the viability impairments induced by some, but not all, Cycloguanil analogues, suggesting these compounds may have additional targets. Cycloguanil and its most promising analogue, NSC127159, induced similar metabolite profiles compared to established DHFR inhibitors Methotrexate and Pyrimethamine while also blocking downstream signaling, including STAT3 transcriptional activity. These data confirm that Cycloguanil and its analogues are potent inhibitors of human DHFR, and their anti-cancer activity may be worth further investigation.
Citation: Brown, J.I.; Wang, P.; Wong,A.Y.L.; Petrova, B.; Persaud, R.;Soukhtehzari, S.; Lopez McDonald,M.; Hanke, D.; Christensen, J.; Iliev,P.; et al. Cycloguanil and AnaloguesPotently Target DHFR in CancerCells to Elicit Anti-Cancer Activity.Metabolites 2023, 13, 151. https://doi.org/10.3390/metabo13020151Academic Editor: Silvia RaveraReceived: 15 December 2022Revised: 14 January 2023Accepted: 16 January 2023Published: 19 January 2023Copyright: © 2023 by the authors.Licensee MDPI, Basel, Switzerland.This article is an open access articledistributed under the terms andconditions of the Creative CommonsAttribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).metabolitesHOHOHArticleCycloguanil and Analogues Potently Target DHFR in CancerCells to Elicit Anti-Cancer ActivityJennifer I. Brown 1, Peng Wang 2,3, Alan Y. L. Wong 2,4, Boryana Petrova 2,3 , Rosanne Persaud 1,Sepideh Soukhtehzari 1, Melanie Lopez McDonald 5, Danielle Hanke 1, Josephine Christensen 1, Petar Iliev 1,Weiyuan Wang 5 , Daniel K. Everton 1, Karla C. Williams 1, David A. Frank 5 , Naama Kanarek 2,3,6and Brent D. G. Page 1,*1 Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, BC V6T 1Z3, Canada2 Department of Pathology, Boston Children’s Hospital, Boston, MA 02115, USA3 Harvard Medical School, Boston, MA 02115, USA4 Harvard/MIT MD-PhD Program, Harvard Medical School, Boston, MA 02115, USA5 Department of Hematology and Medical Oncology, Emory University, Atlanta, GA 30322, USA6 The Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA* Correspondence: brent.page@ubc.caAbstract: Dihydrofolate reductase (DHFR) is an established anti-cancer drug target whose inhibitiondisrupts folate metabolism and STAT3-dependent gene expression. Cycloguanil was proposed as aDHFR inhibitor in the 1950s and is the active metabolite of clinically approved plasmodium DHFRinhibitor Proguanil. The Cycloguanil scaffold was explored to generate potential cancer therapiesin the 1970s. Herein, current computational and chemical biology techniques were employed tore-investigate the anti-cancer activity of Cycloguanil and related compounds. In silico modelingwas employed to identify promising Cycloguanil analogues from NCI databases, which were cross-referenced with NCI-60 Human Tumor Cell Line Screening data. Using target engagement assays, itwas found that these compounds engage DHFR in cells at sub-nanomolar concentrations; however,growth impairments were not observed until higher concentrations. Folinic acid treatment rescuesthe viability impairments induced by some, but not all, Cycloguanil analogues, suggesting thesecompounds may have additional targets. Cycloguanil and its most promising analogue, NSC127159,induced similar metabolite profiles compared to established DHFR inhibitors Methotrexate andPyrimethamine while also blocking downstream signaling, including STAT3 transcriptional activity.These data confirm that Cycloguanil and its analogues are potent inhibitors of human DHFR, andtheir anti-cancer activity may be worth further investigation.Keywords: dihydrofolate reductase; folate metabolism; target engagement; cancer therapy; cycloguanil;breast cancer; STAT31. IntroductionDisrupting folate metabolism is one of the oldest and most effective strategies to treatcancer. The dihydrofolate reductase (DHFR) inhibitor methotrexate (MTX) was one of thefirst chemotherapies to be discovered and has been consistently used to treat various typesof cancer since the late 1940s [1]. Classic DHFR inhibitors, including MTX, Pemetrexed,and Pralatrexate, mimic dihydrofolate (DHF) and occupy the DHF binding site of DHFR(Figure S1) [2].While DHFR is one of the ‘oldest’ anti-cancer drug targets, more recent research hasilluminated new inhibitors and polypharmacological effects that offer a more thoroughunderstanding of DHFR biology and inhibitors. For example, the use of target engage-ment technologies such as Thermal Proteome Profiling (TPP)) helped confirm thymidylatesynthase as an additional target for MTX [3]. Additionally, similar techniques helpeddemonstrate that the anti-malaria drug Pyrimethamine (Pyr) selectively inhibits humanMetabolites 2023, 13, 151. https://doi.org/10.3390/metabo13020151 https://www.mdpi.com/journal/metabolitesMetabolites 2023, 13, 151 2 of 22DHFR in cancer cell lines, which is linked to its downstream inhibition of STAT3 signalingand underlies its promising anti-cancer activity [4–6]. DHFR and its high-affinity inhibitorshave been routinely used as positive controls when developing target engagement tech-nologies [7–11]. This, in turn, has provided an ideal tool-kit for studying DHFR inhibitorsand has prompted the discovery of new DHFR-focused target engagement assays, such asmeasuring DHFR accumulation following inhibitor treatment as an indicator of target en-gagement [4]. It is within this fruitful landscape that previously identified DHFR inhibitorswere re-investigated for their ability to inhibit human DHFR in biochemical assays andengage DHFR in cancer cell lines.Cycloguanil (Cyc) is the active form of the anti-malaria drug Proguanil which tar-gets plasmodial DHFR to prevent parasitic infection. Activation of Proguanil to Cycrequires oxidation in the liver by cytochrome P450 enzymes [12]. Variability in cytochromep450 expression in different patient populations contributes to the variable prophylacticefficacy of Proguanil [12]. The chemical structures of Cyc and Pyr are highly similar, withboth compounds possessing a diamino-, nitrogen-containing heterocycle appended toa chlorophenyl substituent (Figure 1a). Cyc was originally identified as an inhibitor ofhuman DHFR in the 1970s when it and many Cyc analogues were explored for their DHFRinhibitory activity and their ability to prolong life in rat models of leukemia [13–15]. Despiteshowing promising activity in these early experiments, these compounds arise in relativelyfew citations, suggesting a lack of further development, summarized in Table S1. Thus,using modern in silico methods, archived screening data, and state-of-the-art chemicalbiology techniques, Cyc and its known triazine-containing analogues were herein revis-ited for their inhibitory activity against human DHFR and as potential cancer therapies.While similar potency was observed in biochemical experiments, potent target engagementwas observed in cell-based assays suggesting that these triazine compounds may still bepromising DHFR inhibitors with interesting biological and anti-cancer properties.Metabolites 2023, 13, x FOR PEER REVIEW 3 of 24 Figure 1. Molecular docking with Cyc and Cyc analogues to human DHFR. (a) Chemical structures of DHFR inhibitors methotrexate (MTX), Pyrimethamine (Pyr), Cycloguanil (Cyc), and Baker’s an‐tifolate, as well as analogous top compounds from the NCI‐DTP database referred to by their re‐spective NSC numbers. (b) Overlay co‐crystalized MTX (green) and docked MTX (magenta) into crystalized DHFR (PDB: 1U72) using GLIDE (Maestro, Schrödinger). NADPH was removed from the active site prior to the docking simulation. (c) Overlaid docking images of Pyr, 3062, Cyc, 3077, 123032, 127159, 127153, 128184, and 139105 in the folate‐binding pocket of DHFR. The diamino ni‐trogen‐containing heterocycles of these compounds mimic the interactions of the diaminopteridine moiety of MTX. (d) The top scoring pose of Cyc (yellow) and (e) 127159 (orange) docked into the folate‐binding pocket of DHFR. Figure 1. Cont.Metabolites 2023, 13, 151 3 of 22Metabolites 2023, 13, x FOR PEER REVIEW 3 of 24 Figure 1. Molecular docking with Cyc and Cyc analogues to human DHFR. (a) Chemical structures of DHFR inhibitors methotrexate (MTX), Pyrimethamine (Pyr), Cycloguanil (Cyc), and Baker’s an‐tifolate, as well as analogous top compounds from the NCI‐DTP database referred to by their re‐spective NSC numbers. (b) Overlay co‐crystalized MTX (green) and docked MTX (magenta) into crystalized DHFR (PDB: 1U72) using GLIDE (Maestro, Schrödinger). NADPH was removed from the active site prior to the docking simulation. (c) Overlaid docking images of Pyr, 3062, Cyc, 3077, 123032, 127159, 127153, 128184, and 139105 in the folate‐binding pocket of DHFR. The diamino ni‐trogen‐containing heterocycles of these compounds mimic the interactions of the diaminopteridine moiety of MTX. (d) The top scoring pose of Cyc (yellow) and (e) 127159 (orange) docked into the folate‐binding pocket of DHFR. Figure 1. Molecular docking with Cyc and Cyc analogues to human DHFR. (a) Chemical structuresof DHFR inhibitors methotrexate (MTX), Pyrimethamine (Pyr), Cycloguanil (Cyc), and Baker’sa tif late, as well as analogou top compounds from the NCI-DTP database referred to by theirr spective NSC numbers. (b) Overlay co-crystalized MTX (green) and docked MTX (magenta) intocrystalized DHFR (PDB: 1U72) using GLIDE (Maestro, Schrödinger). NADPH was removed fromthe active site prior to the docking simulation. (c) Overlaid docking images of Pyr, 3062, Cyc, 3077,123032, 127159, 127153, 128184, and 139105 in the folate-binding pocket of DHFR. The diaminonitrogen-containing heterocycles of these compounds mimic the interactions of the diaminopteridinemoiety of MTX. (d) The top scoring pose of Cyc (yellow) and (e) 127159 (orange) docked into thefolate-binding pocket of DHFR.2. Materials and Methods2.1. Cell CultureHuman epithelial breast adenocarcinoma cell lines MDA-MB-468 (HTB-132), MCF-7 (HTB-22), and MDA-MB-231 (HTB-26) were obtained from American Type CultureCollection (ATCC). Cells were routinely grown in Dulbecco’s Modified Eagle’s Medium(DMEM, Corning) supplemented with 4.5 g/L glucose, L-glutamine, sodium pyruvate, and10% fetal bovine serum (FBS, Fisherbrand) at 37 ◦C with 5% CO2 in a humidified incubator.2.2. CompoundsAll compounds were prepared in 10 mM DMSO. Pyrimethamine (D897, AK Scientific,Union City, CA, USA), methotrexate (J10045, AK Scientific, Union City, CA, USA), andcycloguanil (7651AA, AK Scientific, Union City, CA, USA) were commercially purchased.Most cycloguanil analogues were received from the National Cancer Institute (NCI) De-velopmental Therapeutics program [16]: 3062 (etoprine), 123032, 127159, 127153, 128184,Metabolites 2023, 13, 151 4 of 22and 139105 (triazinate). Analogue 3077 was synthesized according to previously publishedprotocols, as described in supplementary materials. Compounds were locally indexed andvisualized using Instant JChem (22.6.0) (ChemAxon).2.3. DockingCompounds were docked into the folate binding pocket of the DHFR crystal structurePDB 1U72 using GLIDE (Maestro, Schrödinger) [17]. Cyc analogues were downloadedfrom the National Cancer Institutes (NCI)—Developmental Therapeutics Program chemicalcompound dataset (2016 release) [16]. Triazine-containing structures were identified usingthe structure search function (Instant JChem) and were extracted for docking studies. Struc-tures were prepared for docking using LigPrep. The DHFR co-crystal structure containedboth nicotinamide adenine dinucleotide phosphate (NAPDH, which was removed for dock-ing) and MTX. The protein crystal was prepared for docking using standard workflows.The co-crystallized MTX was used to set the center of a 10 × 10 × 10-angstrom dockinggrid. As a positive control, MTX was also subjected to docking experiments and comparedto the co-crystalized ligand through the determination of the RMSD using the DockRMSDtool (v1.1) [18].2.4. Expression and Purification of Human DHFRExpression and purification of human 6 × His-DHFR was performed by the Pro-tein Science Facility of Karolinska Institutet (Department of Medical Biochemistry andBiophysics, Biomedicum, Stockholm, Sweden). Briefly, the gene for human DHFR wasproduced by GeneArt (Thermofisher) with an N-terminal 6×His-tag and cleavable tobaccoetch virus (TEV) site and was cloned into the pNIC-Bsa4 expression plasmid. The constructwas transformed into BL21 (DE3) T1R pRARE2, and expression was induced at OD 3 with0.5 mM isopropyl ß-D-1-thiogalactopyranoside (IPTG) and grown 16 h at 18 ◦C. Cells wereharvested by centrifugation at 4500× g and suspended in lysis buffer (100 mM HEPES,500 mM NaCl, 10 mM imidazole, 10% glycerol, 0.5 mM tris(2-carboxyethyl)phosphine(TCEP), pH 8.0) supplemented with EDTA-free protease inhibitor cocktail (PIC, Roche) andbenzonase nuclease cell suspension (50 µL/mL) at 1.5 mL buffer per gram wet cell pellet.Resuspended cells were frozen at −80 ◦C to aid in lysis. The cell suspension was thawedin a room temperature water bath and sonicated on ice in 4-s intervals at 80% amplitudefor 4 min. Cellular debris and insoluble components were separated by centrifugation at49,000× g for 20 min. The soluble fraction was removed and clarified by filtration (0.45 µm).Clarified lysate was loaded onto a 5 mL HisTrap HP (GE Healthcare) that waspre-equilibrated with wash buffer 1 (20 mM HEPES, 500 mM NaCl, 10 mM imidazole,10% glycerol, 0.5 mM TCEP, pH 7.5). Subsequent washes with wash buffer 1 and washbuffer 2 (wash buffer 1 with 50 mM imidazole) were performed. Bound protein was eluted(20 mM HEPES, 500 mM NaCl, 500 mM imidazole, 10% glycerol, 0.5 mM TCEP, pH 7.5)and subsequently loaded onto a HiLoad 16/60 Superdex 75 (GE Healthcare) size exclu-sion column pre-equilibrated with gel filtration buffer (20 mM HEPES, 300 mM NaCl,10% glycerol, 0.5 mM TCEP, pH 7.5) to remove imidazole. The resulting purified proteinwas concentrated using a Vivaspin concentration filter with a 10 kDa molecular weightcut-off. The concentration of purified protein was determined by measuring the A280 usinga Nanodrop and using the extinction coefficient 26,930 M−1 cm−1. The final fraction wasdetermined to be >90% pure, as monitored by SDS-PAGE.2.5. DHFR Enzymatic Inhibition AssayReactions containing 200 nM purified human DHFR, 137.5 µM dihyrdrofolate (DHF)substrate, and varying concentrations of inhibitor (0.091–200 µM) were prepared in DHFRbuffer (50 mM Tris, 50 mM NaCl, pH 7.4). Working stocks of each inhibitor were created sothat the final concentration of DMSO in each reaction was 2% in a final reaction volumeof 100 µL. A DMSO control reaction containing 200 nM DHFR, 137.5 µM DHF, 2% DMSO,125 µM NADPH, and no inhibitor was performed. A no-DHFR control reaction containingMetabolites 2023, 13, 151 5 of 222% DMSO, 137.5 µM DHF, and 125 µM NADPH was also performed. Reactions wereprepared on ice in 384-well plates. To initiate the reaction, the NADPH cofactor (125 µM)was added. Consumption of NADPH by measuring absorbance at 340 nm was used tomonitor the progress of the reaction. Readings were taken every 5 min for 1 h at 37 ◦Cusing a Synergy MX microplate reader (BioTek).Percent inhibition relative to the no-inhibitor control was determined using Equation (1).% Inhibition =A340 Inhibitor− A340DMSO ControlA340No DHFR− A340DMSO Control × 100 (1)Percent inhibition data were then fit to the four-parameter logistic model (Equation (2))in GraphPad Prism 9.4.1 to determine half-maximal inhibitory concentrations (IC50):y =Bottom + (Top− Bottom)(1 + IC50x)Hill slope (2)where y represents the percent inhibition, x represents the concentration of inhibitor (µM),the bottom and top represent the bottom and top plateaus, and the Hill slope represents theslope factor. Each experiment contained duplicates of each sample, and each experimentwas performed 2 times (n = 2). An ordinary one-way ANOVA was used to test for statisticalsignificance between treatments.2.6. NCI-60 Sensitivity Correlation AnalysesGrowth inhibition of 50% (GI50) data were accessed from the NCI-60 Human Tu-mor Cell Lines Screen database (https://dtp.cancer.gov/public_compare/ (accessed on28 October 2022)) [19]. Datasets were pruned and points removed where GI50 values wereequal to the maximum tested concentration. To analyze sensitivity profiles for compounds,GI50 values were compared using a correlation matrix in GraphPadPrism 9.4.1 to give Pear-son Correlation Coefficients (r-values). Statistical significance is reported using a two-tailedstatistical analysis to generate p values. Similarly, individual compound GI50 values werecompared to MTX across different cancer cell types by performing correlation analysisto generate r-values using two-tailed statistical analysis to generate p-values. A plot ofbreast cancer GI50 values was prepared in which GI50 values that were equal to the highestconcentration tested were omitted from the graph. These instances are indicated below thelabels on the x-axis.2.7. Viability AssaysThe incorporation and metabolism of resazurin to resorufin was used to monitor cellviability [20]. MDA-MB-468, MCF7, and MDA-MB-231 cells were grown in 96-well plateswith a total of 5000 cells per well in a total volume of 180 µL for 24 h, as described above.After 24 h of growth, cells were treated with increasing concentrations of compounds(0.0457–100 µM) for 72 h. A vehicle control was also performed. All treatments had a finalconcentration of 1% DMSO. The volume of treatment added to each well was 20 µL. Forfolinic acid rescue experiments, 5000 cells were treated with 10 µM compound with orwithout 300 µg/mL folinic acid (Supelco). After 72 h of treatment, resazurin was addedto a final concentration of 44 µM, and cells were incubated for an additional 4 h at 37 ◦C.The fluorescence of resorufin was monitored on a Synergy MX microplate reader (BioTek)using an excitation wavelength of 540 nm and an emission wavelength of 600 nm. Percentviability relative to the DMSO control was determined. Each treatment was performed intriplicate, and each individual experiment was repeated three times (n = 3).2.8. Wound Healing AssayMDA-MB-231 cells were seeded in a 96-well Essen Image Lock plate (Essen Bioscience)at a density of 60,000 cells/well and cultured in DMEM medium supplemented with10% Fetal Bovine Serum until 90% confluence at 37 ◦C and 5% CO2.Metabolites 2023, 13, 151 6 of 22Confluent monolayers were scratched by using a 96-pin WoundMaker™ (BioScienceInc, Ann Arbor, MI, USA). Cells were then washed with DMEM three times to removedetached cells and debris. Compounds were diluted in DMEM medium and were addedto cells at a final concentration of 10 µM for 24 h along with blank medium including1% DMSO. Wound images were acquired by the IncuCyte™ software system (Essen Bio-Sciences) every 3 h. Data were processed and analyzed using IncuCyte™ Scratch WoundAnalysis Software Module. Data are presented as the Relative Wound Density, whichrepresents the ratio of the cell density at the wound area relative to the cell density outsideof the wound area over time. An ordinary one-way ANOVA with a Dunnett multiplecomparison test was performed to detect significant differences between each treatmentand the DMSO control. Each experimental condition was evaluated in quadruplicate inthree independent assays (n = 3).2.9. Lysate Cellular Thermal Shift Assay (CETSA)Trypsinized MDA-MB-468 cells were harvested by centrifugation at 200× g for 5 minand washed with PBS supplemented with EDTA-free PIC (Roche) and flash frozen forstorage at −80 ◦C. Cells were lysed by resuspension in 60 µL PBS/PIC per 1 × 106 cells.Cells were lysed by three freeze-thaw cycles, where cells were frozen in an ethanol/dryice bath for 3 min, immediately followed by incubation in a 37 ◦C water bath for 3 min.The insoluble fraction was removed by centrifugation at 20,000× g for 20 min at 4 ◦C. Thesupernatant containing the soluble lysate was removed and saved for subsequent steps.To determine the melting temperature of DHFR, reactions containing 55 µg MDA-MB-468 lysate and 1% DMSO in 28 µL total DHFR buffer were incubated in a gradientfrom 37–81 ◦C for 3 min in PCR tubes in a DNA Engine Dyad Peltier Thermal Cycler(BioRad). After incubation, each reaction was transferred to a 1.5 mL tube and centrifugedat 20,000× g for 20 min at 4 ◦C to remove the insoluble proteins. After centrifugation,18 µL of supernatant was carefully removed from each reaction, without disturbing anypelleted aggregates, and added to 4.5 µL of 5× SDS-PAGE loading buffer. 