Design, in-silico ADME Study and molecular docking study of novel quinoline-4-on derivatives as Factor Xa Inhibitor as Potential

anti-coagulating agents

Nikunj Patadiya¹*, Vipul Vaghela²

¹Research Scholar, Department of Pharmaceutical Chemistry, A.R College of Pharmacy and G.H Patel Institute of Pharmacy, Vallabh Vidhyanagar, Anand, Gujarat, India.

²Professor, Department of Pharmaceutical Chemistry, A.R College of Pharmacy and G.H Patel Institute of Pharmacy, Vallabh Vidhyanagar, Anand, Gujarat, India.

*Corresponding Author E-mail: nikunj20899@gmail.com

ABSTRACT:

The main aim of present work is to identification of potency of novel quinoline-4-one derivatives as a factor Xa inhibitors by in-silico ADME study and molecular docking study. Factor Xa is enzyme which play major role in blood coagulation process by conversation of prothrombine to thrombine. Thrombine is the protein which converts fibrinogen to fibrin (clot). Inhbition of factor Xa is altimetly inhbition of blood coagulation process. Due to the abnormal blood coagulation, serious to very serious problems can create and will lead to death. Betrixaban, Rivaroxaban, Epixaban and Edoxaban which are FDA approval dugs as factor Xa inhibitors. They are very potent drugs and very few side effects compare to other available anti-coagulating drugs so they was taken as a reference molecules for current study. Some novel quinoline-4-one derivatives was design and screened for factor Xa enzyme. We design 26 compounds and first they screen for in-silico ADME parameters. Very few compounds not pass Lipinski rule. A majority compound shows excellent in-silico ADME properties. In molecular docking study almost all compound shows near binding energy to reference drug and shows almost near dock score. Q23 and Q26 show excellent inhibitory activity against Factor Xa. 13 molecules shows very near dock score compare to reference drugs. This study became a reference and provides valuable data for the synthesis, in-vitro and in-vivo evaluation of quinolone-4-on derivatives as Factor Xa inhibitors.

KEYWORDS: Quinoline-4-on, Factor Xa, In-Silico ADME/T, Molecular Docking.

INTRODUCTION:

Factor Xa Inhibitors:

Factor Xa inhibitors are a type of anticoagulant (blood thinning drugs) that work by binding selectively and reversibly to the clotting factor Xa^1,2. Factor Xa plays a crucial role in the blood clotting mechanism when you get an injury by forming a mesh to prevent loss of blood³.

However, clots can form within the body and cause blockages in the arteries, veins, and heart causing heart attacks and strokes^4,5. Factor Xa inhibitor can affect factor Xa that is present in both the blood and an existing clot. This makes factor Xa an excellent target for anticoagulation therapy. Factor Xa inhibitor will not show any direct affect on platelet aggregation^6,7. The inhibition of clotting factor Xa has been shown to be a potential target for anticoagulation therapy.

Mechanism of Action:

In the formation of clot, different factors play their unique role. In all factors one is Factor Xa. It’s a subtype of factor X. Blood clotting either trigger by intrinsic pathway or extrinsic pathway, factor Xa is formed. This factor is responsible for the conversation of thrombin from prothrombin, and thrombine is essential for conversation of fibrin (clot) from fibrinogen. So conversation of thrombin is reduce or blocked at site of action, and it’s directly affecting the fibrin synthesis which is responsible as a clot. It’s have also not affected on aggregation of platelets^8,9.

Figure 1. Mechanism of Action of Factor Xa Inhibitors

Uses of Factor Xa inhibitors¹⁰:

· Nonvalvular atrial fibrillation (irregular heartbeat caused by excess pressure or stretching of the heart chambers).

· Venous thromboembolism (blood clot that starts in a vein).

· Reduction of recurrent deep vein thrombosis (blood clots in a deep vein, usually in the legs) and pulmonary embolism (blockage in one of the pulmonary arteries in your lungs).

· Prophylaxis following knee or hip replacement surgery.

METHODOLOGY:

In silico ADME studies:

The pharmacokinetic phase has four steps: absorption, distribution, metabolism and excretion (ADME). Recently, a phase for the toxicological evaluation of new drug candidates has been incorporated into it, resulting in the ADME-T study.²⁴ The primary goal is to provide a competitive product based on efficacy and adequate safety, avoiding PK-based failures in the clinic. A major challenge for the development of a drug is the evaluation of its ADME properties in humans. The analysis of the pharmacokinetic profile of a drug candidate is performed in vitro and in vivo by testing its solubility, absorption, permeability and metabolites, among other parameter.^25,26 We investigate in-silico ADME parameters of novel quinoline-4-one derivatives by using online tool SwissADME. SwissADME tool gives precise data about ADME parameters of compounds¹¹.

