Quinoline–1,3,4-Oxadiazole Conjugates: Synthesis, Anticancer Evaluation, and Molecular Modelling Studies

Abstract Cancer continues to have overwhelming impacts on human health and the development of new chemotherapeutics. Molecular hybridization has thus been valued as a structure-based drug design approach to drugs with enhanced efficacy. Herein, we report the multistep synthesis of quinoline–2-mercapto-1,3,4-oxadiazole conjugates and their cytotoxicity evaluation. Compound 4j 2-[(5-bromopentyl)thio]-5-[(quinolin-8-yloxy)methyl]-1,3,4-oxadiazole showed the best cytotoxicity to pancreatic (MIA PaCa-2) and colorectal (HCT116) cancer cells with IC50 values of 29.19 ± 0.99 and 75.10 ± 1.87 µM, respectively. The compound is also less cytotoxic to non-cancerous human primary dermal fibroblast cells with IC50 = 91.87 ± 1.29 µM compared to the parent compound 8-hydroxyquinoline (IC50 = 72.36 ± 4.23 µM). ADME properties prediction suggested the drug-likeness of potent compounds while molecular docking and molecular dynamics simulations with doublecortin-like kinase (DCLK1) revealed the compounds’ stable binding interactions at the kinase domain. Overall, the results illuminate compound 4j as a structural model to furnish new cytotoxic agents against pancreatic and colorectal cancer.


Introduction
The devastating effect of cancer lingers as an unsolved reddle despite the landmark progress made in understanding the molecular biology and pathogenesis. The disease remains the main culprit behind disorders disabilities, and elevated mortality rates in humans globally. 1 The Global Cancer Observatory (GLOBOCAN) reports for the year 2020 estimated the disease burden as 19.3 million new cases and 9.96 million cancer-related deaths with a projected increase of 64 and 61% in the incidence and mortality rates, respectively, by the year 2040. 2 Gastrointestinal (GI) cancers, i.e. neoplasms found in the GI tract including colon, pancreas, and stomach, accounts for 26.3% of new cancer cases and 35% of all cancer mortalities. 3 Precisely, colorectal cancer (CRC) has the highest incidence and mortality rates among GI cancers and exists as the third most diagnosed malignancy, i.e. 10% of all new cases globally. On the other hand, pancreatic cancer (PC) presents the poorest prognosis and an abysmally low five-year survival rate of less than 8% compared to other cancer types. 1,3 The fatality of PC is highlighted by its parallel incidence and mortality rates arising from an aggressive metastatic nature.
The burden of these GI cancers is further complicated by the lack of safe therapies at the metastatic stage where majority of the cases are diagnosed. Although combination therapies including chemo-and radiotherapy have been employed as a treatment option, low selectivity for cancerous cells and consequently adverse effects remains a significant challenge. For instance, the toxicity issues associated with combination drug FOLFIRINOX and nab-paclitaxel/gemcitabine. 4 These limitations highlight a desperate need for new anticancer drugs that will momentously improve patients' survival. 5 Drug resistance is another menacing hurdle in anticancer drug development for which molecular hybridization (MH), a polypharmacology and structure-based approach has been adopted by both industry and academia to deliver drugs with enhanced potencies. 6 The strategy involves covalently linking two or more pharmacophores into a single molecular architecture; hence, resulting in a synergetic effect of the pharmacophores. 7 The hybrid molecule is thus furnished with multi-receptor recognition and consequently, an improved efficacy. The pinnacle of MH is better pharmacokinetics, reduced cost, and side effects as well as minimized drug-drug interactions.
