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Drug repurposing of novel quinoline acetohydrazide derivatives as potent COX-2 inhibitors and anti-cancer agents
Accepted Manuscript Drug repurposing of novel quinoline acetohydrazide derivatives as potent COX-2 inhibitors and anti-cancer agents Chelli Sai Manohar, A. Manikandan, P. Sridhar, A. Sivakumar, B. Siva Kumar, Sabbasani Rajasekhara Reddy PII:
S0022-2860(17)31392-3
DOI:
10.1016/j.molstruc.2017.10.075
Reference:
MOLSTR 24446
To appear in:
Journal of Molecular Structure
Received Date: 7 June 2017 Revised Date:
13 October 2017
Accepted Date: 15 October 2017
Please cite this article as: C.S. Manohar, A. Manikandan, P. Sridhar, A. Sivakumar, B. Siva Kumar, S.R. Reddy, Drug repurposing of novel quinoline acetohydrazide derivatives as potent COX-2 inhibitors and anti-cancer agents, Journal of Molecular Structure (2017), doi: 10.1016/j.molstruc.2017.10.075. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Drug repurposing of Novel Quinoline Acetohydrazide derivatives as potent COX-2 inhibitors and anti-cancer agents Chelli Sai Manohara, Manikandan Ab, P. Sridharc, Sivakumar Ab, B. Siva Kumara and Sabbasani
Sri Sathya Sai Institute of Higher Learning, Prashanthi Nilayam. (A.P) India, - 51513.
b
c
Department of Biotechnology, School of Biosciences and Technology, VIT University, Vellore, India - 632014.
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a
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Rajasekhara Reddyc*
Department of Chemistry, School of Advanced sciences, VIT University, Vellore, India - 632014.
E-mail: [email protected]
Abstract
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*corresponding author
Novel QuinolineAcetohydrazide (QAh) derivatives (9a-n) were firstly evaluated in silico to
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determine their anti-inflammatory and anti-cancer efficacy via the mechanisms of COX1 and COX2 inhibition, and NF-ĸB, HDAC and Human Topoisomerase I pathways respectively. In the studied set, the trifluoro substituted QAh derivatives: (E)-N'-(4-(trifluoro methyl) benzylidene)2-(7-fluoro-2-methoxy
quinolin-8-yl)
acetohydrazid
and
(E)-N'-(3-(trifluoro
methyl)
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benzylidene)-2-(7-fluoro-2-methoxy quinolin-8-yl) acetohydrazide are determined to be potential leads, indicated from their best docked scores, relative ligand efficiency, and significant
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structural attributes evaluated by ab initio simulations. The only setback being their partition coefficient that retrieved a red flag in the evaluation of their Lipinski parameters. The experimental in vitro studies confirmed the significant enhancement as COX-2 inhibitors and appreciable enhancement in MTT assay of breast and skin cancer cell lines. Significantly, trifluoro substituent in the quinoline scaffold can be reasoned to note the excellent binding affinity to all the evaluated drug targets. Keywords: QuinolineAcetohydrazide; COX 2 inhibitors, Anti-inflammatory agents; Anti-cancer agents; Drug Design; Molecular Docking study; Lipinski parameter.
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Introduction Recent genomics of various microorganisms accrue their drug resistance to prolonged exposure to antimicrobials and antibiotics,[1] demanding effective design and synthesis of novel molecules.[2] To match up to this ever increasing demand, an economic strategy
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involves the drug repurposing of established/synthesised drugs for multi-functional potency. [3] Quinoline derivatives are popular wide-spectrum drugs [1,2,4–8] with the azomethine functionality accounting for observed pharmacological and biological activities.[9–12] The ease of hydrolysis in hydrazide-hydrazone functionalities within
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biological systems as determined from in vitro studies of metabolism becomes an advantage in treating various life threatening diseases.[13,14].
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Given the group’s forte of evaluating N-N bond bearing therapeutics, the present study was aimed at Quinolineacetohydrazide derivatives (9a-n) with a fluorine and a methoxy substituent in the quinoline nucleus and alkoxy, OCF3 and fluorine functionality on the phenyl moiety. While their in vitro antibacterial and DNA gyrase inhibition was previously determined, [15] we explored their drug repurposing in this study to maximize their benefit. In this regard, we evaluated their anti-inflammatory and anti-cancer
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potential. COX-1 and COX-2 that play a significant role in conversion of arachidonic acid to prostaglandins [16,17] are key to various pathophysiological processes like inflammatory responses, carcinogenesis and cardiovascular events.
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Further, notable cancer pathways include the Topoisomerase inhibition, [18] Glucocorticoid-responsive cancers characterized by a constitutive NF-κB activity[19] and
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HDAC inhibition that leads to significant anti-tumor activity via the enhancement of the histone acetylation level, inducing cell cycle arrest, differentiation and apoptosis. [20] Hence, given the prior review of the potential of quinolone derivatives in these roles, [12,21–24] we evaluate the COX-1, COX-2, NF-κB, HDAC and Topo-I inhibition, exploring the in silico binding affinities of our synthesised QAH derivatives and confirming the notable findings with in vitro assays. Lastly, the drug likeness of these derivatives namely their Lipinski parameters helped evaluate them as potential leads.
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Quinoline-acetohydrazide-hydrazone derivatives The following schematic provides the undertaken synthetic route to prepare (E)-N'-(substitutedbenzylidene) -2-(7-fluoro -2-methoxy quinolin-8-yl) aceto hydrazide–hydrazone derivatives 9a-n (Scheme 1) which was reported earlier. [14] The compounds were preserved by avoiding
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contaminations and stored under 4oC.
Scheme 1. Synthesis of novel Quinoline acetohydrazide derivatives 9a-n
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Experimental Conditions: a) Cinnamoyl chloride, aq. NaHCO3, isopropyl acetate, RT, 30 min; b) AlCl3, chlorobenzene, 90oC, 1h; c) MeI, KtOBu, DMSO, 70oC, 2.5h; d) NBS, benzoyl peroxide, xylene, 70oC, 1.5h; e) KCN, DMF, 60oC, 16h; f) TMSiCl, MeOH,
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70oC, 2.5h; g) NH2-NH2, ethanol, reflux, 20h; h) Benzaldehydes, a-n, ethanol, reflux, 4 h
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Materials and Methods
Molecular docking
The receptors were obtained from the protein data bank and suitably cleaned for their solvent and heteroatoms in MOE. Molecular docking studies were consequently undertaken using PyRx autodock Vina using the active site in the protein determined by the pre-existing ligand. [25] The ligand structures of the compounds 9a-n were drawn using Chemdraw ultra 10.0 version of Cambridge University. The 3D atomic coordinates were optimized to the least energy conformation using the ab intio DFT calculations using Gaussian 03. [26] The derivatives were eventually engendered as the corresponding pdb files for the consequent docking study.
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HRBC membrane protection investigations The Human Red Blood Cell (HRBC) membrane stabilization study was carried out by using
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indomethacin as the standard. The percentage haemolysis was calculated by assuming the haemolysis produced in presence of distilled water at 100%. The percentage of HRBC membrane stabilization was calculated using the following formula,
% inhibition of haemolysis = 100 x [(OD1-OD2) /OD1]
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Where; OD2 = optical density of sample, and OD1 = optical density of control.
