In silico vetting of vinyl quinoline derivatives as potent Anti- Diabetic leads

doi:10.21203/rs.3.rs-2719300/v1

The increased microbial resistance against developed and existing drug molecules urges us to design targeted drug molecules in short span of time though designing and marketing new drug is tedious and time-consuming as it requires several clinical trials. Thus the current study focuses on computer-aided drug design through in silico studies which hastens the screening of millions of lead compounds quickly. It also facilitates the design of new lead compounds instead of using the wet-lab method. The potential pharmaceutical activity of vinylquinoline compounds made us choose them as a lead for anti-diabetic screening. In this study, we attempted to explore the in silico anti-diabetic activity of randomly chosen 25 vinylquinoline derivatives using Maestro Schrödinger software. The toxicity of the ligands are predicted in silico using the software Toxtree. The preliminary screening of these ligands against potent Dipeptidyl Peptidase (DPP IV) reveals vinyl quinoline derivatives possess docking scores comparable to standard Metformin Hydrochloride. Thus the docking results highly recommends vinyl quinoline derivatives as a potent anti-diabetic drug.

In silico

Docking

Maestro Schrödinger

Hex

Vinyl quinolines

Antidiabetic activity

India is called as the capital of diabetics. One fourth in India is diabetic. Diabetes is one of the chronic illness which cause 4.2 million deaths worldwide in 2019. About 1.1 million children and adults, with type 1 diabetes and 374 million people developed a risk of type 2 diabetes [1]. The increased urbanization, modernized lifestyle behaviours, unhealthy foods, lack of physical activity, and increased weight gain are the leading cause of diabetes. Diabetes also leads to other severe complications such as damage to nerves and blood vessels which is a root cause for organ damage such as vision loss, renal failure, strokes and cardiac arrest. Though there are several commercially available antidiabetic drugs, majority of them cause side effects.

There are two types of diabetes: i) lack of insulin production by the pancreas. ii) The insulin produced is not utilized by body cells, and gradually the production of insulin decreases. Type 2 diabetes is more common in children and adult because of poor diet and decreased physical exercise. This can be treated by administration of insulin, increasing the sensitivity of cells to insulin, by control of the release of insulin, to increase absorption of glucose and glucose excretion by urine [2].

The drugs designed to treat diabetes should either secrete insulin or slow down the absorption of carbohydrates. The drug that can inhibit alpha-glucosidase enzyme can delay glucose absorption [3]. Similarly, DPP IV is a pleiotropic enzyme that inactivates various intestinal hormones [4]. It quickly degrades a hormone called incretins containing GLP-1 and GIP responsible for delayed emptying of the stomach, increasing insulin secretion, and decreasing glucagon secretion.

DPP IV inhibitors such as sitagliptin, saxagliptin, linagliptin, alogliptin and Metformin have been so far administered to treat type II diabetes [5]. Thus DPP IV inhibiting drugs with lesser side have been explored for type 2 diabetes.

Quinolines are nitrogen-containing aromatic heterocyclic compounds possessing a variety of biological and pharmacological activities. The cinchona alkaloids used in malaria treatment are also a quinoline moiety [6]. Quinoline and its derivative are found to be anti-bacterial [7], antifungal [8], antimalarial, anthelmintic [9], anticonvulsant, anti-inflammatory [10], and analgesic activity [11]. Broad application of quinolines in agro chemistry, medicinal chemistry and material science are well known. Several commercially available antimalarial drugs belong to the class of amino quinolines, namely chloroquine, amodiaquine, piperaquine [12]. Also, the pharmacological activities of the quinolines are of great importance. These made us to explore the in silico anti-diabetic activity of the randomly chosen quinoline derivatives. Computer aided software is used to determine the drug likeliness of numerous compounds, including natural products and synthetic compounds. The commercial software Schrödinger and computer freeware Hex were used and reported to screen thousands of lead compounds for its in silico biological activity [13, 14]

Thus the present study aims to screen vinyl quinoline lead compounds for its anti-diabetic potential as potent DPP IV inhibitor using the commercial Schrödinger software and Hex freeware. The toxicity of these class of vinyl quinolines are determined by Toxtree software. The novelty of the work lies in showcasing vinyl quinoline derivatives as anti-diabetic lead where the docking score is comparable to Metformin.