11 µL of eachreaction was loaded onto a gel in duplicate, and proteins were detected by Western blot (asdescribed below). Resulting band densities were fit to the Boltzmann equation to determinethe melting temperature (Tm):y = Bottom +(Top− Bottom)1 + e(Tm−xSlope )(3)To rescue the thermal degradation of DHFR by inhibitors, samples containing 10 µMinhibitor, 55 µg lysate, and 1% DMSO in a total volume of 28 µL in DHFR buffer wereprepared in PCR tubes and incubated at room temperature for 20 min. Two DMSO-onlycontrols were also prepared. Reactions containing inhibitors were then incubated at 45 ◦Cfor 3 min. One DMSO-only control was also heated at 45 ◦C for 3 min, and the other controlwas heated at 37 ◦C for 3 min. The soluble protein fraction was separated from the insolubleproteins by centrifugation, and proteins were separated by SDS-PAGE, as described above,and analyzed via Western blot, as described below. Each experiment was repeated 3 times.2.10. DHFR Accumulation AssayTrypsinized MDA-MB-468 cells were seeded into 6-well plates at a density of 300,000 cellsper 2 mL of media and allowed to adhere for 24 h. Cells were then treated with the indicatedinhibitor at concentrations from 0.001 µM to 10 µM or from 0.012 nM to 1 nM. The finalconcentration of DMSO in each well was 1%. A DMSO-only control was also performed oneach individual plate. Cells were then trypsinized, harvested by centrifugation at 200× gfor 5 min at 4 ◦C, and washed once with PBS/PIC. Cell pellets were flash frozen usingan ethanol/dry ice bath and stored at −80 ◦C prior to lysis. Each cell pellet was lysedas described above using 50 µL PBS/PIC per cell pellet. Samples were then analyzed byWestern blot, as described below, using 30 µg lysate per lane. Band intensities of DHFRwere normalized to the loading control SOD1 via densitometry using ImageJ (Fiji), and eachMetabolites 2023, 13, 151 7 of 22DHFR band was normalized to the DMSO control. Fold-change in DHFR band intensitywas plotted against inhibitor concentration (µM). Each experiment was performed twoseparate times as individual biological replicates (n = 2).2.11. Western BlotProteins were electrophoretically separated on a 10% gel, and proteins were transferredto a methanol-activated PVDF membrane using the Trans-Blot Turbo transfer system (Bio-Rad) for 7 min at 1.3 A and 25 V in Trans-Blot Turbo transfer buffer (Bio-Rad). Membraneswere blocked with 5% skim milk w/v in TBS-T (20 mM Tris, 150 mM NaCl, 0.05% Tween-20)for 1 h at room temperature. Primary antibodies were added for 1 h at room temperaturein TBS-T using the following concentrations: anti-DHFR (sc-377091, Santa Cruz; 1:200);anti-SOD1 (sc-17767, Santa Cruz; 1:3000); anti-thymidine phosphorylase (TP) (sc-47702,Santa Cruz; 1:100). The horseradish peroxidase (HRP)-linked anti-mouse IgG secondaryantibody (NA931, Cytiva; 1:3000) was added for 1 h at room temperature in 5% skim milkw/v in TBS-T. Signal was detected by adding Immobilon Forte Western HRP Substrate(Millipore), and chemiluminescence was captured on a Sapphire Biomolecular Imager(Azure Biosystems). Band densities were determined using ImageJ (Fiji) [21]. The bandintensity of DHFR was normalized to the thermostable loading control SOD1 [22].2.12. Liquid Chromatography/Mass Spectrometry (LC/MS)-Based Metabolite Profiling2.12.1. Sample Preparation for LC/MS Analysis of Polar Metabolites fromMDA-MB-231 CellesFor characterization by mass spectrometry, MDA-MB-231 cells were seeded at a densityof 3 × 105 cells per well in 6-well plates. After 24 h of growth, cells were treated with either10 µM inhibitor (MTX, Pyr, Cyc, or 127159) or 10 µM inhibitor plus 300 µg/mL folinic acidfor 24 h. DMSO only and DMSO + folinic acid controls were also performed. Per condition,biological quadruplicates of approximately one million cells were harvested, washed brieflywith 1 mL of 0.9% NaCl (prepared in LC/MS-grade water Fisher Scientific W6500), andextracted in 500 µL prechilled extraction buffer (80% LC/MS-grade methanol, 20% 125 mMammonium acetate, 12.5 mM sodium ascorbate prepared in LC/MS-grade water andsupplemented with aminopterin (catalog no.: 16.330; Schircks Laboratories) and isotopicallylabeled internal standards (17 amino acids and reduced glutathione [Cambridge IsotopeLaboratories; MSK- A2-1.2 and CNLM-6245-10])) using a cell scraper. After centrifugationfor 10 min, 4 ◦C, at maximum speed on a benchtop centrifuge (Eppendorf), the clearedsupernatant was transferred to a new tube and dried using a nitrogen dryer (Reacti-Vap™ Evaporator, Thermo Fisher Scientific, TS-18826) while on ice. Once the dryingprocess was completed, samples were reconstituted in 50 µL QReSS water (CambridgeIsotope Laboratories, MSK-QRESS-KIT) by brief sonication in a 4 ◦C water bath. Extractedmetabolites were spun for 3 min, 4 ◦C, at maximum speed on a bench-top centrifuge, andcleared supernatant was transferred to LC/MS microvials (National Scientific, C5000-45B).Three microliters of each sample were pooled and serially diluted 3- and 10-fold to beused as quality controls throughout the run of each batch. Unlabeled QReSS metabolites(Cambridge Isotope Laboratories, MSK-QReSS-US-KIT) and unlabeled amino acid mixstandard (Cambridge Isotope Laboratories, MSK-A2-US-1.2) were also included in the runto ensure high-quality metabolomics results.2.12.2. Chromatographic Conditions for LC/MSOne microliter (equivalent to 2 × 104 cells) of the reconstituted sample was injectedinto a ZIC-pHILIC 150× 2.1 mm (5µm particle size) column (EMD Millipore) operatedon a Vanquish™ Flex UHPLC Systems (Thermo Fisher Scientific, San Jose, CA, USA).Chromatographic separation was achieved using the following conditions: buffer A wasacetonitrile; buffer B was 20 mM ammonium carbonate, 0.1% ammonium hydroxide. Gra-dient conditions were: linear gradient from 20% to 80% B; 20–20.5 min: from 80% to 20% B;Metabolites 2023, 13, 151 8 of 2220.5–28 min: hold at 20% B. The column oven and autosampler tray were held at 25 ◦C and4 ◦C, respectively.2.12.3. Orbitrap Conditions for Targeted Analysis of Polar MetabolitesMass spectrometry data acquisition was performed using a QExactive benchtop orbi-trap mass spectrometer equipped with an Ion Max source and a HESI II probe (ThermoFisher Scientific, San Jose, CA, USA) and was performed in positive and negative ionizationmode in a range of m/z = 70–1000, with the resolution set at 70,000, the AGC target at1 × 106, and the maximum injection time (Max IT) at 20 msec. For nucleotide tSIM scans,the resolution was set at 70,000, the AGC target was 1 × 105, and the max IT was 100 msec.2.12.4. Data Analysis and QuantitationManual curation and integration of chromatographic peaks were performed withTraceFinder 4.1 (Thermo Fisher Scientific, Waltham, MA, USA) using a 5 ppm mass toler-ance and referencing an in-house library of chemical standards. Data from TraceFinderwere further consolidated and normalized with an in-house R script: (https://github.com/FrozenGas/KanarekLabTraceFinderRScripts/blob/main/MS_data_script_v2.4_20221018.R (accessed on 22 November 2022)). Briefly, this script performs normalization and qual-ity control steps: (1) extracts and combines the peak areas from TraceFinder output .csvs;(2) calculates and normalizes to an averaged factor from all mean-centered chromatographicpeak areas of isotopically labeled amino acids internal standards within each sample;(3) filters out low-quality metabolites based on user inputted cut-offs calculated frompool reinjections and pool dilutions; (4) calculates and normalizes for biological materialamounts based on the total integrated peak area values of high-confidence metabolites. Inthis study, the linear correlation between the dilution factor and the peak area cut-offs isset to RSQ > 0.95 and the coefficient of variation (CV) < 30%. Finally, data were Log trans-formed and Pareto scaled within the MetaboAnalyst-based statistical analysis platform [23]to generate principal component analysis (PCA), partial least squares-discriminant analysis(PLSDA), and heatmaps. The relative abundance of each analyte per treatment was plottedand comparisons between each treatment alone and the DMSO control and each treatment+ FA and the DMSO + FA control were performed using an Ordinary one-way ANOVAwith Šídák’s correction for multiple comparisons.2.13. STAT3 Luciferase Reporter AssayThe STAT3-dependent luciferase reporter assay was performed as previously re-ported [24]. One day prior to the assay, the U3A STAT3 luciferase reporter cell line [24]was seeded in a 96-well plate at 8000 cells per well. Cells were then incubated with com-pounds at the indicated concentration, and each well was treated with either media