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COX-2 enzyme assay
COX-2 Inhibitor Screening Kit (Fluorometric) from Biovision Pvt. Ltd (Catalog No.: K547-100) was used for the COX-2 inhibition assay studies. Protocols were followed as per the manufacturer’s instructions. The assay mixture was pre-incubated at 22°C for 1 min along with the test compounds. Other than the test compounds, the assay mixture included EDTA (3 mM), haematin (15 mM), Tris–HCl buffer (100 mM, pH 8.0), and COX-2 enzyme (100 mg).
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Arachidonic acid and TMPD were added together to a 1 ml total volume. The rate of TMPD oxidation in 20 seconds was measured as the enzyme activity at 602 nm absorbance. Cell lines preparation for assay
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The proposed cancer cell lines used in this study were cultured in DMEM (Dulbecco’s Modified Eagle’s Medium) supplemented with 10% Fetal Bovine Serum (FBS), (100U) 20
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µg/ml penicillin, and 100 µg/ml streptomycin. They were sub-cultured by removing existing medium and adding fresh 0.25% trypsin 0.53 mM EDTA for several minutes. Thereafter, the trypsin was removed and the culture was incubated at 37°C for 10 to 15 minutes. Fresh medium was added, aspirated and dispensed into new flasks that were incubated at 37°C in an atmosphere of 5% CO2. For the assay, 1 ml of homogenized cell suspension was poured in each well of microtitre plate and kept in desiccator. After 48 hours of incubation, the cells were observed in inverted microscope. 0.05 ml of drug was dissolved in 4.95 ml of DMSO to get a working concentration of 1 mg/ml. The working concentration was prepared freshly and filtered through 0.45 micron filter before bioassay.
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MTT assay for anti-proliferation/cancer evaluations The anticancer activity of Quinoline Acetohydrazide (QAh) derivatives 9a-n on human breast cancer (MCF-7) and skin cancer (G-361) cell lines was determined by the MTT (3-(4, 5-
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dimethylthiazol-2yl)-2,5-diphenyl tetrazolium bromide) assay. Doxorubicin (DOX) was used as the standard drug in this study since it is generally used in the treatment as an anti-cancer agent [24] Approximately 5000 cells were seeded in 96-well, flat-bottom titer plates and incubated for 24, 48, and 72 hours at 37oC in 5% CO2 atmosphere. Different concentrations of PQPDs (4a-l) (50 – 500 µg/mL) were added and incubated further for various time periods. After completion
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of incubation, the medium was removed. The wells were rinsed with with PBS and 100 µL of the working MTT dye in DMEM (Dulbecco's Modified Eagle's Medium) media was added and
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incubated for 2 hours. MTT lysis buffer (100 µL) was added and incubated for another 4 hrs. The absorbance was measured at 570 nm and the cell viability was calculated using the following farmula: Cell viability (%) = Mean OD/Control OD x 100%
Results and Discussion
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Molecular Docking Studies
The ligands were ab initio DFT optimized using Gaussian 03 [25] and the least energy pose was docked into the 3D structures of COX1 (PDB ID: 3N8Y),[27] COX2 (PDB ID:3LN1),[28]
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Human Topoisomerase I (PDB ID: 1T8I), NF-ĸB protein (PDB ID: 2V2T),[29] and HDAC2 (PDB ID: 4LXZ) [30] receptors retrieved from the protein data bank (Source: www.rcsb.org/pdb/). These proteins were first suitably prepared by cleansing them of their
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solvent, heteroatoms and existing crystallographic ligand in the co-crystal complex. The docking study was then carried out in the active site using PyRx Autodock-Vina which is a simple and effective tool.[25] The typical binding pocket and interactions observed are captured in Fig. 1 for the potent derivatives (9k and 9l) in their best docked poses. Further, the standard deviation shows that the molecules assume similar interactions in the case of cancer mechanisms (~0.3) while they possess relatively deviant mechanistic potential (~0.6) in the case of antiinflammatory activities. The various interactions of the best poses of the ligand with the protein are consequently obtained using pymol as tabulated (Table 2).
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Figure 1. The binding interactions of the least energy docked poses: (a) 9k with the COX2 inhibitor, (b) 9l with the COX2 inhibitor (PDB ID: 3LN1), (c) 9k with Human topoisomerase I
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and (d) 9l with Human topoisomerase I (PDB ID: 1T8I) captured by PyMol
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Table1. Binding affinity of the derivatives as obtained from the docked poses using Autodock-Vina QAhn COX1 COX2 Topo I NF-ĸB HDAC2 Avg. BA Active Binding Sites COX2) Asn361, Leu210 9h -7.8 -8.3 -7.2 -6.6 -8.1 -7.6 Tyr108 9d -8.8 -8.1 -7.2 -6.5 -8 -7.72 Gly121, Tyr116 9a -8.3 -9 -7.5 -6.9 -7.6 -7.86 Asn 361 9g -8 -9.5 -7.3 -6.9 -7.8 -7.9 9i -8.9 -8.5 -7.4 -6.9 -7.9 -7.92 Gly 121 (2) 9f -8.8 -8.8 -7.2 -6.9 -7.9 -7.92 Cys 21, Cys 32 9c -8.4 -9.4 -7.2 -6.6 -8.1 -7.94 Gly 121, Leu 201, Ser 129 9b -8.1 -9.3 -7.5 -7.1 -8.1 -8.02 9m -8.7 -8.6 -7.8 -7 -8.2 -8.06 Asn 24 9e -9 -9.5 -7.3 -6.8 -7.9 -8.1 Tyr116, Asn24, Gln447, Ala142 9j -9.4 -9.4 -7.6 -7.1 -8.4 -8.38 9n -9.3 -9.3 -7.6 -7 -8.7 -8.38 Ser 34 9k -9.7 -9.3 -7.8 -7.4 -8.1 -8.46 Gly 121 (2), Tyr 116 9l -9.3 -10.2 -8.1 -7.3 -8.8 -8.74 Gly 121 Avg. -8.4 -8.8 -7.4 -6.8 -7.9 -7.88 NA Sd 0.6 0.6 0.3 0.3 0.3 0.31 NA Ref 1* -8.1 -10.6 -9.3 -6.8 -8.9 -8.74 NA Ref 2* -7.5 -8.2 -8.6 -6.8 -8.3 -7.88 NA Saha -5.9 -6.4 -6.8 -5.4 -6.1 -6.12 NA *Ref 1: Daunorubicin, *Ref 2: Dexamethasone; NA – Not Applicable
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The hydrogen bonds and non-covalent bonds (π-π interaction and π-cation interactions) were considered for the ligand-receptor interactions. The binding affinities (ascending order) noted for the best docked poses with least RMSD are significant as the interaction energies exhibited an average of -7.88 for the whole data set across the studied inhibitions. Clearly the chief active site
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residues in the COX2 protein are the Gly121, Tyr116 and Asn361 residues with other active groups being Serine, Cys, Ala and Gln where the hydrogen bond is formed through the NH of the hydrazide and N of the Quinoline ring. However, in the key derivatives of interest 9k and 9l that exhibit the maximum binding affinity, it’s the OCH3 in the Quinoline ring that takes part in
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the binding. We can see that while mostly it is this hydrogen bonding driving the interaction, there’s also van der waals interactions - non-covalent bonds - like in 9b and 9j with very good
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binding affinity. We can rationalize that the presence of the electron pumping group in -OCH3 present in 9a-9e in general leads to the lesser binding affinity relatively, given that they pump the electron cloud into the N on the NH in the hydrazide group involved in the interaction, reducing the availability of H for bonding with the protein. As observed, in fact, in some cases, even this group itself becomes the acceptor to a relevant donor in the active site of the protein. Consequently, the presence of the electron withdrawing -CF3 group in 9k and 9l explains the
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increased binding affinity, especially in 9k where the NH forms a 1.9A0 bond to the Gly 121 residue given that the group leaves the electron cloud on H intact for more interaction.