The ligands for the present study are detailed in Table s1. (Supporting Information) where Metformin hydrochloride serves as a standard. This is a broad spectrum anti-diabetic drug which is prescribed by the clinicians worldwide. The antidiabetic activity of vinyl quinolines derivatives was determined using commercial Maestro Schrödinger software, Hex 6.3 internet freeware. The Protein chosen for the present study is DPPIV (PID: 2RIP). The protein 2RIP was downloaded from Protein Data Bank. The docking values of the ligands are compared with the standard Metformin hydrochloride. The toxicity of the ligands are determined using Toxtree freeware.

Docking Studies

The vinyl quinoline derivative lead compounds and standard Metformin Hydrochloride are docked with 2RIP protein using Hex software (6.3). The docking energy obtained was recorded. The same lead compounds are docked using Maestro Schrödinger software. The ligands are prepared using Ligprep and docked with the prepared protein (2RIP) based on Gride-Based Ligand Docking with Energies (GLIDE). The GLIDE score for lead compounds and standard Metformin Hydrochloride from both Hex and Maestro Schrödinger was noted and compared.

Ligand Preparation

Initially, the ligands and the protein structures are saved as pdb file, to perform docking using Hex. The ligands and proteins are also prepared for docking in the Schrödinger software.

The ligand preparation was executed with the Lig prep in the application wizard of Schrödinger software. Each ligand was saved as separate files after Lig prep job execution. Following are the ligands prepared using Chem Draw professional software (V 16.0.1.4[77]) and used for the current study

Protein preparation

The 3D structure of the target protein DPP IV (PID: 2RIP) (Fig. 1) is downloaded from the Protein Data Bank (PDB). The protein was prepared using the protein preparation wizard (Fig. 2).

Determination of ADME properties

ADME properties of the ligands were determined using Maestro Schrödinger software. These properties paved a better path to identify the drug likeliness and the effect upon oral administration of the chosen ligands. As the ligands are organic moieties, determining ADME properties is necessary to arrive at the drug dissolution, oral bioavailability, drug like properties etc. Thus, QikProp operation wizard in Schrödinger software determines the ADME properties of ligand.

Prediction of Toxicity

Toxtree is a user-friendly open application which predicts the toxicity of the ligand by decision tree approach. The chemical toxicity of ligand is estimated by computer-based freeware. It categorizes the ligands based on their toxic nature by various parameters such as Cramer’s rule, Verhaar scheme, Skin irritation prediction etc. The Smiles of the ligand are given as input. The toxicity is predicted by parameters like Cramer’s rule, skin sensitization, genotoxic carcinogenicity, potential carcinogen based on QSAR [15].

Docking Studies

Docking of Ligands with protein using Hex and Maestro Schrödinger software

Initial screening of the ligands with the DPP IV complex was done using the Hex software. Energy obtained for the ligands was recorded, and it was compared with standard Metformin hydrochloride. Fig. 3 depicts docking of 2 – vinyl quinoline with the protein 2RIP.

Table 1. Docking Score from Hex

S. No	Name of the compound	Energy(kcal mol^-1)
1	Metformin Hydrochloride-1	-128.51
1a	Metformin Hydrochloride-2	-128.51
2	2-Vinylquinoline	-143.07
2a	2-Vinylquinoline-1	-143.07
2b	2-Vinylquinoline-2	-143.07
3	8- Bromo-2-vinylquinoline	-155.81
4	6-Methoxy-8-nitro-2-vinylquinoline	-178.02
5	7-Chloro- 2- vinylquinoline	-152.50
5a	7-Chloro-2-vinylquinoline	-152.50
6	6,7-Difluoro-2-vinylquinoline	-163.06
7	8-Chloro- 2- vinylquinoline	-155.81
7a	8-Chloro- 2- vinylquinoline	-155.81
8	4-Methyl-2-vinylquinoline	-152.02
9	3-Vinylquinoline	-138.87
9a	3-Vinylquinoline-1	-138.87
10	2-Methoxy-3-vinylquinoline	-172.47
11	2-Chloro-7-methyl-3-vinylquinoline	-159.91
12	4-Vinylquinoline	-152.02
13	6-Bromo-4-vinylquinoline	-159.64
14	6-Methoxy-4-vinylquinoline	-151.44
15	5-Vinylquinoline	-142.65
16	8-Chloro-5-vinylquinoline	-162.85
17	8-Bromo-5-vinylquinoline	-162.85
18	8-Nitro-5-vinylquinoline	-160.86
19	3-Methoxy-5-vinylquinoline	-148.84
20	2-Chloro-7-methyl-5-vinylquinoline	-159.04
21	2-Bromo-7-methyl-5-vinylquinoline	-159.04
22	2-Chloro-5-vinylquinoline	-152.34
22a	2-Chloro-5-vinylquinoline	-152.34
23	7-Vinylquinoline	-138.87
23a	7-Vinylquinoline	-138.87
24	8-Vinylquinoline	-142.71
25	5-Bromo-8-vinylquinoline	-154.62
26	2-Ethyl-3-methyl-8-vinylquinoline	-167.44