controlor stimulated with 10 ng/mL oncostatin M (OSM) and incubated for six hours at 37 ◦C.Luciferase activity was quantified using the Bright-Glo Luciferase Assay system (Promega)and a Luminoskan Ascent Luminometer (Labsystems). Collected luminescence readingswere normalized to DMSO-treated controls. Stimulation with (+OSM) gave luminescencevalues around 2.5 times that of the unstimulated control (−OSM). Quadruplicates wereaveraged and plotted with error bars representing standard deviation. Each condition wasperformed in quadruplicate on two separate occasions (n = 2) with representative datashown. Statistical significance was determined using Ordinary one-way ANOVA with aDunnett multiple comparison test.3. Results3.1. Cyclogunail-Like Triazine Compounds Potently Inhibiti Human DHFR In VitroGiven the high structural similarity between the antimalarials Cyc and Pyr (Figure 1a)and the recent evidence highlighting Pyr’s anti-cancer properties stem from functionalinhibition of human DHFR [4], Cyc and its triazine analogues were analyzed to determineif they may interact with human DHFR using molecular docking. Cyc analogues fromMetabolites 2023, 13, 151 9 of 22the NCI—Developmental Therapeutics Program were docked to human DHFR (PDB:1U72) using GLIDE (Maestro, Schrödinger) with Xtra precision [16,17,25]. MTX was alsodocked into the active site as a positive control, which fit nearly identically compared tothe co-crystalized MTX (RMSD: 0.964) (Figure 1b).Docked Cyc analogues (57) were ranked according to their Xtra precision GLIDE (XPG)scores, and 40 compounds were acquired from the NCI. Compounds were selected based ontheir XPG score, their similarity to other compounds in the data set (prioritizing diversity),and based on their availability from the NCI. Notably, within these top compounds wereseveral analogous pairs of compounds that possessed or lacked a chlorine atom on thephenyl substituent of the Cyc pharmacophore (i.e., 3,4-dichlorophenyl in 3077 versus4-chlorophenyl in Cyc). Four compounds had an additional 4-n-butylphenyl substituentappended to the 4-position of the aromatic ring of the Cyc backbone, two of which alsoincorporated a sulfonylfluoride group that imparts the potential for covalently modifyingDHFR (123032 and 127159). These compounds were initially reported as DHFR inhibitorsback in the early 1970s [13–15]. Chlorinated analogues of Cyc (3077) and Pyr (3062), as wellas Baker’s antifolate (139105), were included in this workflow. Baker’s antifolate has beenwell-characterized as a DHFR inhibitor and was previously a subject of Phase I clinicaltrials [26–28]. The structures of all compounds are shown in Figure 1a.All compounds docked to the DHFR crystal structure with reasonably strong XPGscores (Table 1). Docking analyses predicted the phenyltriazine moiety of Cyc analogues(Figure 1c) and Cyc itself (Figure 1d) overlaid with the pteridine ring of MTX and thepyrimidine ring of Pyr within the DHFR active site. While hydrogen bonding with Ile7,Val115 and Glu30 anchor the nitrogen-containing heterocycles for MTX and Pyr, the triazinering appears to rely more heavily on interactions with Glu30 making both ionic and hydro-gen bonds with this residue. Cyc and Cyc analogues also made pi-stacking interactionswith Phe34, and some made additional pi-stacking interactions with Phe31 (i.e., 128184and 127153). Baker’s antifolate additionally made a hydrogen bond with Asn64. Noneof the Cyc compounds could mimic the ionic interactions MTX makes with Arg70 at theopening of the active site (Figure S1). Figure 1e shows the top docked pose of 127159 as arepresentative example highlighting the similarity in docked orientation relative to the Cycbackbone in Figure 1d. A notable difference between Cyc and 127159 docking orientationsis that the triazine ring is flipped in how it aligns in the active site, which is most obviouswhen comparing the location of the dimethyl groups in Figure 1d,e. Ligand interactiondiagrams for all docked compounds are included in Figure S1.Table 1. Comparison of GLIDE XPG scores and biochemical IC50 values in the DHFR activityassay. Errors represent the standard deviation between two independent experiments (n = 2), eachperformed in duplicate.Compound XPG Score (kcal/mol) IC50 (µM)MTX −12.630 0.117 ± 0.006 aPyr −8.217 16.9 ± 7.93062 −8.774 8.6 ± 2.7Cyc −7.718 10.8 ± 3.53077 −8.653 1.26 ± 0.66123032 −10.067 1.17 ± 0.46127159 −10.257 0.75 ± 0.32127153 −9.338 0.93 ± 0.24128184 −10.193 0.72 ± 0.24139105 −10.165 2.11 ± 0.53a average of three replicates reported for MTX in Heppler et al., 2022 [4].Encouraged by the docking scores and predicted interactions, these compounds wereassessed for their ability to inhibit purified human DHFR enzymatic activity. DHFRactivity was determined by monitoring reduced NADPH levels (absorbance at 340 nm) inthe presence of dihydrofolic acid (DHF) and potential inhibitors. Percent inhibition wasMetabolites 2023, 13, 151 10 of 22determined relative to the DMSO (no inhibition) and “no DHFR” (no activity) controls,and normalized data were fit to a four-parameter non-linear regression to determine IC50values reported in Table 1. Inhibition curves are presented in Figure S2, and the linearrange of the assay is presented in Figure S3.In general, compounds possessing a 3-chloro moiety had lower IC50 values thananalogous compounds, which lacked this group. This modification likely enhances thepi-stacking interaction with Phe34 seen in the docking simulations. The larger compounds127159, 127153, and 128184 had IC50 values that were below 1 µM and approaching the IC50of MTX (IC50 = 0.177 ± 0.006 µM). This correlated nicely with the docking scores, whichsuggested that these compounds fit well into the DHFR active site.3.2. Cyclogunail-Like Triazene Compounds Elicit Anti-Cancer Activity in Breast Cancer CellsAll of the aforementioned compounds, except for 127153, were tested in the NCI-60 Human Tumor Cell Lines Screen to determine if they may have potential anti-canceractivity [19]. This publicly available data reports the concentration at which compoundsinduce 50% inhibition of cell growth (GI50) in an array of (male and female) cancer cell lines.From the NCI-60 screens, all compounds displayed anti-cancer activity and wereherein subjected to additional analyses to predict functional similarities between the com-pounds. To determine correlations, GI50 values for each compound against each cell linewere compared, and Pearson correlation coefficients (r-values) were reported in Figure 2a.Data points where GI50 values were the same as the maximum concentrations tested wereexcluded from this analysis. While all compounds demonstrated a degree of positivecorrelation with the others, particularly strong correlations were observed within threedifferent groupings: Firstly, MTX activity most strongly correlated with Pyr, the chlorinatedPyr analogue 3062 and Baker’s antifolate (139105), with r-values ranging from 0.67 to 0.74.Secondly, Cyc and its chlorinated analogue, 3077, unsurprisingly demonstrated a highdegree of correlation (r = 0.76); however, these compounds did not correlate as stronglywith the other analogues. In particular, Cyc demonstrated a relatively poor correlation withMTX (r = 0.40), suggesting that there may be differences in their functionality in these celllines. Finally, the larger Cyc analogues (123032, 127159, 128184), as well as Baker’s antifo-late (139105), had a high degree of correlation across the NCI-60 cell lines with r-valuesranging between 0.73 and 0.91. The highest correlations were seen between chlorinatedand non-chlorinated analogues (123032 and 127159, for example). All correlations werestatistically significant, with p-values reported in Table S2. These different groupings willbe referred to herein as “MTX-like,” “Cyc-like,” or “Large Cyc Analogues,” where Baker’santifolate spans both the “Large Cyc Analogues” and “MTX-like” groups.To determine if these correlations were more pronounced in specific cancer types,Pearson correlation coefficients (r) were calculated within each cancer type, comparingcompound GI50 values to MTX’s. Due to limited data availability, an r-value could not bedetermined for 3062 in leukemia. After plotting r-values as a heat map (Figure 2b), thestrongest correlations are observed in melanoma and breast cancer cells, most of whichwere statistically significant (Table S3). Further, GI50 values of each compound wereplotted against breast cancer cell lines to investigate trends related to specific cell lines andpotentially breast cancer subtypes (Figure 2c). These compounds typically displayed thestrongest activity against MDA-MB-468 (triple negative) and MCF-7 (hormone receptor-positive, HER2 negative) and weakest activity against HS578T (triple negative), suggestingthat their activity may not be linked to specific breast cancer subtypes. The Large CycAnalogues appear to be more potent than other compounds in MDA-MB-231 cells. Basedon these findings, MCF-7, MDA-MB-468, and MDA-MB-231 cells were used to investigatethe effects of these compounds further.Metabolites 2023, 13, 151 11 of 22Metabolites 202 , 3, x FOR PEER REVIEW 12 of 24 Figure 2. Cyc analogues inhibit cell growth in cancer cells. (a) GI50 values obtained from the NCI‐60 Human Tumor Cell Lines Screen were compared against each compound to reveal statistically sig‐nificant Pearson Coefficient correlations. (b) GI50 values of each compound compared to MTX sep‐arated by cancer type reveal positive, statistically significant correlations of Pearson Coefficients in melanoma and breast cancer cells. There were not enough data to compare 3062 to MTX in leukemia (white X box). Grey boxes indicate a negative correlation outside the heatmap range. The statistical significance of both plots in (a,b) was determined using a two‐tailed statistical analysis. (c) Plots of the GI50 values for each compound against each breast cancer cell line. For instances where GI50 values were equal to the maximum concentration tested, data were omitted, as indicated by the symbols under the x‐axis. (ns = not significant; * = p ≤ 0.05; ** = p ≤ 0.01; *** = p ≤ 0.001; **** = p ≤ 0.0001). 