The above results thus indicated the potential of these derivatives to pursue the corresponding
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mechanisms to result in the respective medicinal property. However, the docking scores suggest that these set of derivatives in general could act as better anti-inflammatory agents as compared
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to anti-cancer agents. Specifically, the COX2 inhibitors retrieve the best poses as against the COX1 inhibition with the highest average binding potential. The inhibition binding with respect to NF-ĸB falls short even though its promise is established when compared to the reference drugs dexamethasone.[29] Further, these QAh exhibited significant HDAC inhibition as against their tubulin interaction. Thus, the wide mechanistic role of these derivatives demonstrates their potential as anti-cancer agents as when compared to the reference drug Daunorubicin [29] and Saha. [30] The study infers the significant derivatives that could be explored as potential leads in 9k and 9l with the highest binding affinities observed which are better even than corresponding reference ligands. The presence of the tri-fluorocarbon group substitution can be considered as a
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major factor that influences the azomethine moiety that primarily takes part in the binding interactions with the active residues in the enzymes. To examine the structural features of these synthesised derivatives, we undertook their conformational study using the Gaussian 03
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program. [26] Computational Studies
In this computational study, the ab intio DFT calculations were performed using Becke’s three parameter exchange functional in combination with the Lee–Yang–Parr correlation functional
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(B3LYP) and standard 6-311G(d,p) basis set in the Gaussian 03 program [26] to obtain the optimized conformation generated by energy minimization with respect to all geometrical
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parameters. Consequently, we also determined the MO picture, hyperpolarizability and chemical reactivity for each of these species optimized by the DFT method. The Fig. 2 captures the optimized conformers of potent derivatives of interest (9k and 9l) in the study. Given the Koopman’s theorem,[31] the global chemical reactivity descriptors (GCRD), based on the conceptual DFT that defines molecular structure stability and reactivity were studied. [32] For these are also employed in the progress of quantitative structure activity (QSAR), structure-
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property (QSPR), and structure- toxicity (QSTR) relationships.
Figure 2. MO diagrams of the least energy conformations of the DFT level G03 optimized least energy conformations of 9k and 9l derivatives
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In this study, our focus was to find the values of various GCRD parameters such as chemical hardness (η),[33–35] chemical potential (µ), softness (S), electronegativity (χ) and the electrophilicity index (ω) of the QAh derivatives from their HOMO and LUMO energies values using different functional as tabulated (Table 2). Most importantly, the species with the most
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chemical reactivity also happen to exhibit the best medicinal efficacy, providing a plausible attribute, key to the design of these class of drugs. Perhaps, their reactivity is a consequence of their MO energy gap driving their interaction with the active site eventually.
Hardness Softness Potential EN (η) (S) (µ) (χ) 0.06202 0.00621 -0.13834 0.17650 0.06147 0.00597 -0.13283 0.16851 0.06314 0.00626 -0.13529 0.17136 0.06419 0.00634 -0.13326 0.16779 0.05940 0.005734 -0.13367 0.17080 0.06373 0.00642 -0.13779 0.17483 0.07244 0.00806 -0.15001 0.18879 0.05919 0.00569 -0.13328 0.17033 0.06002 0.00581 -0.13372 0.17057 0.07571 0.00835 -0.14495 0.17957 0.07236 0.00812 -0.15201 0.19184 0.07356 0.00838 -0.15438 0.19479 0.07366 0.00836 -0.15320 0.19297 0.07117 0.00782 -0.14867 0.18742
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EHOMO (au) -0.2004 -0.1943 -0.1984 -0.1975 -0.1931 -0.2015 -0.2225 -0.1925 -0.1937 -0.2207 -0.2244 -0.2279 -0.2269 -0.2198
GEI (ω) 0.15429 0.14352 0.14494 0.13830 0.15040 0.14898 0.15532 0.15006 0.14896 0.13875 0.15967 0.16199 0.15931 0.15528
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9a 9b 9c 9d 9e 9f 9g 9h 9i 9j 9k 9l 9m 9n
ELUMO (au) -0.0763 -0.0714 -0.0722 -0.0691 -0.0743 -0.0741 -0.0776 -0.0741 -0.0737 -0.0692 -0.0797 -0.0808 -0.0795 -0.0775
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QAha
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Table 2. Chemical reactivity of the QAH derivatives calculated theoretically from the G03 studies
Non Linear Optics
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New frequency conversion materials based on organic NLO materials with high nonlinear susceptibilities have been discovered but their application has been hindered in practical device applications owing to inadequate transparency, poor optical quality and low laser damage threshold. [36]
In this regard, we observe that our studied set of derivatives (Table 3)
demonstrate significant NLO potential as when compared to the standard reference of Urea. The calculated first hyper polarizability (SHG) of the QAH derivatives are on an average around 18 times more than that of the standard NLO material urea (0.13×10-30 esu) [37]. This can be attributed to the electron pumping and withdrawing nature of the substituents and their positions
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which is clear in the high SHG and 3rd order Hyperpolarizability for 9k and 9l given the good electron withdrawing group (p-CF3) at the para position. We therefore conclude that these derivatives could be explored as attractive molecules for nonlinear optical properties with respect
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to both their SHG parameters and 3rd order Hyperpolarizability. Table 3. Dipole moment ‘µ’, polarizability αtot (×10-24 esu) and first order static hyper polarizability βtot (×10-30esu) and third order hyper polarizability (×10−36 esu) data for QAH derivatives using DFT theory
1.372 a
17.08733 183.18657 220.44898 138.99893 118.24639 191.76005 279.31362 124.74487 127.66726 323.27514 9.27642 60.31177 190.51739 32.39189
13.80223 10.98813 10.37671 9.76634 11.92301 9.88300 10.92604 13.74135 15.66986 11.03326 14.27444 13.26674 11.72014 9.562501
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Mean First Order Hyper polarizability
Mean Polarizabili ty* (αtot)
2.35648 2.14033 3.12538 2.03715 1.68149 2.07507 3.21909 1.96250 1.50096 3.07379 2.36176 2.77183 1.59482 1.98186
24.9777 22.334 22.0644 22.2432 22.8856 21.0321 21.9329 23.7003 24.3379 20.2629 24.5449 24.0722 23.867 21.8535
0.13
-
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Third order Hyper polarizability*
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Anisotropy of Polarizability
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9a 9b 9c 9d 9e 9f 9g 9h 9i 9j 9k 9l 9m 9n Urea (Ref.)
Static Dipole Moment (µ) 9.7716 8.8624 9.9781 8.7239 8.924 10.1357 9.4991 8.9597 8.9905 7.0599 1.2233 10.7589 7.9311 8.5638
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*negative values
In Vitro Studies
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QAh
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Finally, given the inference from the docking studies that indicated the significant potential of
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this class of derivatives for their anti-inflammatory activity, we undertook the in vitro studies via the COX2 enzyme inhibition assay (Table 4). We notice that 9k (IC50 0.13 µM) and 9l (IC50 0.14 µM) as predicted from the docking scores returned significant values of inhibition that’s even better that the standard (IC50 0.38 µM) (Fig. 3). Further, 9h also serves as an interesting derivative to be considered. Also, the in-vitro anti-inflammatory activity was carried out by Human Red Blood Cell (HRBC) membrane stabilization method using indomethacin as standard. The compounds 9k and 9l exhibited an excellent % membrane protection. Even though the indomethacin (standard) showed an IC50 of 0.08 µg/mL with % protection 82.22, the significant
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derivatives 9k (0.098 µg/mL, 76.21) and 9l (0.092 µg/mL, 78.43) also established a remarkable activity.