Table 1 shows the docking energy of ligands and standard metformin hydrochloride from Hex. It is to be noted that lower the energy in kcal mol ^-1, higher will be the docking score for ligands with protein. From the Table 2, 3-vinylquinoline and 7-vinylquinoline isomers possess energy -138.87 kcal mol^-1which is lower and comparable with the standard Metformin hydrochloride having energy -128. 51 kcal mol^-1.As there are several limitations for the Hex software, the results obtained from Hex is compared with a commercial software Maestro Schrödinger.

The ligands are docked with the protein in Maestro Schrödinger with Gride based Ligand docking energies (GLIDE). The active site chosen for this particular study is the A: 34 Q (800). Gride is generated for this active site, and the docking is executed. Maestro Schrödinger software is very efficient in determining the ligand's isomers, and docking is done for each isomer. The isomers of the ligands are listed as a,b,c with the ligand name. The docking score of ligands from Schrödinger software is given in Table 2.

Table 2. Docking score obtained from Schrödinger software

1	Metformin Hydrochloride-1	-4.141
1a	Metformin Hydrochloride-2	-2.203
2	2-Vinylquinoline	-6.504
2a	2-Vinylquinoline-1	-5.767
2b	2-Vinylquinoline-2	-3.659
3	8-Bromo-2-vinylquinoline	-5.587
4	6-Methoxy-8-nitro-2-vinylquinoline	-5.368
5	7-Chloro- 2- vinylquinoline	-4.926
5a	7-Chloro-2-vinylquinoline	-4.67
6	6,7-Difluoro-2-vinylquinoline	-4.724
7	8-Chloro- 2- vinylquinoline	-4.092
7a	8-Chloro- 2- vinylquinoline	-3.378
8	4-Methyl-2-vinylquinoline	-4.044
9	3-Vinylquinoline	-3.916
9a	3-Vinylquinoline-1	-3.538
10	2-Methoxy-3-vinylquinoline	-4.941
11	2-Chloro-7-methyl-3-vinylquinoline	-3.997
12	4-Vinylquinoline	-6.364
13	6-Bromo-4-vinylquinoline	-4.778
14	6-Methoxy-4-vinylquinoline	-3.67
15	5-Vinylquinoline	-4.542
16	8-Chloro-5-vinylquinoline	-3.908
17	8-Bromo-5-vinylquinoline	-3.842
18	8-Nitro-5-vinylquinoline	-5.601
19	3-Methoxy-5-vinylquinoline	-4.291
20	2-Chloro-7-methyl-5-vinylquinoline	-3.527
21	2-Bromo-7-methyl-5-vinylquinoline	-3.39
22	2-Chloro-5-vinylquinoline	-4.022
22a	2-Chloro-5-vinylquinoline	-3.752
23	7-Vinylquinoline	-4.002
23a	7-Vinylquinoline	-3.357
24	8-Vinylquinoline	-4.744
25	5-Bromo-8-vinylquinoline	-4.305
26	2-Ethyl-3-methyl-8-vinylquinoline	-4.036
1	Metformin Hydrochloride-1	-4.141