Furthermore, a deeper understanding of the genomic landscape and molecular mechanisms of cancer is regarded as the catalyst for the needed breakthrough in targeted therapies and the associated drug resistance. 8,9 One of the most appealing candidates being protein kinases due to their roles in fundamental cellular pathways conducted by phosphorylating proteins associated with membrane transport, gene expression, metabolic pathways, cell division, growth, survival and apoptosis. 10 Doublecortin-like kinase 1 (DCLK1), a serine-threonine protein kinase belonging to the microtubule-associated protein family, is acknowledged as a tuft cell marker and has been implicated in the poor prognosis of GI, 11 lung, 12 breast, 13 and ovarian 14 cancers. DCLK1 regulates the dynamic polymerization of microtubule through its doublecortin domain to expedite cellular growth and differentiation. The protein kinase is expressed in quiescent GI cells and upon injury is a strong driver for GI cancers by promoting tumor growth, survival and metastasis. 15,16 Moreover, the overexpression of DCLK1 in cancer cells bearing KRas mutations such as CRC (HCT116) and PC (MIA PaCa-2) cells has been linked to the aggressiveness and poor prognosis of such cancers. 17 DCLK1 has therefore been explored as a druggable target for the treatment of CRC and PC. [18][19][20] Among nitrogen-containing heterocyclic compounds, the quinoline ring has proven its worth as an anticancer pharmacophore. This is evidenced by marketed drugs such as irinotecan, cabozantinib, and capmatinib 21,22 and libraries of quinoline-based hybrids recently reported as potent anti-colorectal cancer agents via the inhibition of protein kinases. 23,24 Moreover, 8-hydroxyquinoline (8-HQ) and its derivatives exist as a prominent class of quinoline compounds due to their metal chelating properties and extensive bioactivity spectrum. [25][26][27] 8-HQs have also demonstrated their anticancer efficacy via the modulation of target proteins and pathways crucial to cell proliferation and apoptosis such as b-(1,4)-galactosyltransferase, 28 glioma-associated oncogene 1, 29 matrix metalloproteinases, 30 Ras converting enzyme 1, 31 bradykinin B2 receptor 32 and mitochondrial pathway. 33 The 1,3,4-oxadiazole moiety, on the other hand, is consistently recruited in drug design owing to its broad spectrum of activity as well as bioisosterism of amides and esters. The azole's electronic properties favor non-covalent interactions with drug targets to elicit interesting pharmacological effects. Studies reveal that 1,3,4-oxadiazole derivatives exhibit potent anticancer properties via the inhibition of target proteins such as epidermal growth factor, vascular endothelial growth factor, histone deacetylase and glycogen synthetase kinase-3. 34 Zibotentan, an anticancer drug candidate currently in clinical trials illuminates the therapeutic significance of 1,3,4-oxadiazole based molecules. 35 Our exploits on MH approach to developing bioactive molecules have highlighted the anticancer potential of 2-mercapto-1,3,4-oxadiazole and 8-HQ pharmacophores. 36,37 Herein, we examined the in vitro cytotoxicity of hybrid molecules bearing both pharmacophores against CRC and PC cell lines alongside the toxicity of potent compounds to human primary dermal fibroblast (HDFa) cells, a non-cancerous cell line to verify the compounds' selectivity for cancer cells. The drug-likeness (ADME properties) of these compounds and their binding affinity to DCLK1 were also explored in-silico.