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Table 4. Results of COX2 enzyme inhibition of 9a-l Entity Ligand efficiency % inhibition IC50 (µM)** 9a -0.044 32.92 7.12 µM 9b -0.040 30.32 6.88 µM 9c -0.003 64.01 0.85 µM 9d 0.011 70.38 0.58 µM 9e Not Inhibited 9f 0.001 52.36 0.98 µM 9g 0.009 58.01 0.62 µM 9h 0.027 72.42 0.25 µM 9i -0.014 53.16 1.87 µM 9j Not Inhibited 9k 0.042 80.82 0.13 µM 9l 0.041 80.98 0.14 µM 9m 0.006 68.24 0.75 µM 9n -0.037 35.21 5.21 µM Std* 0.022 79.46 0.38µM *Celecoxib, ** All IC50 values are the mean of duplicate/triplicate measurements.
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Figure 3. Inhibition of COX2 with compound 9k and 9l
Ligand efficiency (LE)
This factor measures the binding energy per atom of a ligand to receptor or enzyme. [38] This is an important feature for it assists at an early stage in the filtering of the potential leads possessing optimal combination of physicochemical and pharmacological properties. [39] Mathematically, it can thus be defined as the ratio of Gibbs free energy (∆G) to the number of non-hydrogen atoms of the compound as determinable in the equation: [40] LE = 1.4(-logIC50)/N
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In the evaluation of the LE for our set of prepared derivatives, as tabulated (Table 4) we interestingly note that the ligand efficiency is also maximum with respect to the established most active molecules. Further, more significantly, the efficiency also happens to be more than the
Anticancer determinations by MTT assay
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standard reference celecoxib, almost doubling from 0.022 to 0.041 and 0.042.
The human breast cancer (MCF-7) and skin cancer (G-361) cell lines were incubated with different doses (10 to 150 µg/ml) of QAh to evaluate the anticancer activity. Cells were seeded at
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a density of 1×104 cells/well in a 96-well plate and grown for another 24 hours. After 24 hours of incubation, cell viability was determined by the MTT assay and the inhibitory percentage were calculated. QAh 9a-n was able to inhibit the proliferation of the cancer cells. IC50 values indicate
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that some of the tested QAh were as active as the standard drug Doxorubicin (IC50 2.444 µM), the standard (Fig. 4). QAh 9h (2.416 µM), 9k (2.071 µM) and 9l (2.224 µM) were found with
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excellent activity and results were considerably similar/more with Doxorubicin.
Figure 4. Anticancer activity results of doxorubicin and (clockwise) 9h, 9i and 9k at various concentrations.
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Lipinski’s filter
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A typical strategy during drug discovery is to optimize step-wise to increase efficiency vis-a-vis the activity and selectivity while ensuring the conformity of the drug-like physicochemical properties described by Lipinski's rule. [41] For, the Lipinski's rule of five (R05) serves as a popular and significant thumb’s rule in the evaluation of drug likeness in determination of the
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molecule’s potential as an orally active drug with respect to its pharmacological or biological activity. The rule covers important molecular properties in the drug's pharmacokinetics like ADME but fails to predict if a compound is pharmacologically active. A conformity to the R05 S+logP 3.705 3.577 3.363 3.511 3.471 3.838 4.293 3.32 3.954 4.119 4.576 4.514 4.093 4.104
S+logD 3.705 3.577 3.363 3.511 3.471 3.838 4.293 3.32 3.954 4.119 4.576 4.514 4.093 4.104
R05 0 0 0 0 0 0 0 0 0 0 1 1 0 0
R05_Code LP LP
MWt (da) 339.372 369.398 369.398 369.398 369.398 383.425 397.452 399.425 327.336 393.343 377.344 377.344 345.326 345.326
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MlogP 3.08 2.534 2.534 2.534 2.534 2.754 2.971 1.995 3.754 3.417 4.204 4.204 3.868 3.868
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QAh 9a 9b 9c 9d 9e 9f 9g 9h 9i 9j 9k 9l 9m 9n
M_NO 5 6 6 6 6 6 6 7 4 5 4 4 4 4
T_PSA 55.74 64.97 64.97 64.97 64.97 64.97 64.97 74.2 46.51 55.74 46.51 46.51 46.51 46.51
HBDH 1 1 1 1 1 1 1 1 1 1 1 1 1 1
provides more promise to the candidate drug for eventual success during clinical trials and
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consequently greater chance of reaching the market. [42,43]
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Table 4. Determination of the Lipinski filters in the evaluation of the drug-likeness of the derivatives Some of the standard markers evaluated in this regard are as follows: • S+logP - logP calculated using Simulations Plus’ highly accurate internal model. • S+logD - logD at user-specified pH (default 7.4), based on S+logP. • MlogP - Moriguchi estimation of logP. • HBDH - Number of Hydrogen bond donor protons. • M_NO - Total number of Nitrogen and Oxygen atoms. • T_PSA - Topological polar surface area in square angstroms. • RuleOf5 - Lipinski’s Rule of Five: a score indicating the number of potential problems a structure might have with passive oral absorption.
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•
RuleOf5_Code - Lipinski’s Rule of Five codes: LP = logP; Hb = number of Hydrogen bond donor protons; Mw = molecular weight; NO = number of Nitrogen- and Oxygenbased Hydrogen bond acceptors.
In the established values (Table 4) for the various Lipinski parameters, the presence of a code in
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R05_Code infers the violation of the corresponding Lipinski rule. Here, we notice that the two derivatives of preferred 9k and 9l violate the Lipinski rules with respect to their partition coefficient (Log P not greater than 3). This, therefore, serves as a red flag in the in silico evaluation of their role as potential multi-functional therapeutic leads. However, this could be addressed
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either with the kind of formulation in the eventual design, or even otherwise serve as a wonderful starting point to explore the specific groups (SAR) that serves as a key to a particular biological
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activity – in this specific case being – the trifluoro substituent.
Conclusion
An extensive theoretical study of the structure, reactivity and NLO attributes of novel quinoline-acetohydrazide-hydrazone derivatives was undertaken. Further, their molecular docking studies were evaluated to explore their drug repurposing. The entire data set
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demonstrated significant in silico anti-cancer and anti-inflammatory activity potential against a wide spectrum of notable mechanisms. In specific, the derivatives with trifluoro substituent in the quinoline scaffold showed excellent binding that was attributed to their withdrawing effect on the interacting donor group in the ligand. Their appreciable in
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silico binding affinities comparable to the prescribed standard reference drugs suggested their role as potential inflammation and cancer therapeutics that was consequently
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confirmed in vitro. The docking study helped rationalize the mechanism by providing the ideal docked poses of the least energy conformations of the drug ligands in the interacting active sites amino residues in the protein. While the Lipinski parameters noted a set back with respect to the partition coefficient, the ligand efficiency and NLO potential of 9k and 9l derivatives prove them to be promising leads given their 3 fold enhancement in their COX2 inhibiting potential with respect to the reference drug Celecoxib.