3.3. Cycloguanil Analogues Inhibit Breast Cancer Cell Viability Cell viability experiments in MDA‐MB468, MDA‐MB‐231, and MCF‐7 (female) breast cancer cell lines gave variable responses with the Cyc analogues despite the structural similarities and biochemical activity towards DHFR (Figure 3). In general, there are two distinct phenotypic responses detected in these cell lines. First, several compounds appear to induce a growth arrest, where viability remains around 50% relative to vehicle controls at high concentrations. These include Cyc‐like and MTX‐like compounds, including Baker’s antifolate. Second, the other Large Cyc Analogues killed cells at high concentra‐tions and had minimal impact on viability at lower concentrations. Compounds 123023 and 127159 show little effect at low concentrations and cytotoxicity at higher concentra‐tions in a dose‐dependent manner. However, 127153 and 128184 induce growth arrest at low concentrations and induce cell death at higher concentrations. Thus, it appears there are two common phenotypic responses in these cell lines (growth arrest and inducing cell death), with Large Cyc Analogues behaving differently from the other compounds tested. Figure 2. Cyc analogues inhibit cell growth in cancer cells. (a) GI50 values obtained from theNCI-60 Human Tumor Cell Lines Screen were compared against each compound to reveal statis-tically significant Pearson Coeffici nt correl tions. (b) GI50 values of each c mp und comparedto MTX separated by cancer type reveal positive, statistically significant correlations of PearsonCoefficients in melanoma and breast cancer cells. There were not enough data to compare 3062 toMTX in leukemia (white X box). Grey boxes indicate a negative correlation outside the heatmaprange. The statistical significance of both plots in (a,b) was determined using a two-tailed statisticalanalysis. (c) Plots of the GI50 value for e ch compound against each breast cancer cell line. Forinstances where GI50 values were equal to the maximum concentration tested, data were omitted,as indicated by the symbols under the x-axis. (ns = not significant; * = p ≤ 0.05; ** = p ≤ 0.01;*** = p ≤ 0.001; **** = p ≤ 0.0001).3.3. Cycloguanil An logues Inhibit Breast Cancer Cell ViabilityCell viability experiments in MDA-MB468, MDA-MB-231, and MCF-7 (female) breastcancer cell lines gave variable responses with the Cyc analogues despite the structuralsimilarities and biochemical activity towards DHFR (Figure 3). In general, there are twodistinct phenotypic responses detected in these cell lines. First, several compounds appearto induce a growth arrest, where viability remains around 50% relative to vehicle controls athigh concentrations. These include Cyc-like and MTX-like compounds, including Baker’santifolate. Second, the other Large Cyc Analogues killed cells at high concentrationsand had minimal impact on viability at lower concentrations. Compounds 123023 and127159 show little effect at low concentrations and cytotoxicity at higher concentrationsin a dose-dependent manner. However, 127153 and 128184 induce growth arrest at lowconcentrations and induce cell death at higher concentrations. Thus, it appears there aretwo common phenotypic responses in these cell lines (growth arrest and inducing celldeath), with Large Cyc Analogues behaving differently from the other compounds tested.Metabolites 2023, 13, 151 12 of 22Metabolites 2023, 13, x FOR PEER REVIEW 13 of 24 Figure 3. Biological activity of Cyc analogues in breast cancer cells. Cell viability of MDA‐MB‐468 (black circle), MDA‐MB‐231 (purple square), and MCF‐7 (blue triangle) breast cancer cells when treated with methotrexate and cycloguanil analogues. Cells were treated with 0–100 μM of each inhibitor for 72 h. Cell viability was measured by adding 44 μM resazurin and quantifying the amount brought into and metabolized by live cells by monitoring the fluorescence of Ex540/Em600. Percent viability relative to the DMSO control was calculated and plotted against the inhibitor (μM, Log10 scale). Models of the data were determined by fitting Equation (2). 3.4. Folinic Acid Rescues DHFR Inhibitory Activity In the folate metabolism cycle, DHFR reduces folic acid to dihyrdofolic acid and sub‐sequently dihydrofolic acid to tetrahydrofolic acid, which is then further metabolized to produce metabolites needed for nucleic acid biosynthesis. Folinic acid (FA) is another di‐etary source for these nucleic acid building blocks, which does not require DHFR‐medi‐ated metabolism [29]. We previously observed that treatment with FA rescues DHFR‐spe‐cific inhibitory mechanisms that impact downstream folate metabolism and cellular growth arrest and/or cell death[4]. To assess DHFR‐dependence and FA rescue, cell via‐bility assays were performed again in MDA‐MB‐468, MDA‐MB‐231, and MCF‐7 cells in the presence of 10 μM of each compound ± 300 μg/mL FA for 72 h. Consistently, in all three cell lines tested, FA rescued the effects of Pyr on cell viabil‐ity. Only Pyr and Baker’s antifolate demonstrated statistically significant rescue in MDA‐MB‐468 cells, but viability impairment by Baker’s antifolate was not rescued in the other Figure 3. Biological activity of Cyc analogues in breast cancer cells. Cell viability of MDA-MB-468(black circle), MDA-MB-231 (purple square), and MCF-7 (blue triangle) breast cancer cells whentreated with met otrexate and cycloguanil analogues. Cells were treated with 0–100 µM of eachinhibitor for 72 h. Cell viability was measured by adding 44 µM resazurin and quantifying theamount brought into and metabolized by live cells by monitoring the fluorescence of Ex540/Em600.Percent viability relative to the DMSO control was calculated and plotted against the inhibitor (µM,Log10 scale). Models of the data were determined by fitting Equation (2).3.4. Folinic Acid Rescues DHFR Inhibitory ActivityIn the folate metabolism cycle, DHFR reduces folic acid to dihyrdofolic acid andsubsequently dihydrofolic acid to tetrahydrofolic acid, which is then further metabolizedto produce metabolites needed for nucleic acid biosynthesis. Folinic acid (FA) is another di-etary source for these nucleic acid building blocks, which does not require DHFR-mediatedmetabolism [29]. We previously observed that treatment with FA rescues DHFR-specificinhibitory mechanisms that impact downstream folate metabolism and cellular growtharrest and/or cell death [4]. To assess DHFR-dependence and FA rescue, cell viabilityassays were performed again in MDA-MB-468, MDA-MB-231, and MCF-7 cells in thepresence of 10 µM of each compound ± 300 µg/mL FA for 72 h.Consistently, in all three cell lines tested, FA rescued the effects of Pyr on cell viability.Only Pyr and Baker’s antifolate demonstrated statistically significant rescue in MDA-MB-468 cells, but viability impairment by Baker’s antifolate was not rescued in the other twocell lines (Figure 4 and Table S4). Conversely, viability impairment by MTX was rescuedMetabolites 2023, 13, 151 13 of 22in both MCF-7 and MDA-MB-231 cells but not in MDA-MB-468 cells. In general, Cyc-likecompounds showed no rescue by FA in all cell lines, except for a small yet statisticallysignificant rescue of 3077 viability impairment in MCF-7 cells. Interestingly, FA failedto rescue the impairment of viability caused by 127153 and 128184 in all three cell lines,whereas 127159 and 123032 were rescued in all but MDA-MB-468 cells, with the largestamplitude of rescue in MDA-MB-231 cells. The failure to rescue impaired viability withFA suggests that this effect may not be exclusively due to DHFR inhibition, and inhibitionof other targets or pathways may contribute to the observed decreases in viability forsome compounds.Metabolites 2023, 13, x FOR PEER REVIEW 14 of 24 two cell lines (Figure 4 and Table S4). Conversely, viability impairment by MTX was res‐cued in both MCF‐7 and DA‐MB‐231 cells but not in DA‐MB‐468 cells. In general, Cyc‐like comp unds showed no rescue by FA in all cell lines, except for a small yet s atis‐tically significant rescue of 3077 viability i pairment in MCF‐7 cells. Interestingly, FA failed to rescue the i pairment of viability caused by 127153 and 128184 in all three cell lines, whereas 127159 and 123032 were rescued in all but MDA‐MB‐468 cells, with the largest amplitude of rescue in DA‐MB‐231 cells. The failure to rescue impaired viability with FA suggests that this effect may not be exclusively due to DHFR inhibition, and in‐hibition of other targets or pathways may contribute to the observed decreases in viability for some compounds. Figure 4. Folinic acid viability rescue in breast cancer cells. MCF‐7, MDA‐MB‐231, and MDA‐MB‐468 cells were treated with 10 μM inhibitor for 72 h with or without 300 μg/mL folinic acid (FA) to investigate DHFR dependence. Cell viability was monitored by the incorporation of resazurin, as measured by fluorescence. The relative viability of each treatment was normalized to the DMSO control. An Ordinary one‐way ANOVA with Šídák’s multiple comparisons was performed to test for significant differences between each treatment with inhibitor alone and treatment with inhibitor Figure 4. Folinic acid viability rescue in breast cancer cells. MCF-7, MDA-MB-231, and MDA-MB-468cells were treated with 10 µM inhibitor for 72 h with or without 300 