Materials and methods
All the reagents used were purchased from Sigma Aldrich, South Africa. The reaction progress were all monitored with silica gel coated thin later chromatography (TLC) plates at different solvent polarities and visualized under 254 nm UV lamp. Final products were purified using silica gel (0.063-0.200 mm) column chromatography and ethyl acetate: hexane eluents. NMR data ( 1 H, 13 C and 2 D) was recorded with Bruker Avance III 400 and 600 Hz spectrometers ( 1 H at 400 or 600 MHz and 13 C at 101 or 151 MHz). The chemical shifts are reported in parts per million (ppm) and referenced relative to the residual solvent signals of DMSO-d 6

Synthesis of ethyl 2-(quinolin-8-yloxy)acetate (1)
To a solution of 8-HQ (70 mmol) in DMF (40 mL) was added anhydrous potassium carbonate (138 mmol). The mixture was stirred at room temperature (r.t.) for 10 minutes and ethyl chloroacetate (83 mmol) was added and stirring continued for 6 hours. The reaction mixture was then poured into a slurry of ice and stirred for few minutes. The resulting yellow precipitate was filtered in vacuo while washing with hexane to obtain ethyl 2-(quinolin-8-yloxy)acetate (1) 13

Synthesis of 2-(quinolin-8-yloxy)acetohydrazide (2)
Hydrazine hydrate (120 mmol) was carefully added to 80 mL ethanol solution of compound 1 (60 mmol) in a round bottom flask. The flask's content was refluxed while stirring at 95 C overnight after which ethanol was removed using a rotary evaporator. The residue was cooled in an ice to precipitate 2-(quinolin-8-yloxy)acetohydrazide 2 which was filtered under vacuum and thoroughly washed with cold diethyl to obtain an cream white solid product.
Pale yellow solid; Chemical formula: C 11
Dark yellow solid; Chemical formula: C 12 H 9 N 3 O 2 S, Yield; 80%, Mol wt: 259.28 gmol General method for the synthesis of quinoline-1,3,4-oxadiazole conjugates (4a-u) The mixture of compound 3, benzyl bromides and potassium carbonate in DMF was stirred at room temperature for 2 hours. When the reaction was complete as monitored with TLC, the reaction mixture was diluted with water and extracted with EtOAc. The crude product was purified with column chromatography in EtOAc-hexane solvent mixture to obtain the quinoline-oxadiazole conjugates in 27-100% yields.            Kit-Serum-free (ATCC) cocktail, respectively. Cells were preserved in tissue culture flasks at 37 C and 5% CO2. Culture medium was replaced every three days.

Cell viability assay
The effect of each compound on cell viability was tested using the MTS assay. 38 Briefly, 7000 cells/well were grown in 96-well plates for 12 h. Then these cells were incubated with either DMSO (control) or different concentrations of the test compounds for 48 h. Three hours before the termination point, 20 mL of MTS was added to measure cellular viability. IC 50 values were calculated using OriginPro 8.5.1.

Molecular modeling protocols
The Schr€ odinger molecular modeling suite (release 2020-3) and OPLS3e force field were used for all calculations.

Ligand preparation
The 3 D models with low energy conformation for 8-HQ, 4j, 4l, and 4m compounds were generated with LigPrep 39 while their protonation states were assigned using Epik 40 at pH 7 ± 2.0.

Protein preparation
The crystal structure of DCLK1 protein with PDB ID: 5JZN was retrieved from Protein Data Bank. 41 The protein structure was prepared using Protein Preparation Wizard. 42 The default preprocess workflow was followed namely; adding hydrogen atoms, filling in missing side chains and loops using Prime, generating heteroatomic states at pH 7 ± 2.0, and deleting unwanted water molecules and heteroatoms. Subsequently, the protonation and tautomeric states of Asp, Asn and His were assigned followed by hydrogen bond network optimization and a brief minimization of the optimized protein structure to an RMSD of 0.3 Å.

Induced-fit docking and MM-GBSA binding free energy
The induced-fit docking (IFD) module 43 was utilized for ligand docking at the kinase domain of DCLK1. The protocol employs Glide docking and Prime refinement to accurately predict the ligand binding modes while accounting for protein flexibility. The parameters used includes defining the receptor's binding site using the centroid of workspace ligand, docking ligands with a length of 18 Å, auto trimming of residues withing 5 Å of binding site, initial glide docking using softened potential (van de Waals scaling of 0.7 Å), and Prime refinement of residues within 5 Å of docked ligand for each protein-ligand pose. Glide redock for each protein-ligand complex was performed using the lowest energy structure within 30 kcal/mol and extra-precision docking mode where the ligand is rigorously docked into the induced-fit receptor structure. Finally, each protein-ligand complex is scored by estimating the binding energy of each output pose. The protein-ligand complex with the best pose was selected using docking score, glide emodel and IFD scores then used as input for Prime Molecular Mechanics-Generalized Borne Surface Area (MM-GBSA) 44 calculations to estimate the free binding energy of the protein-ligand complex.

Molecular dynamics simulation
The docked poses of DCLK1-KD and potent compounds were submitted for molecular dynamics (MD) simulations with Desmond module. 45 The requisite model system of each complex was generated with the System Builder and solvated with single point charges (SCP) solvent models in an orthorhombic box with periodic boundary conditions. The model system was neutralized with appropriate Na þ and Clions and relaxed before the MD simulation. Using an NPT ensemble at a constant temperature of 300 K and pressure of 1 atm, MD simulation was performed for 200 ns while recording intervals at 200ps of the trajectory. The trajectory data was analyzed using the simulation interaction diagram tool.

Structural elucidation
The synthesized compounds were characterized using their spectroscopic data viz., NMR ( 1 H, 13  The cyclization of 2 to 1,3,4-oxadiazole 3 was then confirmed by the absence of these amino peaks and the presence of a broad singlet corresponding to -SH (d H 14.77). Specifically, the formation of compound 4 m was displayed in the 1 HNMR spectrum by prominent methylene (-CH 2 ) singlets of H-6 0 and H-7 0 resonating at d H 5.61 and 4.51, respectively. All the carbon and proton peaks were assigned using their heteronuclear single quantum coherence (HSQC) and heteronuclear multiple bond coherence (HMBC) correlations. For example, H-6 0 in compound 4m showed HMBC correlations with C-5 0 and C-8 at 164.37 and 153.37 ppm respectively while H-7'correlated with C-2 0 , C-8 0 and C-9 0 /13 0 at 164.71, 136.13 and 131.32 ppm, respectively ( Figure 1).