Molecular Docking Study¹²:

Molecular docking is a kind of computational modeling, which facilitates the prediction of preferred binding orientation of one molecule (ligand) to another (Receptor), when both interact each other in order to form a stable complex. Types of docking information gained from the preferred orientation of bound molecules may be employed to predict the energy profiling (such as binding free energy), strength and stability (like binding affinity and binding constant) of complexes.^13-22 Autodock 4.2.6 tool was used for the docking of Factor Xa protein (PDB Code: 1WU1) as target enzyme. For the suanalyze docking results, Discovery Studio 2021 was used.

RESULTS:

In-Silico ADME Results:

By using online tool SwissADME we investigate molecules in-silico ADME parameters. SwissADME analyse all most all important parameter related to ADME data like Molecular weight, hydrogen bond donor (HBD), hydrogen bond acceptor(HBA), Molecular refractivity (MR), LogP value, Rotatable bonds number, Skin permeability, GI absorption, Bioavailability etc. It also analyzes synthetic ability which is very important parameter for medicinal chemist.

Table 1. Lipinski Rule Study of Compounds

Molecule	Formula	Molecular Weight (g/mol)	HBA	HBD	MR	TPSA (A˚)	iLogP	Rotatable Bonds	Lipinski Following
Normal	C23H16N2O3	368.38	3	1	108.59	68.17	2.83	5	Yes
Q1	C23H15ClN2O3	402.83	3	1	113.6	68.17	2.61	5	Yes
Q2	C24H15F3N2O3	436.38	6	1	113.59	68.17	3.21	6	Yes
Q3	C24H18N2O4	398.41	4	1	115.08	77.4	3.24	6	Yes
Q4	C24H17N3O4	411.41	4	2	116.69	111.26	2.56	6	Yes
Q5	C24H16ClN3O4	445.85	4	2	121.7	111.26	2.86	6	Yes
Q6	C25H16F3N3O4	479.41	7	2	121.69	111.26	2.49	7	Yes
Q7	C25H19N3O5	441.44	5	2	123.18	120.49	2.09	7	Yes
Q8	C25H18N4O5	454.43	5	3	124.78	154.35	1.9	7	Yes
Q9	C25H17ClN4O5	488.88	5	3	129.79	154.35	1.79	7	Yes
Q10	C26H17F3N4O5	522.43	8	3	129.78	154.35	1.74	8	No
Q11	C26H20N4O6	484.46	6	3	131.27	163.58	1.72	8	Yes
Q12	C26H19N5O6	497.46	6	4	132.88	197.44	0.8	8	No
Q13	C25H17ClN4O5	488.88	5	3	129.79	154.35	2.13	7	Yes
Q14	C26H17F3N4O5	522.43	8	3	129.78	154.35	2.09	8	No
Q15	C26H20N4O6	484.46	6	3	131.27	163.58	1.54	8	Yes
Q16	C26H19N5O6	497.46	6	4	132.88	197.44	1.19	8	No
Q17	C24H16ClN5O5	489.87	6	3	127.59	167.24	1.27	7	Yes
Q18	C25H18N6O6	498.45	7	4	130.67	210.33	0.8	8	No
Q19	C25H17ClN6O6	532.89	7	4	135.68	210.33	0.35	8	No
Q20	C26H19N7O7	541.47	8	5	138.77	253.42	0.29	9	No
Q21	C32H23N7O7	617.57	8	5	164.89	239.43	0.9	11	No
Q22	C32H23N7O7	617.57	8	5	164.89	239.43	0.82	11	No
Q23	C32H23N7O7	617.57	8	5	164.89	239.43	0.97	11	No
Q24	C32H23N7O7	617.57	8	5	164.89	239.43	0.95	11	No
Q25	C38H27N7O7	693.66	8	5	191.01	225.44	2.56	13	No
Q26	C38H27N7O7	693.66	8	5	190.32	239.43	1.75	12	No

Table 2. Pharmacokinetics Study of Compounds

Molecule	GI absorption	BBB permeate	Pgp substrate	Skin permeability log Kp (cm/s)	Bioavailability Score	Synthetic Accessibility
Normal	High	Yes	No	-5.96	0.55	2.54
Q1	High	Yes	No	-5.73	0.55	2.59
Q2	High	No	No	-5.75	0.55	2.75
Q3	High	Yes	No	-6.17	0.55	2.68
Q4	High	No	No	-7.03	0.55	2.72
Q5	High	No	No	-6.79	0.55	2.8
Q6	High	No	No	-6.81	0.55	3.05
Q7	High	No	No	-7.23	0.55	2.95
Q8	Low	No	No	-8.09	0.55	2.99
Q9	Low	No	No	-7.85	0.55	3.01
Q10	Low	No	No	-7.88	0.55	3.17
Q11	Low	No	No	-8.29	0.55	3.09
Q12	Low	No	No	-9.15	0.55	3.16
Q13	Low	No	No	-7.85	0.55	3.01
Q14	Low	No	No	-7.88	0.55	3.18
Q15	Low	No	No	-8.29	0.55	3.1
Q16	Low	No	No	-9.15	0.55	3.15
Q17	Low	No	No	-8.38	0.55	3.13
Q18	Low	No	No	-9.67	0.55	3.27
Q19	Low	No	No	-9.44	0.17	3.28
Q20	Low	No	No	-10.74	0.17	3.4
Q21	Low	No	No	-9.81	0.17	3.82
Q22	Low	No	No	-9.81	0.17	3.83
Q23	Low	No	No	-9.81	0.17	3.79
Q24	Low	No	No	-9.81	0.17	3.79
Q25	Low	No	No	-8.88	0.17	4.19
Q26	Low	No	No	-9.12	0.17	4.21

Table. 3 Molecular Docking Score.