Acknowledgements
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We are grateful to Sathya Sai Baba, the founder chancellor, SSSIHL for his constant guidance and inspiration. We are also indebted to the administration of SSSIHL and the department of
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S0022-2860(17)31392-3
DOI:
10.1016/j.molstruc.2017.10.075
Reference:
MOLSTR 24446
To appear in:
Journal of Molecular Structure
Received Date: 7 June 2017 Revised Date:
13 October 2017
Accepted Date: 15 October 2017
Please cite this article as: C.S. Manohar, A. Manikandan, P. Sridhar, A. Sivakumar, B. Siva Kumar, S.R. Reddy, Drug repurposing of novel quinoline acetohydrazide derivatives as potent COX-2 inhibitors and anti-cancer agents, Journal of Molecular Structure (2017), doi: 10.1016/j.molstruc.2017.10.075. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Drug repurposing of Novel Quinoline Acetohydrazide derivatives as potent COX-2 inhibitors and anti-cancer agents Chelli Sai Manohara, Manikandan Ab, P. Sridharc, Sivakumar Ab, B. Siva Kumara and Sabbasani
Sri Sathya Sai Institute of Higher Learning, Prashanthi Nilayam. (A.P) India, - 51513.
b
c
Department of Biotechnology, School of Biosciences and Technology, VIT University, Vellore, India - 632014.
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Rajasekhara Reddyc*
Department of Chemistry, School of Advanced sciences, VIT University, Vellore, India - 632014.
E-mail: [email protected]
Abstract
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*corresponding author
Novel QuinolineAcetohydrazide (QAh) derivatives (9a-n) were firstly evaluated in silico to
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determine their anti-inflammatory and anti-cancer efficacy via the mechanisms of COX1 and COX2 inhibition, and NF-ĸB, HDAC and Human Topoisomerase I pathways respectively. In the studied set, the trifluoro substituted QAh derivatives: (E)-N'-(4-(trifluoro methyl) benzylidene)2-(7-fluoro-2-methoxy
quinolin-8-yl)
acetohydrazid
and
(E)-N'-(3-(trifluoro
methyl)
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benzylidene)-2-(7-fluoro-2-methoxy quinolin-8-yl) acetohydrazide are determined to be potential leads, indicated from their best docked scores, relative ligand efficiency, and significant
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structural attributes evaluated by ab initio simulations. The only setback being their partition coefficient that retrieved a red flag in the evaluation of their Lipinski parameters. The experimental in vitro studies confirmed the significant enhancement as COX-2 inhibitors and appreciable enhancement in MTT assay of breast and skin cancer cell lines. Significantly, trifluoro substituent in the quinoline scaffold can be reasoned to note the excellent binding affinity to all the evaluated drug targets. Keywords: QuinolineAcetohydrazide; COX 2 inhibitors, Anti-inflammatory agents; Anti-cancer agents; Drug Design; Molecular Docking study; Lipinski parameter.
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Introduction Recent genomics of various microorganisms accrue their drug resistance to prolonged exposure to antimicrobials and antibiotics,[1] demanding effective design and synthesis of novel molecules.[2] To match up to this ever increasing demand, an economic strategy
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involves the drug repurposing of established/synthesised drugs for multi-functional potency. [3] Quinoline derivatives are popular wide-spectrum drugs [1,2,4–8] with the azomethine functionality accounting for observed pharmacological and biological activities.[9–12] The ease of hydrolysis in hydrazide-hydrazone functionalities within
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biological systems as determined from in vitro studies of metabolism becomes an advantage in treating various life threatening diseases.[13,14].
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Given the group’s forte of evaluating N-N bond bearing therapeutics, the present study was aimed at Quinolineacetohydrazide derivatives (9a-n) with a fluorine and a methoxy substituent in the quinoline nucleus and alkoxy, OCF3 and fluorine functionality on the phenyl moiety. While their in vitro antibacterial and DNA gyrase inhibition was previously determined, [15] we explored their drug repurposing in this study to maximize their benefit. In this regard, we evaluated their anti-inflammatory and anti-cancer
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potential. COX-1 and COX-2 that play a significant role in conversion of arachidonic acid to prostaglandins [16,17] are key to various pathophysiological processes like inflammatory responses, carcinogenesis and cardiovascular events.
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Further, notable cancer pathways include the Topoisomerase inhibition, [18] Glucocorticoid-responsive cancers characterized by a constitutive NF-κB activity[19] and
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HDAC inhibition that leads to significant anti-tumor activity via the enhancement of the histone acetylation level, inducing cell cycle arrest, differentiation and apoptosis. [20] Hence, given the prior review of the potential of quinolone derivatives in these roles, [12,21–24] we evaluate the COX-1, COX-2, NF-κB, HDAC and Topo-I inhibition, exploring the in silico binding affinities of our synthesised QAH derivatives and confirming the notable findings with in vitro assays. Lastly, the drug likeness of these derivatives namely their Lipinski parameters helped evaluate them as potential leads.
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Quinoline-acetohydrazide-hydrazone derivatives The following schematic provides the undertaken synthetic route to prepare (E)-N'-(substitutedbenzylidene) -2-(7-fluoro -2-methoxy quinolin-8-yl) aceto hydrazide–hydrazone derivatives 9a-n (Scheme 1) which was reported earlier. [14] The compounds were preserved by avoiding
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contaminations and stored under 4oC.
Scheme 1. Synthesis of novel Quinoline acetohydrazide derivatives 9a-n
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Experimental Conditions: a) Cinnamoyl chloride, aq. NaHCO3, isopropyl acetate, RT, 30 min; b) AlCl3, chlorobenzene, 90oC, 1h; c) MeI, KtOBu, DMSO, 70oC, 2.5h; d) NBS, benzoyl peroxide, xylene, 70oC, 1.5h; e) KCN, DMF, 60oC, 16h; f) TMSiCl, MeOH,
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70oC, 2.5h; g) NH2-NH2, ethanol, reflux, 20h; h) Benzaldehydes, a-n, ethanol, reflux, 4 h
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Materials and Methods
Molecular docking
The receptors were obtained from the protein data bank and suitably cleaned for their solvent and heteroatoms in MOE. Molecular docking studies were consequently undertaken using PyRx autodock Vina using the active site in the protein determined by the pre-existing ligand. [25] The ligand structures of the compounds 9a-n were drawn using Chemdraw ultra 10.0 version of Cambridge University. The 3D atomic coordinates were optimized to the least energy conformation using the ab intio DFT calculations using Gaussian 03. [26] The derivatives were eventually engendered as the corresponding pdb files for the consequent docking study.
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HRBC membrane protection investigations The Human Red Blood Cell (HRBC) membrane stabilization study was carried out by using
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indomethacin as the standard. The percentage haemolysis was calculated by assuming the haemolysis produced in presence of distilled water at 100%. The percentage of HRBC membrane stabilization was calculated using the following formula,
% inhibition of haemolysis = 100 x [(OD1-OD2) /OD1]
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Where; OD2 = optical density of sample, and OD1 = optical density of control.
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COX-2 enzyme assay
COX-2 Inhibitor Screening Kit (Fluorometric) from Biovision Pvt. Ltd (Catalog No.: K547-100) was used for the COX-2 inhibition assay studies. Protocols were followed as per the manufacturer’s instructions. The assay mixture was pre-incubated at 22°C for 1 min along with the test compounds. Other than the test compounds, the assay mixture included EDTA (3 mM), haematin (15 mM), Tris–HCl buffer (100 mM, pH 8.0), and COX-2 enzyme (100 mg).