Cytotoxicity studies
The synthesized compounds 4a-4u were appraised for their cytotoxicity against pancreatic (MIA PaCa-2), colorectal (HCT116) and lung (H-460) cancer cell lines as well as human primary dermal fibroblast (HDFa) using cell viability assay ( Figure S1). The corresponding IC 50 values of potent compounds (i.e. the minimum concentration required to inhibit the growth of 50% cancer cells) are presented in Table 1.
We explored how MH and the variation of R-substituents affected the test compounds' cytotoxicity. Interestingly, compound 3, the precursor to compound 4a-4u had an inferior cytotoxicity compared to parent 8-HQ against the examined cancer cells. The results suggests that the reduced lipophilicity of 8-HQ and, conceivably, the hydrogen bond (H-b) donor ability of hydroxyl unit favors cytotoxicity compared to compound 3 and its thiol unit, respectively. The abolished cytotoxicity in compound 3 against CRC (HCT116) cells was also bequeathed on compounds 4a-u and varying the alkyl chain length or type and position of substituent on benzyl pendant did not translate to an enhanced potency.
Nonetheless, compound 4j, the 5-bromopentyl substituted derivative exhibited modest cytotoxicity (IC 50 ¼ 75.10 mM) against the CRC cells and two-fold superior cytotoxicity against PC (MIA PaCa-2) cells with IC 50 ¼ 29.19 mM compared to parent 8-HQ (IC 50 ¼ 63.54 mM); hence emerging as the most active compound in the library. More importantly, compound 4j showed significantly less cytotoxicity to HDFa cells with an IC 50 value of 91.87 mM compared to parent 8-HQ having IC 50 of 72.36 mM; thus, justifying the O-alkylation approach to attenuate the toxicity associated with 8-HQ.
Compounds 4l and 4m, the para-fluoro and -chlorobenzyl derivatives also displayed moderate cytotoxicity to PC cells with IC 50 values of 92.39 and 81.04 mM, respectively and were less toxic to HDFa cells (IC 50 > 100 mM). Interestingly, the para-bromo substituted compound 4n was inactive whereas changing the fluoro and chloro substituents to meta-positions led to total loss of potency. These results imply that the chloro unit is preferred to fluoro and bromo units for antipancreatic cancer activity even as the para-position is favored over meta-position. This SAR trend was reproduced in dihalo-substituted compounds 4s, 4t and 4u. The SARs are summarized in Figure 2.  The biochemical data also proved that the present molecular framework is not a suitable cytotoxic scaffold for lung cancer (H460) cells as the parent 8-HQ, hybrid molecules and their varied substituents did not provide the desired cytotoxicity. However, compound 4j with improved potency against PC cells (MIA PaCa-2), upheld the concept of molecular hybridization although the strategy was not favored in CRC and lung cancer cell lines HCT116 and H460, respectively.

ADME properties
Absorption, distribution, metabolism, and excretion (ADME) are pharmacokinetic properties governing the in vivo fate of bioactive molecules and their ability to elicit the desired physiological effect at the site of action. The proper tailoring of ADME properties is thus crucial to assessing structural optimization protocols, compound selection and consequently, the novelty in the drug development process. Fundamental properties such as structural and physicochemical properties as evaluated by the Lipinski's rule of 5, permeability, solubility and bioavailability are benchmarks conditions which an experimental drug must satisfy. 46 The ADME properties (Table 2) of active compounds in this work were computed with QikProp6.5 module in Schr€ odinger molecular modeling suite. 48 Compounds 4j, 4l and 4m with promising cytotoxicity against PC presented desirable druglike properties qualifying them for further structural optimization to enhance potency. This was evidenced from their non-violation of both Lipinski's rule of 5 (Ro5) and Jorgensen's rule of 3 (Ro3) except the lipophilicity parameter (QPlogPo/w) which was greater than 5 in compound 4j and 4m. The good oral bioavailability of the compounds is exhibited by their acceptable values for molecular weight (MW), hydrogen bond donors/acceptors (HBD/A), and percentage human oral absorption (h.O.abs). Moreover, the compounds' logP values (>3) and tPSA (>75) suggest their reduced likelihood of in vivo toxicity 49 while the QPPCaco values indicate good permeability to ensure complete absorption.