µg/mL folinic acid (FA) toinv stigate DHFR dependenc . Cell iability was monitored by the inc rporation of resazurin, asmeasured by fluorescence. The relative viability of each tr atment was normalized to the DMSOcontrol. An Ordinary one-way ANOVA with Šídák’s multiple comparisons was performed to testfor significant differences between each treatment with inhibitor alone and treatment with inhibitorand FA (red). Each experiment was performed in triplicate and repeated in three independent assays(n = 3). (ns = not significant; * = p ≤ 0.05; ** = p ≤ 0.01; *** = p ≤ 0.001; **** = p ≤ 0.0001).Metabolites 2023, 13, 151 14 of 223.5. Cycloguanil Derivatives Potently Engage DHFR in Cells and Cell LysatesTo determine whether each compound could engage DHFR in a biologically relevantenvironment, a modified cellular thermal shift assay (CETSA) in MDA-MB-468 lysates wasperformed. CETSA experiments measure changes in thermal stability that occur when aligand or inhibitor binds to its protein target. A shift in the thermal denaturing profile ofprotein is evidence of direct physical interaction between an inhibitor and its target [30]. Amelting curve for DHFR was established where cell lysates were first heated, then insolubleproteins were removed by centrifugation, and soluble DHFR levels were determined fromthe supernatant using Western blot. The quantified Western blot bands were fit usingnon-linear regression analysis to give an aggregation temperature (Tagg, temperature where50% of DHFR aggregates) of 41.50 ± 1.0 ◦C. When lysates were heated at 45 ◦C, therewas ~18% soluble DHFR remaining (Figure S4), which was appropriate to investigateDHFR stabilization by inhibitors in a higher throughput experimental format. Uncroppedblots are shown in Figure S5. MDA-MB-468 cell lysates were accordingly incubated with10 µM of each inhibitor and heated at 45 ◦C for 3 min, which significantly reduced solubleDHFR levels compared to the 37 ◦C control (Figure 5a,b and Table S5). Each compoundsubstantially rescued DHFR against thermal degradation up to levels that were comparableto the DMSO control at 37 ◦C. For most treatments, this stabilization was statisticallysignificant, except for 3062 and 139105 (Table S5). Treatment with 10 µM Pyr, MTX, Cyc,3077, 123032, and 127153 resulted in band densities that were greater than 100% which maybe due to some denaturing occurring in the 37 ◦C control that the inhibitors can also rescue.Uncropped blots are shown in Figure S6.To move into a cellular context, DHFR accumulation was used as a determinant oftarget engagement leveraging DHFR’s autoregulatory mRNA-binding mechanism. In cells,human DHFR binds to its own mRNA, preventing further translation into protein [31]. How-ever, upon inhibitor binding to DHFR, this interaction is disrupted, releasing DHFR mRNA,which is translated into protein. This leads to a temporary accumulation of DHFR proteinlevels which can be observed in both cell-based assays [4] and clinical settings [32,33].All compounds tested led to an accumulation of DHFR in MDA-MB-468 breastcancer cells in a dose-dependent manner, indicating that they engaged DHFR in cells(Figure 5c). Pyr and MTX both induced accumulation of DHFR in a similar manner toprevious studies [4]. Several of the Cyc derivatives were more potent than both Pyr andMTX, approaching saturating DHFR accumulation at a concentration of only 1 nM. Sub-sequent experiments were performed at a lower concentration range (0.012–1 nM) whereMTX, 127153, 127159, and 128184 led to a notable accumulation of DHFR at only 0.33 nM(Figure 5d), indicating these triazene compounds are highly potent and cell-active DHFRinhibitors. Uncropped Western blots from all DHFR accumulation experiments are shownin Figures S7 and S8.3.6. Inhibitors Fail to Impair Wound Healing nor bind Thymidine Phosphorylase in MDA-MB-231Breast Cancer CellsA recent report highlighted Pyr demonstrates promising anti-cancer and anti-metastaticactivity in lung cancer through dual targeting of DHFR and thymidine phosphorylase(TP) [34]. To determine if targeting TP may also contribute to the reduced viability of breastcancer cells, TP engagement by CETSA was assessed MDA-MB-468 cell lysates, but no sta-bilization of TP was detected by any of the compounds, including Pyr (Figures S9 and S10).To investigate the effects on cell migration, a wound-healing assay was performed inMDA-MB-231 cells. A scratch wound was induced on a confluent layer of MDA-MB-468cells treated with or without 10 µM inhibitor. In this setting, none of the inhibitors signifi-cantly inhibited cell migration relative to the DMSO control (Figure S11). Taken together,these data failed to confirm Pyr and other DHFR inhibitors bind to TP or inhibit migra-tion of MDA-MB-231 cells at concentrations where Pyr, MTX, Cyc, and Cyc derivativesengage DHFR.Metabolites 2023, 13, 151 15 of 22Metabolites 2023, 13, x FOR PEER REVIEW 16 of 24 Figure 5. Cyc analogues interact with and stabilize DHFR in breast cancer cells. (a) MDA‐MB‐468 lysates were treated with 10 μM of each compound and incubated at 45 °C. Lysates were electro‐phoretically separated, and DHFR was detected via Western blot. DHFR bands were normalized to the thermostable SOD1 control. (b) Relative band intensities from (a) were compared to the DMSO control at 45 °C (red, #) using an Ordinary one‐way ANOVA with Dunnett’s test for multiple com‐parisons. Each treatment was performed with five replicates over three independent experiments (n = 5). (c) MDA‐MB‐468 cells were treated with 0–10 μM of each inhibitor for 24 h. DHFR and the thermostable SOD1 were detected via Western blot as described in (a). Relative band densities were plotted against inhibitor concentration (μM, Log10 scale) to observe a dose‐dependent increase in DHFR protein levels. (d) MDA‐MB‐468 cells were treated with 0–1 nM of select inhibitors as de‐scribed in (c) to investigate relative potency. Some compounds stabilize DHFR at sub‐nanomolar concentrations. All DHFR accumulation experiments were performed in duplicate in two independ‐ent assays (n = 2). (ns = not significant; * = p ≤0.05; ** = p ≤ 0.01; *** = p ≤ 0.001). To move into a cellular context, DHFR accumulation was used as a determinant of target engagement leveraging DHFR’s autoregulatory mRNA‐binding mechanism. In Figure 5. Cyc analogues interact with and stabilize DHFR in breast cancer cells. (a) MDA-MB-468lysates were treated with 10 µM of each compound and incubated at 45 ◦C. Lysates were elec-trophoretically separated, and DHFR was detected via Western blot. DHFR bands were normalizedto the thermostable SOD1 control. (b) Relative band intensities from (a) were compared to the DMSOcontrol at 45 ◦C (red, #) using an Ordinary one-way ANOVA with Dun ett’s t st for multiple compar-isons. Ea h treatm nt was performed with five replicates over three independent exp riments (n = 5).(c) MDA-MB-468 cells wer treated with 0–10 µM of each inhibitor for 24 h. DHFR and the ther-mostable SOD1 were detected via Western blot as described in (a). Relative band densities wereplotted against inhibitor concentration (µM, Log10 scale) to observe a dose-dependent increase inDHFR protein levels. (d) MDA-MB-468 cells were treated with 0–1 nM of select inhibitors as describedin (c) to investigate relative potency. Some compounds stabilize DHFR at sub-nanomolar concentra-tions. All DHFR accumulation experiments were performed in duplicate in two independent assays(n = 2). (ns = not significant; * = p ≤0.05; ** = p ≤ 0.01; *** = p ≤ 0.001).Metabolites 2023, 13, 151 16 of 223.7. Cycloguanil and 127159 Inhibit Cellular Folate MetabolismOut of the Cyc analogues tested, 127159 was selected for further study due to itsrobust interaction with DHFR in vitro and cells, as well as strong rescue by FA in cellviability experiments, especially in MDA-MB-231 cells. Therefore, 127159 and Cyc wereassessed alongside MTX and Pyr (tested previously [4]) to determine their impact on folate-dependent nucleotide levels. Accordingly, MDA-MB-231 cells were treated with MTX, Pyr,Cyc, or 127159 (10 µM) with or without 300 µg/mL FA, and nucleotide levels were assessedusing LC/MS. Supplementation with FA resulted in an increase in downstream folatespecies, as expected (Figure S12). Principal component analysis (PCA) of the metabolicresponse to the different compounds (with and without FA supplementation) demonstratedthat Cyc- and MTX-treated cells clustered together, whereas 127159 clustered with Pyr(Figure 6a). All four treatments were markedly different compared to the DMSO-treatedcells. Cells treated with MTX, Pyr, and Cyc and supplemented with FA clustered withDMSO-treated cells, whereas the 127159 + FA trended towards these data but remaineddistinct (Figure 6a). This suggests a common molecular mechanism for the four drugsinvolved in reduced-folate depletion via DHFR inhibition.To investigate the downstream impacts of these compounds, nucleotide metabo-lite levels were assessed (summarized in Figure 6b). All four compounds significantlydepleted ADP, CDP, GDP, and IMP (Figure 6c and Table S6). UDP was significantly de-pleted in cells treated with Pyr and Cyc but not upon treatment with MTX and 127159alone. In all cases, FA supplementation led to an accumulation of nucleotides approachingthe DMSO + FA control, although not all conditions were statistically insignificant com-pared to the control (Table S6). Other nucleotide intermediates, including those whichrely on reduced folate for their metabolism (dUMP, glycineamide ribonucleotide (GAR),5-aminoimidazole-4-carboxamide ribonucleotide (AICAR)) and the pyrimidine intermedi-ate orotate were also measured. Similar effects were observed on dUMP and GAR, whereDHFR inhibitor treatment