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Arachidonic acid and TMPD were added together to a 1 ml total volume. The rate of TMPD oxidation in 20 seconds was measured as the enzyme activity at 602 nm absorbance. Cell lines preparation for assay
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The proposed cancer cell lines used in this study were cultured in DMEM (Dulbecco’s Modified Eagle’s Medium) supplemented with 10% Fetal Bovine Serum (FBS), (100U) 20
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µg/ml penicillin, and 100 µg/ml streptomycin. They were sub-cultured by removing existing medium and adding fresh 0.25% trypsin 0.53 mM EDTA for several minutes. Thereafter, the trypsin was removed and the culture was incubated at 37°C for 10 to 15 minutes. Fresh medium was added, aspirated and dispensed into new flasks that were incubated at 37°C in an atmosphere of 5% CO2. For the assay, 1 ml of homogenized cell suspension was poured in each well of microtitre plate and kept in desiccator. After 48 hours of incubation, the cells were observed in inverted microscope. 0.05 ml of drug was dissolved in 4.95 ml of DMSO to get a working concentration of 1 mg/ml. The working concentration was prepared freshly and filtered through 0.45 micron filter before bioassay.
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MTT assay for anti-proliferation/cancer evaluations The anticancer activity of Quinoline Acetohydrazide (QAh) derivatives 9a-n on human breast cancer (MCF-7) and skin cancer (G-361) cell lines was determined by the MTT (3-(4, 5-
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dimethylthiazol-2yl)-2,5-diphenyl tetrazolium bromide) assay. Doxorubicin (DOX) was used as the standard drug in this study since it is generally used in the treatment as an anti-cancer agent [24] Approximately 5000 cells were seeded in 96-well, flat-bottom titer plates and incubated for 24, 48, and 72 hours at 37oC in 5% CO2 atmosphere. Different concentrations of PQPDs (4a-l) (50 – 500 µg/mL) were added and incubated further for various time periods. After completion
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of incubation, the medium was removed. The wells were rinsed with with PBS and 100 µL of the working MTT dye in DMEM (Dulbecco's Modified Eagle's Medium) media was added and
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incubated for 2 hours. MTT lysis buffer (100 µL) was added and incubated for another 4 hrs. The absorbance was measured at 570 nm and the cell viability was calculated using the following farmula: Cell viability (%) = Mean OD/Control OD x 100%
Results and Discussion
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Molecular Docking Studies
The ligands were ab initio DFT optimized using Gaussian 03 [25] and the least energy pose was docked into the 3D structures of COX1 (PDB ID: 3N8Y),[27] COX2 (PDB ID:3LN1),[28]
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Human Topoisomerase I (PDB ID: 1T8I), NF-ĸB protein (PDB ID: 2V2T),[29] and HDAC2 (PDB ID: 4LXZ) [30] receptors retrieved from the protein data bank (Source: www.rcsb.org/pdb/). These proteins were first suitably prepared by cleansing them of their
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solvent, heteroatoms and existing crystallographic ligand in the co-crystal complex. The docking study was then carried out in the active site using PyRx Autodock-Vina which is a simple and effective tool.[25] The typical binding pocket and interactions observed are captured in Fig. 1 for the potent derivatives (9k and 9l) in their best docked poses. Further, the standard deviation shows that the molecules assume similar interactions in the case of cancer mechanisms (~0.3) while they possess relatively deviant mechanistic potential (~0.6) in the case of antiinflammatory activities. The various interactions of the best poses of the ligand with the protein are consequently obtained using pymol as tabulated (Table 2).
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Figure 1. The binding interactions of the least energy docked poses: (a) 9k with the COX2 inhibitor, (b) 9l with the COX2 inhibitor (PDB ID: 3LN1), (c) 9k with Human topoisomerase I
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and (d) 9l with Human topoisomerase I (PDB ID: 1T8I) captured by PyMol
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Table1. Binding affinity of the derivatives as obtained from the docked poses using Autodock-Vina QAhn COX1 COX2 Topo I NF-ĸB HDAC2 Avg. BA Active Binding Sites COX2) Asn361, Leu210 9h -7.8 -8.3 -7.2 -6.6 -8.1 -7.6 Tyr108 9d -8.8 -8.1 -7.2 -6.5 -8 -7.72 Gly121, Tyr116 9a -8.3 -9 -7.5 -6.9 -7.6 -7.86 Asn 361 9g -8 -9.5 -7.3 -6.9 -7.8 -7.9 9i -8.9 -8.5 -7.4 -6.9 -7.9 -7.92 Gly 121 (2) 9f -8.8 -8.8 -7.2 -6.9 -7.9 -7.92 Cys 21, Cys 32 9c -8.4 -9.4 -7.2 -6.6 -8.1 -7.94 Gly 121, Leu 201, Ser 129 9b -8.1 -9.3 -7.5 -7.1 -8.1 -8.02 9m -8.7 -8.6 -7.8 -7 -8.2 -8.06 Asn 24 9e -9 -9.5 -7.3 -6.8 -7.9 -8.1 Tyr116, Asn24, Gln447, Ala142 9j -9.4 -9.4 -7.6 -7.1 -8.4 -8.38 9n -9.3 -9.3 -7.6 -7 -8.7 -8.38 Ser 34 9k -9.7 -9.3 -7.8 -7.4 -8.1 -8.46 Gly 121 (2), Tyr 116 9l -9.3 -10.2 -8.1 -7.3 -8.8 -8.74 Gly 121 Avg. -8.4 -8.8 -7.4 -6.8 -7.9 -7.88 NA Sd 0.6 0.6 0.3 0.3 0.3 0.31 NA Ref 1* -8.1 -10.6 -9.3 -6.8 -8.9 -8.74 NA Ref 2* -7.5 -8.2 -8.6 -6.8 -8.3 -7.88 NA Saha -5.9 -6.4 -6.8 -5.4 -6.1 -6.12 NA *Ref 1: Daunorubicin, *Ref 2: Dexamethasone; NA – Not Applicable
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The hydrogen bonds and non-covalent bonds (π-π interaction and π-cation interactions) were considered for the ligand-receptor interactions. The binding affinities (ascending order) noted for the best docked poses with least RMSD are significant as the interaction energies exhibited an average of -7.88 for the whole data set across the studied inhibitions. Clearly the chief active site
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residues in the COX2 protein are the Gly121, Tyr116 and Asn361 residues with other active groups being Serine, Cys, Ala and Gln where the hydrogen bond is formed through the NH of the hydrazide and N of the Quinoline ring. However, in the key derivatives of interest 9k and 9l that exhibit the maximum binding affinity, it’s the OCH3 in the Quinoline ring that takes part in
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the binding. We can see that while mostly it is this hydrogen bonding driving the interaction, there’s also van der waals interactions - non-covalent bonds - like in 9b and 9j with very good
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binding affinity. We can rationalize that the presence of the electron pumping group in -OCH3 present in 9a-9e in general leads to the lesser binding affinity relatively, given that they pump the electron cloud into the N on the NH in the hydrazide group involved in the interaction, reducing the availability of H for bonding with the protein. As observed, in fact, in some cases, even this group itself becomes the acceptor to a relevant donor in the active site of the protein. Consequently, the presence of the electron withdrawing -CF3 group in 9k and 9l explains the
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increased binding affinity, especially in 9k where the NH forms a 1.9A0 bond to the Gly 121 residue given that the group leaves the electron cloud on H intact for more interaction.