Molecular docking with DCLK1
Nitrogen-based heterocycles enjoy heightened attention as anticancer agents due to their potent DCLK1 inhibition. For instance, a quinoline-based drug, montelukast, inhibits tumor growth in mice models by suppressing the expression of DCLK1 50,51 while LRRK2-IN-1 and XMD8-92 have been employed as probes to understand the role of DCLK1 in PC and CRC cells but were discontinued due to their lack of specificity; 18 thus, birthing the discovery of a more potent and selective inhibitor, DCLK1-IN-1. The significance of amide units present in the core structure of these heterocycles motivated our selection of 1,3,4-oxadiazole as an amide bond bioisostere to enhance binding affinity at the active site of DCLK1 target. 52 The potency of montelukast in tumor growth minimization via DCLK1 inhibition, also reinforced the choice of quinoline as backbone in the present molecular architecture. Furthermore, abounding empirical evidence have specifically implicated the overexpression of DCLK1 in colon and GI cancers, particularly those bearing KRas mutations as fundamental to tumor growth, invasiveness, and metastasis. Consequently, molecular docking was employed to study the molecular level-behavior of potent compounds at the binding site of DCLK1 kinase domain (KD) to predict the effect of these molecules on DCLK1 kinase and rationalize their anti-GI cancer potential. Montelukast was also modeled, and its predicted DCLK1-binding profile was used to gain an insight on the present compounds' possible DCLK1 inhibition and consequently rationalize their anticancer potentials.
The DCLK1-montelukast complex (Figure 3) reveals the inhibitors appropriately fit to the binding cavity of DCLK1 KD as shown by a higher docking score in comparison to our bioactive molecules. This interaction was further reinforced by a higher MM-GBSA binding free energy showing its affinity to DCLK1 KD. This discovery further proves the interaction of DCLK1 with montelukast in curtailing tumor growth through DCLK1 inhibition.
The results in Table 3 show that the identified compounds exhibited an appreciable binding affinity for DCLK1-KD as evidenced by the binding scores from induced-fit docking (IFD). Moreover, the compounds' significantly higher glide emodel and MM-GBSA binding free energy (DG bind) of molecular hybrids as compared parent 8-HQ suggest that hybridization with 1,3,4oxadiazole moiety provided an enhanced affinity for DCLK1-KD and tight fitting into the active site cavity. This was further supported by the highest glide emodel and DG bind calculations of known inhibitor montelukast. Similarly, the DG bind of compound 4j corroborates its superior cytotoxicity against MIA PaCa-2 and HCT116 cell lines compared to 4l and 4m.
Analysis of the protein-ligand interactions in the DCLK1-KD complexes reveals that the 5-bromopentyl chain in compound 4j (Figure 3(a)) is imbedded deep into the ATP-binding site and stabilized by hydrophobic interactions with Val449, Met456, Glu466, Leu467, Val468 and Lys469 residues of the hinge region. These hydrophobic interactions further extended toward Gly532 and Asp533 residues of the DFG (aspartate-phenylalanine-glycine) motif. Compound 4j participated in hydrogen bond (H-b) interactions in the KD; the quinoline nitrogen acting as H-b acceptor for the backbone and tail amino units of Phe401 and invariant Lys419 in the catalytic loop, respectively. 41 The quinoline H-2 and H-4 atoms also formed aromatic H-b interactions with Glu436 and Asn516, respectively. The ligand's conformation in the KD was stabilized by favorable hydrophobic interactions with Gly532, Phe534, Glue535, Leu536 and the gatekeeper residue Met465. Additionally, the 5-bromo pentyl chain of compound 4j furnished hydrophobic interactions with the hinge region residues to reinforce the tight fitting in the active site. Thus, justifying its superior anticancer potency compared to compound 4l and 4m. These results agree with the DCLK1-montelukast complex where invariant Lys419 and Asp533 acted as H-b acceptors to the acid group of the inhibitor. The quinoline ring formed aromatic hydrogen bond with Val468 and another ring with Phe402. These interactions reveal the inhibitor's appropriate fit to the binding cavity of DCLK1 KD which was further reinforced by a highest DG bind. Moreover, these discoveries further prove the interaction of montelukast with DCLK1 in curtailing tumor growth inhibition.
Similarly, compound 4m is perfectly fitted in the ATP binding site to establish hydrophobic interactions of the benzyl ring with Met456, Glu466, Leu467, Val468 and Gly471 residues of the hinge region (Figure 3(b)). The ligand was reinforced with H-b interactions of quinoline and oxadiazole rings with Lys419 and aromatic H-b interaction of H-2 with Glu436 as in compound 4j. However, the pi-pi stacking interaction of pyridine core in compound 4m with Phe401 unlike compound 4j might be responsible for the poor DG bind and potency in consequential.
In compound 4l, the quinoline ring targeted the deep hydrophobic back pocket surrounded by Val449, Met465, Leu467, and Val468 wherein the benzyl ring formed aromatic H-b interaction with Asp533 (Figure 3(c)). The oxadiazole N-3 atom then participated in H-b interaction with Phe401 while the benzyl ring formed aromatic H-b interactions with Asp389 and Asn400. Notably, the binding affinity of compound 4l and consequently its potency is established by the ligand's orientation in the active site cavity. This might have induced an unfavorable conformation of the KD as a different side of the ligand approached the ATP binding site compared to the more potent compound 4j and 4 m. Although the small size of 8-HQ favored a deep fit into the ATP binding site to engage in H-b interactions with Val468 and Glu466 in the hinge region while the quinoline ring formed aromatic H-b with Asp533, the ligand's binding is unstable; hence, only few interactions were observed in the DCLK1-KD complex (Figure 3(d)).