increased these nucleotides, then returned them towards controllevels with FA, although 127159 + FA quantitation of GAR was significantly different fromthe DMSO + FA control (Figure 6d and Table S6).Interestingly, 127159 had strikingly different impacts on orotate and AICAR levelscompared to the other anti-folates. While decreased or statistically insignificant changesin orotate levels were observed in cells treated with MTX, Pyr, or Cyc, treatment with127159 led to a stark increase in orotate levels. FA supplementation returned orotateto vehicle control levels for MTX, Cyc, and Pyr; however, it failed with 127159, whereorotate remained elevated in the presence of FA. AICAR levels also increased slightly,yet significantly after treatment with 127159, whereas Cyc and Pyr induced much largerincreases in AICAR and MTX failed to increase AICAR levels in a statistically significantmanner. Treatment with FA returned AICAR to the same levels as vehicle controls forCyc and Pyr, but FA treatment further increased AICAR by 127159 (Figure 6c,d), whichmay suggest that 127159 inhibits downstream processing of AICAR. Together, these resultscorroborate the hypothesis that Cyc and 127159, such as MTX and Pyr, likely inhibit DHFRto impact cellular metabolite levels, although there are some unique aspects of their impacton nucleotide metabolism that may warrant further study.3.8. Cycloguanil Analogues Inhibit STAT3 Transcriptional ActivityFinally, with recent evidence demonstrating that Pyr and MTX induce their anti-canceractivity (at least in part) by halting STAT3 transcriptional activity, these compounds wereassessed in the STAT3-dependent luciferase reporter assay using U3A (male) fibrosarcomacells, as performed previously [4]. This cell line lacks basal STAT3 phosphorylation andsubsequent activation [4] and lacks expression of STAT1 [35], thus eliminating confoundingSTAT1-STAT3 interactions and background STAT3-dependent signal. A broad concentrationrange (0.02–20 µM) was used to cover both the concentrations where DHFR accumulationwas observed and where phenotypic responses were seen. Interestingly, potent inhibition ofluciferase activity is found with MTX and Cyc even at low inhibitor concentrations, whereasMetabolites 2023, 13, 151 17 of 22Pyr and 127159 demonstrate a dose-response and do not reach full STAT3 inhibition untilµM concentrations (Figure 7). Data from an additional independent experiment are shownin Figure S13 which shows a similar trend and statistical comparisons for these experimentsare displayed in Table S7. Combined, these results support previous claims that targetingDHFR decreases STAT3 transcriptional activity and point towards STAT3 being involved inthe anti-cancer mechanism of these DHFR inhibitors.Metabolites 2023, 13, x FOR PEER REVIEW 18 of 24 Figure 6. Metabolite profiling with FA supplementation support Cyc and 127159 impact folate ho‐meostasis through inhibition of DHFR. (a) Global PCA analysis of polar metabolites detection in cells treated for 24 h with DMSO, MTX, Pyr, Cyc, 127159, and ± folinic acid. (b) Top 25 differentially detected metabolites from (a). (c) Detected levels of representative nucleotides of de novo synthesis and salvage pathways in the treated cells from (a). All levels were normalized to the DMSO level. (d) Detected levels of nucleotide intermediates in the treated cells from (a). Each replicate represents extracted metabolites from one million cells per condition, and error bars represent the standard deviation of the mean (n = 4). All levels were normalized to the DMSO level. An Ordinary one‐way ANOVA with Šídák’s correction for multiple comparisons was performed to compare each treat‐ment versus DMSO control and to compare each treatment + FA versus DMSO + FA control. Only statistically significant comparisons are indicated (* = p ≤0.05; ** = p ≤ 0.01; *** = p ≤ 0.001; **** = p ≤ 0.0001). To investigate the downstream impacts of these compounds, nucleotide metabolite levels were assessed (summarized in Figure 6b). All four compounds significantly de‐pleted ADP, CDP, GDP, and IMP (Figure 6c and Table S6). UDP was significantly depleted in cells treated with Pyr and Cyc but not upon treatment with MTX and 127159 alone. In all cases, FA supplementation led to an accumulation of nucleotides approaching the DMSO + FA control, although not all conditions were statistically insignificant compared Figure 6. Metabolite profiling with FA supplementation support Cyc and 127159 impact folatehomeostasis through inhibition of DHFR. (a) Global PCA analysis of polar metabolites detection incells treated for 24 h with DMSO, MTX, Pyr, Cyc, 127159, and ± folinic acid. (b) Top 25 differentiallydetected metabolites from (a). (c) Detected levels of representative nucleotides of de novo synthesisand salvage pathways in the treated cells from (a). All levels were normalized to the DMSO level.(d) Detected levels of nucleotide intermediates in the treated cells from (a). Each replicate representsextracted metabolites from one million cells per condition, and error bars represent the standarddeviation of the ean (n = 4). All levels were normalized to the DMSO level. An Ordinary one-way ANOVA with Šídák’s correction f r multiple comparisons was performed to compare eachtreatment versus DMSO control and to compare each treatment + FA versus DMSO + FA control.Only statistically significant comparisons are indicated (* = p ≤0.05; ** = p ≤ 0.01; *** = p ≤ 0.001;**** = p ≤ 0.0001).Metabolites 2023, 13, 151 18 of 22Metabolites 2023, 13, x FOR PEER REVIEW 20 of 24 Figure 7. DHFR inhibitors block STAT3‐dependent gene expression. U3A cells were incubated with respective inhibitors at 0.02, 0.2, 2, or 20 μM for 1 h prior to the addition of OSM (10 ng/mL) or vehicle control and incubation for 5 h. Luciferin was added, and luminescence was measured. Pre‐sented data are normalized to the OSM stimulated control (100%, #), and statistical significance was determined using an Ordinary one‐way ANOVA with a Dunnett multiple comparison test (ns = not significant; ** = p ≤ 0.01; **** = p ≤ 0.0001). This is a representative figure of the experimental results. Data from an additional individual experiment are shown in Figure S13. 4. Discussion Current anti‐cancer drug treatment strategies include diverse medicines spanning more than 70 years of anti‐cancer drug discovery research—from state‐of‐the‐art targeted therapies and biologics all the way back to early anti‐metabolites and platinum‐based chemotherapies. While several classic therapies have stood the test of time and remain the standard of care for cancer patients, the search for new and more effective cancer therapies remains an eternal quest for drug discovery scientists. In this study, modern chemical bi‐ology techniques and analytical methods have been applied to classic DHFR inhibitors MTX, Pyr, Cyc, and Cyc analogues. Capitalizing on databases from the NCI—Develop‐mental Therapeutics Program and NCI‐60 Human Tumor Cell Lines Screening, com‐pounds with promising inhibitory activity against human DHFR were revisited [16,19]. These Cyc analogues were initially explored for their anti‐cancer activity and ability to inhibit DHFR in tissue isolates and in vivo models [14,36]. While Cyc, Pyr, MTX, and Baker’s antifolate had a considerable mention in the literature, the other Large Cyc Ana‐logues appear in relatively few resources. In early studies in the 1970s, 123032 (compound 10 in reference [14]), 128184 (compound 24 in reference [15]), 127153 (compound 19 in reference [14]), and 127159 (compound 2 in reference [13]) showed promising anti‐leuke‐mic activity in vivo, even compared to MTX. Thus, their emergence in this study, using in silico docking and historical growth inhibition from the NCI, was somewhat surprising, yet highlights the utility of drug repurposing and revisiting even very early anti‐cancer compounds to define their scope of use better and to explore them as potential chemical probes. The NCI‐60 data indicated a high correlation between inhibitor GI50 values in both breast cancer and melanoma cell lines. While this study focused on breast cancer, further studying these compounds within the context of melanoma is recommended. In‐house generated cell viability data reinforced trends observed in the NCI data sets and previous studies with these compounds [13–15,36,37]. Many of the compounds gave dose‐response Figure 7. DHFR inhibitors block STAT3-dependent gene expression. U3A cells were incubated withrespective inhibitors at 0.02, 0.2, 2, or 20 µM for 1 h prior to the addition of OSM (10 ng/mL) or vehiclecontrol and incubation for 5 h. Luciferin was added, and luminescence was measured. Presented dataar normalized to the OSM stimulated control (100%, #), and statis cal significance was determinedusing an Ordinary one-way ANOVA with a Dunnett multiple comparison test (ns = not significant;** = p ≤ 0.01; **** = p ≤ 0.0001). This is a representative figure of the experimental results. Data froman additional individual experiment are shown in Figure S13.4. DiscussionCurrent anti-cancer drug treatment strategies include diverse medicines spanningmore than 70 years of anti-cancer drug discovery research—from state-of-the-art targetedtherapies and biologics all the way back to early anti-metabolites and platinum-basedchemotherapies. While several classic therapies have stood the test of time and remainthe standard of care for cancer patients, the search for new and more effective cancertherapies remains an eternal quest for drug discovery scientists. In this study, mod-ern chemical biology techniques and analytical methods have been applied to classicDHFR inhibitors MTX, Pyr, Cyc, and Cyc analogues. Capitalizing