Table 3. Glide score and Glide energy obtained from Schrödinger software

S. No	Name of the compound	Glide score (kcal mol^-1)	Glide energy(kcal mol^-1)
1	Metformin Hydrochloride-1	-4.167	-14.795
1a	Metformin Hydrochloride-2	-4.07	-20.159
2	2-Vinylquinoline	-6.531	-23.067
2a	2-Vinylquinoline-1	-5.772	-19.505
2b	2-Vinylquinoline-2	-5.508	-25.426
3	8-Bromo-2-vinylquinoline	-5.587	-27.405
4	6-Methoxy-8-nitro-2-vinylquinoline	-5.37	-24.45
5	7-Chloro- 2- vinylquinoline	-4.926	-23.023
5a	7-Chloro-2-vinylquinoline	-4.682	-19.068
6	6,7-Difluoro-2-vinylquinoline	-4.724	-23.952
7	8-Chloro- 2- vinylquinoline	-5.236	-27.548
7a	8-Chloro- 2- vinylquinoline	-3.471	-21.279
8	4-Methyl-2-vinylquinoline	-4.063	-21.706
9	3-Vinylquinoline	-3.933	-21.273
9a	3-Vinylquinoline-1	-5.65	-28.376
10	2-Methoxy-3-vinylquinoline	-4.943	-22.109
11	2-Chloro-7-methyl-3-vinylquinoline	-3.997	-19.517
12	4-Vinylquinoline	-6.366	-23.442
13	6-Bromo-4-vinylquinoline	-4.779	-22.594
14	6-Methoxy-4-vinylquinoline	-3.67	-20.519
15	5-Vinylquinoline	-4.542	-21.692
16	8-Chloro-5-vinylquinoline	-3.908	-23.406
17	8-Bromo-5-vinylquinoline	-3.842	-27.366
18	8-Nitro-5-vinylquinoline	-5.606	-20.981
19	3-Methoxy-5-vinylquinoline	-4.291	-21.275
20	2-Chloro-7-methyl-5-vinylquinoline	-3.527	-22.815
21	2-Bromo-7-methyl-5-vinylquinoline	-3.39	-22.745
22	2-Chloro-5-vinylquinoline	-4.022	-22.455
22a	2-Chloro-5-vinylquinoline	-3.752	-26.786
23	7-Vinylquinoline	-4.025	-22.014
23a	7-Vinylquinoline	-5.257	-28.41
24	8-Vinylquinoline	-4.744	-28.861
25	5-Bromo-8-vinylquinoline	-4.307	-19.488
26	2-Ethyl-3-methyl-8-vinylquinoline	-4.036	-22.469

Among 26 vinyl quinoline derivatives, 2-vinylquinoline exhibits the highest docking score of -6.504 where the docking score of Metformin hydrochloride is -4.141. This clearly shows the efficiency of the vinylquinoline as the potent DPP IV inhibitor. Glide score obtained for the vinylquinoline ligands is listed in Table 3. Compared with the standard Metformin hydrochloride, the Glide score obtained for the vinylquinoline derivatives is high and appreciable. Glide score for 2-vinylquinolines is more compared to that of the other vinylquinoline derivatives. This ensures the capability of the ligand as an anti-diabetic drug. All the ligands and their respective isomers show an appreciable glide score compared to the standard Metformin hydrochloride administered as an anti-diabetic drug. Table 3 also shows the ligands' glide energy after docking with the DPP IV complex with an inhibitor. From this table, it is clear that the glide energy is appreciable for all the docked ligands. Some difference in the glide energy value can be seen for isomers.

Fig. 4a and 4b shows the 2D and 3D interaction of the ligand 2-vinylquinoline with the protein 2RIP whereas Fig. 5a and 5b shows 2D and 3D interaction of Metformin hydrochloride with the protein 2RIP. The lead ligand shows π interaction with the amino acid moiety ARG. This gives the excellent docking score in GLIDE. Apart from the π interaction, some weak interaction such as Vander Waal forces is also seen in the 2D interaction of the vinyl quinolines with the protein. Thus the ligand possess appreciable glide score as that of standard Metformin Hydrochloride.