Sr. No.	Molecule	Estimated Free Energy of Binding (kcal/mol)	Estimated Inhibition Constant, Ki (uM (micromolar)/ nanomolar nM)
1	Normal	-9.92	53.21 nM
2	Q1	-9.98	48.68 nM
3	Q2	-9.93	52.50 nM
4	Q3	-9.96	50.34 nM
5	Q4	-10.03	44.41 nM
6	Q5	-9.33	144.66 nM
7	Q6	-9.40	128.17 nM
8	Q7	-10.20	33.44 nM
9	Q8	-10.21	32.55 nM
10	Q9	-10.04	43.85 nM
11	Q10	-8.55	540.06 nM
12	Q11	-10.03	44.18 nM
13	Q12	-10.19	33.66 nM
14	Q13	-10.36	25.27 nM
15	Q14	-10.20	33.20 nM
16	Q15	-9.41	125.82 nM

Table. 3 continued

Sr. No.	Molecule	Estimated Free Energy of Binding (kcal/mol)	Estimated Inhibition Constant, Ki (uM (micromolar)/ nanomolar nM)
17	Q16	-10.23	31.80 nM
18	Q17	-9.51	106.62 nM
19	Q18	-8.28	854.79 nM
20	Q19	-10.38	24.52 nM
21	Q20	-10.89	10.40 nM
22	Q21	-9.53	102.59 nM
23	Q22	-10.27	29.53 nM
24	Q23	-12.34	902.53 pM
25	Q24	-10.46	21.43 nM
26	Q25	-9.74	72.16 nM
27	Q26	-11.80	2.24 nM
28	Betrixaban	-8.27	872.23 nM
29	Rivaroxaban	-9.60	91.88 nM
30	Apixaban	-10.45	21.96 nM
31	Edoxaban	-8.55	539.24 nM

DISCUSSION:

Molecular weights of compounds are nearly 500 and few compounds shows more than 600. Hydrogen bond acceptor atoms are between 3-5. Hydrogen bond donor counts between 1-5. Q1-Q20 shows MR value between 100-160, but Q-21 to Q26 compound shows MR value greater than 160. iLog P value is less than 3.5 which indicate compound can easily absorb in GI track. Rotatable bonds count is less than 10 in Q-1 to Q20, but Q21-Q26 this number is more than 10. Almost all compounds follow Lipinski rule, but fewer compounds not following Lipinski rule. Compounds which fail in Lipinski rule show very close value to passing value. Half of compounds show high GI absorption and only 3 compound shows BBB permeability. Compounds shows excellent skin permeability and bioavailability score. Most of compounds easily synthesized in lab so synthetic accessibility score are also good.

Molecular docking study is performed using Autodock 4.2.6 and MGLTools. Molecular docking study provide information about how ligand bind to target enzyme, how many amino acids are bind with ligand and by which kind of interaction and it also provide binding energy strength in form of numbers.

All molecules shows nearly dock score of reference drugs. Molecule Q23 and Q26 shows lowest binding energy compare to all design compounds and reference drugs. Only Q18 shows higher dock score than reference drug.

Figure 2. Docking Pose of Q23

CONCLUSION:

To identify the potentially Factor Xa inhibitor compounds of novel quinoline-4-one derivatives, computer-assisted virtual screening of quinoline-4-one derivatives based on the literature compounds and verified the candidate compounds by molecular docking and in-silico ADME. Based  on ;itrature review quinoline-4-one derivatives was design and substituted with necessary groups. After we screen those molecules for ADME properties. All molecules are shows satisfactory ADME properties and very few molecules not follow Lipinski Rule. On the basis of ADME data we can say it design molecules shows good GI absorbance except few molecules. After, we perform molecular docking study of design molecules. On the basis of docking results we can say Novel quinoline-4one derivatives shows excellently inhibit Factor Xa enzyme. Q23 shows lowest binding energy which shows Q23 can excellently bind and inhibit Factor Xa. On the basis of all data we can say that Novel Quinoline-4-one derivatives became a safe and potential inhibitors of Factor Xa and use as anti-coagulating agents.

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Received on 26.11.2021         Modified on 04.01.2022

Accepted on 06.02.2022   ©Asian Pharma Press All Right Reserved

Asian J. Pharm. Res. 2022; 12(3):207-211.

DOI: 10.52711/2231-5691.2022.00034