Molecular dynamics simulation
The potency of compounds 8HQ, 4j, 4l and 4m and their predicted binding profiles toward DCLK1-KD propelled us to establish through molecular dynamics (MD) simulation, deeper insights to the compounds' stability in the active site cavity and protein structural changes during the binding events. Root mean square deviation (RMSD), which measures the differences between initial backbone structural conformation and the final position of the protein over time, was used to evaluate the variations in the binding patterns and complexes structural stability. Smaller deviations are associated with a more stable protein structure. 53 The RMSD of protein C-a in 4j-DCLK1-KD complex (Figure 4(a)) depicted relatively stable structural conformations for the entire 200 ns simulation, averaging at an RMSD of 2.5 Å. The ligand's stability at the KD however existed for the first 50 ns then increased fluctuations consistently occurred at approximately 50 ns intervals till the end of the simulation. Similarly, compound 4l complex protein showed fluctuations up to 75 ns then followed by stable conformations with an average RMSD of 2.2 Å. The ligand in this complex also showed unstable binding modes as depicted by fluctuations throughout the simulation. Compound 4m complex protein was harbored by fluctuations from the start to about 150 ns thereafter a form of stability was seen at an average RMSD of 2.7 Å. Also, ligand binding was unstable at the active site cavity as evidenced by fluctuations throughout the simulation. Compound 8HQ complex protein RMSD showed relatively stable conformations for the period of simulation converging at an average RMSD of 2.8 Å. However, the ligand was not stable upon binding as depicted by fluctuations throughout the simulation. The smaller size of 8HQ ligand did not induce perturbation on the active site cavity hence the protein conformation was not affected by its binding to the active site Figure 4. The observed fluctuations by proteins of 4j, 4l and 4m complexes are evidence of structural perturbation upon ligand binding which might affect the protein stable conformation.
Compounds 4j and 4m maintained water mediated hydrogen bonds with the backbone of invariant Lys419. Compound 4l hydrogen bond activity disappeared and hydrophobic interactions with Ile396, Val404 and Leu518 were visible. Compound 8HQ maintained hydrogen bonding with Val468 and hydrophobic interactions with Ile396, Ala417 and Leu518. All protein-ligand interactions lasted for about 20% of simulation period. Therefore, MD simulations were able to give a clear picture of binding mechanisms of each complex over time which explained poor binding scores, free binding energies from molecular docking and poor cytotoxicity with HCT116 and MIA PaCa2 cell lines.

Conclusion
A series of quinoline-2-mercapto 1,3,4-oxadiazoles were developed as anti-GI cancer entities. Compound 4j was established as a potent cytotoxic agent against MIA PaCa-2 and HCT116 with reduced toxicity to non-cancerous HDFa cells. SAR analysis and molecular modelling studies with DCLK1-KD cumulatively revealed the significance of 5-bromopentyl fragment to improved bioactivity profile. This study therefore established that further structural optimization hinging on the synthetic utility of the 5-bromopentyl unit for fragment-based drug design approach is valuable to afford new scaffolds with better anticancer efficacy.