The above results thus indicated the potential of these derivatives to pursue the corresponding
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mechanisms to result in the respective medicinal property. However, the docking scores suggest that these set of derivatives in general could act as better anti-inflammatory agents as compared
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to anti-cancer agents. Specifically, the COX2 inhibitors retrieve the best poses as against the COX1 inhibition with the highest average binding potential. The inhibition binding with respect to NF-ĸB falls short even though its promise is established when compared to the reference drugs dexamethasone.[29] Further, these QAh exhibited significant HDAC inhibition as against their tubulin interaction. Thus, the wide mechanistic role of these derivatives demonstrates their potential as anti-cancer agents as when compared to the reference drug Daunorubicin [29] and Saha. [30] The study infers the significant derivatives that could be explored as potential leads in 9k and 9l with the highest binding affinities observed which are better even than corresponding reference ligands. The presence of the tri-fluorocarbon group substitution can be considered as a
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major factor that influences the azomethine moiety that primarily takes part in the binding interactions with the active residues in the enzymes. To examine the structural features of these synthesised derivatives, we undertook their conformational study using the Gaussian 03
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program. [26] Computational Studies
In this computational study, the ab intio DFT calculations were performed using Becke’s three parameter exchange functional in combination with the Lee–Yang–Parr correlation functional
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(B3LYP) and standard 6-311G(d,p) basis set in the Gaussian 03 program [26] to obtain the optimized conformation generated by energy minimization with respect to all geometrical
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parameters. Consequently, we also determined the MO picture, hyperpolarizability and chemical reactivity for each of these species optimized by the DFT method. The Fig. 2 captures the optimized conformers of potent derivatives of interest (9k and 9l) in the study. Given the Koopman’s theorem,[31] the global chemical reactivity descriptors (GCRD), based on the conceptual DFT that defines molecular structure stability and reactivity were studied. [32] For these are also employed in the progress of quantitative structure activity (QSAR), structure-
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property (QSPR), and structure- toxicity (QSTR) relationships.
Figure 2. MO diagrams of the least energy conformations of the DFT level G03 optimized least energy conformations of 9k and 9l derivatives
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In this study, our focus was to find the values of various GCRD parameters such as chemical hardness (η),[33–35] chemical potential (µ), softness (S), electronegativity (χ) and the electrophilicity index (ω) of the QAh derivatives from their HOMO and LUMO energies values using different functional as tabulated (Table 2). Most importantly, the species with the most
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chemical reactivity also happen to exhibit the best medicinal efficacy, providing a plausible attribute, key to the design of these class of drugs. Perhaps, their reactivity is a consequence of their MO energy gap driving their interaction with the active site eventually.
Hardness Softness Potential EN (η) (S) (µ) (χ) 0.06202 0.00621 -0.13834 0.17650 0.06147 0.00597 -0.13283 0.16851 0.06314 0.00626 -0.13529 0.17136 0.06419 0.00634 -0.13326 0.16779 0.05940 0.005734 -0.13367 0.17080 0.06373 0.00642 -0.13779 0.17483 0.07244 0.00806 -0.15001 0.18879 0.05919 0.00569 -0.13328 0.17033 0.06002 0.00581 -0.13372 0.17057 0.07571 0.00835 -0.14495 0.17957 0.07236 0.00812 -0.15201 0.19184 0.07356 0.00838 -0.15438 0.19479 0.07366 0.00836 -0.15320 0.19297 0.07117 0.00782 -0.14867 0.18742
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EHOMO (au) -0.2004 -0.1943 -0.1984 -0.1975 -0.1931 -0.2015 -0.2225 -0.1925 -0.1937 -0.2207 -0.2244 -0.2279 -0.2269 -0.2198
GEI (ω) 0.15429 0.14352 0.14494 0.13830 0.15040 0.14898 0.15532 0.15006 0.14896 0.13875 0.15967 0.16199 0.15931 0.15528
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9a 9b 9c 9d 9e 9f 9g 9h 9i 9j 9k 9l 9m 9n
ELUMO (au) -0.0763 -0.0714 -0.0722 -0.0691 -0.0743 -0.0741 -0.0776 -0.0741 -0.0737 -0.0692 -0.0797 -0.0808 -0.0795 -0.0775
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QAha
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Table 2. Chemical reactivity of the QAH derivatives calculated theoretically from the G03 studies
Non Linear Optics
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New frequency conversion materials based on organic NLO materials with high nonlinear susceptibilities have been discovered but their application has been hindered in practical device applications owing to inadequate transparency, poor optical quality and low laser damage threshold. [36]
In this regard, we observe that our studied set of derivatives (Table 3)
demonstrate significant NLO potential as when compared to the standard reference of Urea. The calculated first hyper polarizability (SHG) of the QAH derivatives are on an average around 18 times more than that of the standard NLO material urea (0.13×10-30 esu) [37]. This can be attributed to the electron pumping and withdrawing nature of the substituents and their positions
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which is clear in the high SHG and 3rd order Hyperpolarizability for 9k and 9l given the good electron withdrawing group (p-CF3) at the para position. We therefore conclude that these derivatives could be explored as attractive molecules for nonlinear optical properties with respect
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to both their SHG parameters and 3rd order Hyperpolarizability. Table 3. Dipole moment ‘µ’, polarizability αtot (×10-24 esu) and first order static hyper polarizability βtot (×10-30esu) and third order hyper polarizability (×10−36 esu) data for QAH derivatives using DFT theory
1.372 a
17.08733 183.18657 220.44898 138.99893 118.24639 191.76005 279.31362 124.74487 127.66726 323.27514 9.27642 60.31177 190.51739 32.39189
13.80223 10.98813 10.37671 9.76634 11.92301 9.88300 10.92604 13.74135 15.66986 11.03326 14.27444 13.26674 11.72014 9.562501
-
Mean First Order Hyper polarizability
Mean Polarizabili ty* (αtot)
2.35648 2.14033 3.12538 2.03715 1.68149 2.07507 3.21909 1.96250 1.50096 3.07379 2.36176 2.77183 1.59482 1.98186
24.9777 22.334 22.0644 22.2432 22.8856 21.0321 21.9329 23.7003 24.3379 20.2629 24.5449 24.0722 23.867 21.8535
0.13
-
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Third order Hyper polarizability*
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Anisotropy of Polarizability
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9a 9b 9c 9d 9e 9f 9g 9h 9i 9j 9k 9l 9m 9n Urea (Ref.)
Static Dipole Moment (µ) 9.7716 8.8624 9.9781 8.7239 8.924 10.1357 9.4991 8.9597 8.9905 7.0599 1.2233 10.7589 7.9311 8.5638
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*negative values
In Vitro Studies
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QAh
a
Finally, given the inference from the docking studies that indicated the significant potential of
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this class of derivatives for their anti-inflammatory activity, we undertook the in vitro studies via the COX2 enzyme inhibition assay (Table 4). We notice that 9k (IC50 0.13 µM) and 9l (IC50 0.14 µM) as predicted from the docking scores returned significant values of inhibition that’s even better that the standard (IC50 0.38 µM) (Fig. 3). Further, 9h also serves as an interesting derivative to be considered. Also, the in-vitro anti-inflammatory activity was carried out by Human Red Blood Cell (HRBC) membrane stabilization method using indomethacin as standard. The compounds 9k and 9l exhibited an excellent % membrane protection. Even though the indomethacin (standard) showed an IC50 of 0.08 µg/mL with % protection 82.22, the significant
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derivatives 9k (0.098 µg/mL, 76.21) and 9l (0.092 µg/mL, 78.43) also established a remarkable activity.