Among quinoline derivatives, 2-vinylquinolines exhibit an extensive range of pharmacological activities, as epitomized by anti-leishmanial agent chimanine, anticancer compound, integrase inhibitor FZ41, CysLT1 antagonist VUF 5017 and antimalarial agent UCF 501 [12]. Dipeptidyl peptidase IV (DPP-IV) is associated with several epidemic diseases like type I diabetes, tumour growth and obesity [16]. DPP-IV inactivates the action of incretins by scavenging the N-terminal dipeptides of incretins. It results in a decrease in insulin secretion and an increase in blood glucose level [17]. DPP- IV inhibitors shows an advantageous effect compared to classical anti-diabetic therapies when administered as a daily oral dose [18, 19].

It is also observed that there is no correlation between the glide energy values for the ligands obtained from the Schrödinger software and the Hex software. Thus the results made the users to go for the commercial software where freeware could be used for preliminary screening in in silico activity determination.

ADME properties

The properties of the ligands were analyzed to ensure the pharmacokinetic activities, and it is found to obeys Lipinski Rule of five [20]. Table s2. (Supporting Information) shows the Absorption, Distribution, Metabolism and Excretion predictions of the ligands and the standard Metformin hydrochloride. The log P o/w of ligands are between 0.7 – 4.0 where log S lies within -4.1 - -0.4. The values of logP o/w and log S for all ligands falls within the recommended range -2.0 - 6.5 and -6.5 – 0.5 respectively. This further confirms that chosen ligands obeyed Lipinski rule of five and possess good drug dissolution, oral availability and drug like property. The similar studies on nitrogenous heterocyclic compounds for anti-tumour activity against the Alkylglycerone phosphate synthase (AGPS) were carried out where the drug likeliness of the ligands were determined using ADME properties using Schrodinger software [20]. The results ensure the drug-like properties of the heterocyclic compounds belonging to the class of vinylquinoline. Upon further wet-lab studies and clinical trials, the class of vinylquinoline’s can be administrated as anti-diabetic agents.

Prediction of Toxicity

The toxicity of ligands predicted using Toxtree 3.1 software Table s3 (Supporting Information) shows three ligands 8- nitro-5-vinyl quinoline, 6- methoxy-8-nitro-2-vinyl quinoline and 2-nitro-5- vinyl quinoline possess low toxic risk as estimated by Kroes TTC decision tree method. Based on QSAR, all the 28 ligands are not potential carcinogens, but these three ligands possess no genotoxic carcinogenicity. Thus in silico method of toxicity prediction of ligands are possible by utilizing the Toxtree model. Further validation of the results by in vivo or in vitro method is warranted.

The Schrödinger software performs as a perfect platform for the in silico anti-diabetic activity screening of the compounds. The glide score obtained for 2-vinylquinolines are more compared to that of the other vinyl quinoline derivatives and comparable with standard Metformin hydrochloride. This ensures the capability of the ligand as an anti-diabetic drug and potent DPP IV inhibitor. Also, docking studies carried out by the freeware is not in agreement with the values obtained by commercial software. The correlation between the glide energy values for the ligands obtained from the Schrödinger software and the Hex software's docking energy are compared and is not apparent. Thus computer-based commercial software validates and screens millions of lead compounds in lesser time, and it is easy to carry out wet-lab studies for selected compounds with good ADME properties. This has made it possible to discover drugs quickly and reach the market as soon as possible.

Acknowledgement

We acknowledge Bharat Ratna Prof. C.N.R Rao Research Centre, and Department of Biochemistry and Biotechnology, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore for providing software facilities.

Funding

There was no funding supporting this research

Conflict of Interest

The authors declare that there is no conflict of interest

Author’s Contribution

Aruna Ponnusamy performed the research and wrote the main manuscript.
Dr. Lalitha Pottail designed and mentored the research.
Akhila Chithambharan, Ravimoorthy Rajalakshmi and Reena susan Philip analyzed the data

Data Availability

The authors declare that the data supporting the findings of this study are available within the article [and its supplementary information files].

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No competing interests reported.

In silico vetting of vinyl quinoline derivatives as potent Anti- Diabetic leads

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Abstract

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Introduction

Experimental

Results And Discussion

Conclusions

Declarations

References

Additional Declarations

Supplementary Files

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