on databases from theNCI—Developmental Therapeutics Program and NCI-60 Human Tumor Cell Lines Screen-ing, compounds with promising inhibitory activity against human DHFR were revis-ited [16,19]. Th se Cyc a alogues w re initially explored for their anti-cancer activityand ability to i hibit DHFR in tiss e i olates and in vivo models [ 4, 6]. While Cyc, Pyr,MTX, and Bak r’s antifolate had a co siderabl m tion in the literature, the other LargeCyc A alogues appear in relatively few resources. In early studies in the 1970s, 123032(compound 10 in reference [14]), 128184 (compound 24 in ref rence [15]), 127153 (com-pound 19 in reference [14]), and 127159 (compound 2 in reference [13]) showed promisinganti-leukemic activity in vivo, even compared to MTX. Thus, their em rgence in this study,using in silic ocking and hist rical growth inhibition from the NCI, was somewhatsurprising, yet highlights the utility of drug repurposing and revisiting even very earlyanti-cancer compounds to define their scope of use better and to explore them as potentialchemical probes.The NCI-60 data indicated a high correlation between inhibitor GI50 values in bothbreast cancer and melanoma cell lines. While this study focused on breast cancer, furtherstudying these compounds within the context of melanoma is recommended. In-housegenerated cell viability data reinforced trends observed in the NCI data sets and previousstudies with these compounds [13–15,36,37]. Many of the compounds gave dose-responseMetabolites 2023, 13, 151 19 of 22curves that had lower asymptotes, around 50% viability, suggesting a growth inhibitionrather than a cytotoxic mechanism of action. In addition to the growth inhibition phenotype,some compounds also induced cell death at higher concentrations. Initially, this wassuspected to be evidence of polypharmacology or non-specific toxic effects of compounds;however, FA rescue experiments did not support this hypothesis, where impaired viabilityof some of the cell death-inducing compounds (i.e., 123032 and 127159) could be rescuedby FA in MCF-7 and MDA-MB-231 cells. Intriguingly, these compounds both possessa sulfonyl fluoride moiety which confers covalent reactivity to these inhibitors and canbe associated with promiscuity. Their rescue by FA, and the lack of rescue with the non-sulfonyl fluoride analogous compounds (127153 and 128184), in fact, suggests that thesulfonyl fluoride moiety may instead confer selectivity for DHFR rather than promiscuity.Although a previous study suggested that Pyr is also a direct binder and inhibitor ofTP [34] in biochemical experiments (Biacore and differential scanning fluorimetry), CETSAexperiments with Pyr, MTX, Cyc, and Cyc analogues could not confirm binding to TP inbreast cancer cell lysates at relevant concentrations for DHFR engagement and phenotypicresponses in breast cancer cell lines. These compounds also failed to halt cell migration inthe wound-healing assay. Similarly, MTX has recently been shown not to impact migrationin MDA-MB-468 cells [38] but has been found to promote migration in other cancer celltypes [39]. The data presented herein, along with recent investigations on the impact ofnucleic acid synthesis, may point toward cell line-specific or cancer-type-specific responsesto these inhibitors.Perhaps most striking of all is the DHFR target engagement by accumulation data,where Cyc analogues were extremely potent. Similar to MTX, several of the Cyc com-pounds showed evidence of DHFR binding below 1 nM concentration, whereas Pyr andCyc, required higher concentrations to induce DHFR accumulation. Some Cyc analoguesinduced comparable DHFR accumulation to MTX, where 10 nM induced a ~5-fold increase,and 1 µM induced ~40-fold increase in DHFR levels, compared to 127159, which induced 10-and 30-fold increases at 10 nM and 1 µM, respectively. Moreover, while Cyc failed to induceDHFR accumulation at low nM concentrations in MDA-MB-468 cells, STAT3-dependentluciferase activity was significantly inhibited upon treatment with 20 nM Cyc in U3A. Thismay arise either due to cell-line differences or may support a different target or mechanismthat may be linked to the STAT3 inhibitory activity of these compounds.Finally, the metabolite profiles for these compounds were remarkably similar whenanalyzed by PCA, where Cyc and Pyr clustered together, while MTX and 127159 clusteredtogether, all of which moved closer to DMSO-treated levels upon treatment with FA.However, deeper analyses identified unique ways of 127159 affecting the metabolite pools,namely by increasing AICAR levels in the presence of FA, whilst other DHFR inhibitorstended to give the opposite response. In addition, 127159 increased orotate levels bothwith and without FA supplementation, which was unique to this compound over otherDHFR inhibitors tested. Orotate is a pyrimidine molecule that can be converted intouridine monophosphate by uridine-5-monophosphate synthetase. The buildup of orotateby 127159 uniquely is curious and points to possible off-target effects of the inhibitor, butfurther investigation is required to investigate this phenomenon. These effects are likelythe underlying reasons for the differences in the PCA for this compound relative to theother DHFR inhibitors.Overall, it is reasonable to suspect that these differences may be of biological signifi-cance and linked to the anti-cancer efficacy of these compounds; however, at this time, theprecise nature of this relationship is not yet clearly defined for all of these compounds andwarrants further study.5. ConclusionsThe presented data highlight the benefits of applying state-of-the-art chemical biologyand analytical techniques to classic small molecule inhibitors. These methods have shown127159 and other Cyc analogues behave as potent DHFR inhibitors and may be consideredMetabolites 2023, 13, 151 20 of 22for further exploration within the realm of cancer therapies, perhaps with greater emphasison specific disease models and/or scope of utility.Supplementary Materials: The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/metabo13020151/s1, Figure S1: Ligand-receptor 2D interaction diagramsfor the top pose of each docked compound; Figure S2: Cycloguanil analogues inhibit DHFR enzymaticactivity in vitro; Figure S3: Linear range of DHFR enzymatic assay; Figure S4: Melt curve for DHFR incell lysate; Figure S5: Uncropped Western blots for data presented in Figure S4; Figure S6: UncroppedWestern blots for data presented in Figure 5a,b; Figure S7: Uncropped Western blots for data presentedin Figure 5c; Figure S8: Uncropped Western blots for data presented in Figure 5d; Figure S9: Impactof cycloguanil analogues on thymidine phosphorylate thermal stability; Figure S10: UncroppedWestern blots for data presented in Figure S9a; Figure S11: Impact of cycloguanil analogues onwound healing; Figure S12: Folinic acid supplementation significantly increases folate species thatare downstream of DHFR; Figure S13: DHFR inhibitors block STAT3-dependent gene expression;Table S1: Number of References found by structure search using SciFindern as of January, 2023;Table S2: Comparison of GI50 values for each inhibitor from Human Tumor Cell Lines Screen revealsignificant differences; Table S3: GI50 values for each inhibitor compared to the methotrexate goldstandard separated by cell line; Table S4: Cell viability with inhibitor alone and together with folinicacid; Table S5: CETSA analysis of DHFR in lysate treated with cycloguanil-like triazene compounds;Table S6: Statistical comparisons for the data presented in Figure 6; Table S7: Statistical comparisonsfor the data presented in Figure 7 and Figure S13.Author Contributions: Conceptualization, B.D.G.P. and J.I.B.; methodology, B.D.G.P., J.I.B., N.K.,D.A.F. and K.C.W.; software, B.D.G.P. and A.Y.L.W.; validation, J.I.B., P.W., B.P., R.P., S.S., M.L.M.,D.H., J.C. and W.W.; investigation, J.I.B., P.W., B.P., R.P., S.S., M.L.M., D.H., J.C., P.I., D.K.E. and W.W.;formal analysis, J.I.B., B.D.G.P., P.W., A.Y.L.W., S.S. and W.W.; resources, B.D.G.P., N.K., D.A.F. andK.C.W.; data curation, J.I.B. and B.D.G.P.; writing—original draft preparation, J.I.B. and B.D.G.P.;writing—review and editing, J.I.B., B.D.G.P., S.S., P.W., N.K., K.C.W. and D.A.F.; visualization, J.I.B.,B.D.G.P. and P.W.; supervision, B.D.G.P., N.K., D.A.F., K.C.W. and J.I.B.; project administration,B.D.G.P. and J.I.B.; funding acquisition, B.D.G.P., N.K., D.A.F. and K.C.W. All authors have read andagreed to the published version of the manuscript.Funding: This research was funded by: The University of British Columbia (B.D.G.P), The CanadianInstitutes of Health Research (CIHR), (DFSA–DFD-181606, A.Y.L.W; CGSM, D.K.E; CGSD, S.S.; PG-461696, B.D.G.P, and K.C.W.), the Natural Sciences and Engineering Research Council of Canada(NSERC, CGSD, D.H.), Croucher Fellowships for Postdoctoral Research (P.W.). Infrastructure supportwas also received from the Canadian Foundation for Innovation and the British Columbia KnowledgeDevelopment Fund (40725). B.D.G.P is a Michael Smith Health Research B.C. Scholar (18292), N.K. isa Pew Biomedical Scholar.Institutional Review Board Statement: Not applicable.Informed Consent Statement: Not applicable.Data Availability Statement: All data from the National Cancer Institute Developmental Thera-peutics Program NCI-60 Human Tumor Cell Lines Screen can be found here: https://dtp.cancer.gov/public_compare/. 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dihydrofolate reductase
folate metabolism
target engagement
cancer therapy
cycloguanil
breast cancer
STAT3
Cycloguanil and Analogues Potently Target DHFR in Cancer Cells to Elicit Anti-Cancer Activity
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