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Table 4. Results of COX2 enzyme inhibition of 9a-l Entity Ligand efficiency % inhibition IC50 (µM)** 9a -0.044 32.92 7.12 µM 9b -0.040 30.32 6.88 µM 9c -0.003 64.01 0.85 µM 9d 0.011 70.38 0.58 µM 9e Not Inhibited 9f 0.001 52.36 0.98 µM 9g 0.009 58.01 0.62 µM 9h 0.027 72.42 0.25 µM 9i -0.014 53.16 1.87 µM 9j Not Inhibited 9k 0.042 80.82 0.13 µM 9l 0.041 80.98 0.14 µM 9m 0.006 68.24 0.75 µM 9n -0.037 35.21 5.21 µM Std* 0.022 79.46 0.38µM *Celecoxib, ** All IC50 values are the mean of duplicate/triplicate measurements.
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Figure 3. Inhibition of COX2 with compound 9k and 9l
Ligand efficiency (LE)
This factor measures the binding energy per atom of a ligand to receptor or enzyme. [38] This is an important feature for it assists at an early stage in the filtering of the potential leads possessing optimal combination of physicochemical and pharmacological properties. [39] Mathematically, it can thus be defined as the ratio of Gibbs free energy (∆G) to the number of non-hydrogen atoms of the compound as determinable in the equation: [40] LE = 1.4(-logIC50)/N
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In the evaluation of the LE for our set of prepared derivatives, as tabulated (Table 4) we interestingly note that the ligand efficiency is also maximum with respect to the established most active molecules. Further, more significantly, the efficiency also happens to be more than the
Anticancer determinations by MTT assay
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standard reference celecoxib, almost doubling from 0.022 to 0.041 and 0.042.
The human breast cancer (MCF-7) and skin cancer (G-361) cell lines were incubated with different doses (10 to 150 µg/ml) of QAh to evaluate the anticancer activity. Cells were seeded at
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a density of 1×104 cells/well in a 96-well plate and grown for another 24 hours. After 24 hours of incubation, cell viability was determined by the MTT assay and the inhibitory percentage were calculated. QAh 9a-n was able to inhibit the proliferation of the cancer cells. IC50 values indicate
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that some of the tested QAh were as active as the standard drug Doxorubicin (IC50 2.444 µM), the standard (Fig. 4). QAh 9h (2.416 µM), 9k (2.071 µM) and 9l (2.224 µM) were found with
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excellent activity and results were considerably similar/more with Doxorubicin.
Figure 4. Anticancer activity results of doxorubicin and (clockwise) 9h, 9i and 9k at various concentrations.
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Lipinski’s filter
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A typical strategy during drug discovery is to optimize step-wise to increase efficiency vis-a-vis the activity and selectivity while ensuring the conformity of the drug-like physicochemical properties described by Lipinski's rule. [41] For, the Lipinski's rule of five (R05) serves as a popular and significant thumb’s rule in the evaluation of drug likeness in determination of the
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molecule’s potential as an orally active drug with respect to its pharmacological or biological activity. The rule covers important molecular properties in the drug's pharmacokinetics like ADME but fails to predict if a compound is pharmacologically active. A conformity to the R05 S+logP 3.705 3.577 3.363 3.511 3.471 3.838 4.293 3.32 3.954 4.119 4.576 4.514 4.093 4.104
S+logD 3.705 3.577 3.363 3.511 3.471 3.838 4.293 3.32 3.954 4.119 4.576 4.514 4.093 4.104
R05 0 0 0 0 0 0 0 0 0 0 1 1 0 0
R05_Code
MWt (da) 339.372 369.398 369.398 369.398 369.398 383.425 397.452 399.425 327.336 393.343 377.344 377.344 345.326 345.326
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MlogP 3.08 2.534 2.534 2.534 2.534 2.754 2.971 1.995 3.754 3.417 4.204 4.204 3.868 3.868
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QAh 9a 9b 9c 9d 9e 9f 9g 9h 9i 9j 9k 9l 9m 9n
M_NO 5 6 6 6 6 6 6 7 4 5 4 4 4 4
T_PSA 55.74 64.97 64.97 64.97 64.97 64.97 64.97 74.2 46.51 55.74 46.51 46.51 46.51 46.51
HBDH 1 1 1 1 1 1 1 1 1 1 1 1 1 1
provides more promise to the candidate drug for eventual success during clinical trials and
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consequently greater chance of reaching the market. [42,43]
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Table 4. Determination of the Lipinski filters in the evaluation of the drug-likeness of the derivatives Some of the standard markers evaluated in this regard are as follows: • S+logP - logP calculated using Simulations Plus’ highly accurate internal model. • S+logD - logD at user-specified pH (default 7.4), based on S+logP. • MlogP - Moriguchi estimation of logP. • HBDH - Number of Hydrogen bond donor protons. • M_NO - Total number of Nitrogen and Oxygen atoms. • T_PSA - Topological polar surface area in square angstroms. • RuleOf5 - Lipinski’s Rule of Five: a score indicating the number of potential problems a structure might have with passive oral absorption.
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•
RuleOf5_Code - Lipinski’s Rule of Five codes: LP = logP; Hb = number of Hydrogen bond donor protons; Mw = molecular weight; NO = number of Nitrogen- and Oxygenbased Hydrogen bond acceptors.
In the established values (Table 4) for the various Lipinski parameters, the presence of a code in
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R05_Code infers the violation of the corresponding Lipinski rule. Here, we notice that the two derivatives of preferred 9k and 9l violate the Lipinski rules with respect to their partition coefficient (Log P not greater than 3). This, therefore, serves as a red flag in the in silico evaluation of their role as potential multi-functional therapeutic leads. However, this could be addressed
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either with the kind of formulation in the eventual design, or even otherwise serve as a wonderful starting point to explore the specific groups (SAR) that serves as a key to a particular biological
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activity – in this specific case being – the trifluoro substituent.
Conclusion
An extensive theoretical study of the structure, reactivity and NLO attributes of novel quinoline-acetohydrazide-hydrazone derivatives was undertaken. Further, their molecular docking studies were evaluated to explore their drug repurposing. The entire data set
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demonstrated significant in silico anti-cancer and anti-inflammatory activity potential against a wide spectrum of notable mechanisms. In specific, the derivatives with trifluoro substituent in the quinoline scaffold showed excellent binding that was attributed to their withdrawing effect on the interacting donor group in the ligand. Their appreciable in
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silico binding affinities comparable to the prescribed standard reference drugs suggested their role as potential inflammation and cancer therapeutics that was consequently
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confirmed in vitro. The docking study helped rationalize the mechanism by providing the ideal docked poses of the least energy conformations of the drug ligands in the interacting active sites amino residues in the protein. While the Lipinski parameters noted a set back with respect to the partition coefficient, the ligand efficiency and NLO potential of 9k and 9l derivatives prove them to be promising leads given their 3 fold enhancement in their COX2 inhibiting potential with respect to the reference drug Celecoxib.
Acknowledgements
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We are grateful to Sathya Sai Baba, the founder chancellor, SSSIHL for his constant guidance and inspiration. We are also indebted to the administration of SSSIHL and the department of
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