In Silico Design of Novel Dipeptidyl Peptidase 4 (DPP4) Inhibitors Containing Triazolopyrazine Derivatives with Respect to their Anti-Diabetic Activities

Diabetes Mellitus (DM) can be described as a metabolic disorder or a group of systemic dysfunctions of the pancreas characterized by hyperglycaemia with metabolic disturbances of carbohydrates, proteins, and fats due to the destruction of beta cells of the pancreas, leading to less insulin secretion or insulin resistance of the organs or both [1-2]. The three major types of Diabetes Mellitus are Type-I, Type-II & Gestational diabetes mellitus (GDM). Type-I diabetes, also known as Insulin-Dependent DM / IDDM, is responsible for impaired insulin secretion. Type-II diabetes, also known as Non-Insulin-Dependent DM / NIDDM, occurs due to insulin resistance in the body. Human body cells are not responding properly, which they should be in the presence of insulin. In 2017, approximately 8.8% of the population, which is about 424.9 million individuals, was identified as having DM. This trend shows that this number will be high, approximately 693 million or 9.9% of the world population in 2040 [3-4]. DM is becoming a growing epidemic disorder by the day. Managing DM should have not only pharmacologic but also non-pharmacologic interventions for better reports. As the most common type of diabetes, type-II DM is the point of interest of most of the pharmacologists and medicinal chemists for the betterment of the prevention and care process of DM patients. Several new oral diabetic agents are being discovered nowadays by them, which include sulfonylurea, thiazolidinediones, etc., along with Dipeptidyl peptidase 4 (DPP-4) inhibitors. DPP-4 inhibitors have moderate efficacy compared to the mainstay treatment of metformin, with a combination of another good-profile drug and insulin. DPP-4 inhibitors are recommended when metformin is contraindicated [5]. There are very few established DPP-4 inhibitors like sitagliptin, gemigliptin, teneligliptin, gosogliptin, etc. [6]. We have taken 20 test compounds as screened by the structure of the established drug using various chemical databases. Docking of test compounds to the target was analysed with the standard DPP-4 inhibitor’s docking result to screen for comparatively better suitable test molecules.

General Information On Enzyme & It’s Inhibitors

In 1966, the first DPP-4 (Molecular weight: 110 kDa) was discovered as an enzyme [7]. It is a type II transmembrane glycoprotein that contained 766 amino acids [7]. The primary three domains of DPP-4 that allow it to attach to the cell membrane are: a brief cytoplasmic domain made up of six amino acids, a transmembrane domain consisting of twenty-two amino acids, and an extracellular domain containing seven hundred thirty-eight amino acids [7]. This extracellular domain can be broken down into three distinct parts: a highly glycosylated region, a cysteine-rich region, and a catalytic region [8,9]. This protein is released from the cell membrane in a non-classical secretary mechanism and degrades substrates, including incretin hormones, cytokines and growth factors [10]. Incretin hormones like GLP-1 (Glucagon-like peptide 1), GIP (glucose-dependent insulinotropic polypeptide) have a marked anti-diabetic property through their ability to stimulate the pancreas to secrete insulin, inhibit glucagon secretion, inhibit beta cell apoptosis, and increase neogenesis. DPP-4 rapidly inactivates the GLP-1 hormone (resulting in a half-life of the active form of GLP-1 reduced to < 2min), causing a negative effect on the above-mentioned physiological activities [11-12]. DPP-4 inhibitors are designed as a way that they can bind specifically with this exopeptidase (DPP-4), causing the blockade of the protein that leads to the inactivation of the physiological activity of the protein. It results in an increased half-life of GLP-1, which results in increased beta cell neogenesis and inhibited apoptosis, increased insulin secretion, etc., and reduced plasma glucose level [13,9].

Parent Molecule & Substructures:

There are many drugs already established in the DPP-4 Inhibitor category, e.g., Sitagliptin, Gemigliptin, Teneligliptin, Gosogliptin, Saxagliptin, Vildagliptin, etc. [14-15]. This research has taken Sitagliptin as a Standard Parent Molecule to screen test compounds from the chemical database. Along with this, 3 more molecules have been taken for the comparison study between a few established compounds and test compounds to understand the activity differences. Sitagliptin was the first oral DPP-4 inhibitor to receive approval from the USFDA, which is the United States Food and Drug Administration. The chemical name of sitagliptin[ (2R)-4- Oxo-4[3-(trifluoromethyl)-5,6-dihydro[1, 2, 4]triazolo[4,3-a]pyrazin-7(8H)-yl] 1-(2,4,5-trifluorophenyl]butan2-amine ]. The structure mainly has a triazolopyrazine heterocyclic ring and a trifluorophenyl group [16]. All 20 test compounds have been taken as substructures of this Sitagliptin parent structure.

MATERIALS & METHODOLOGY:

Sl. No.	Name	Type	Used for	Reference No.
1	PubChem	Web Database	Virtual Screening	[17]
2	ZINC20	Web Database	Virtual Screening	[18]
3	RCSB PDB	Database	Receptor / Protein research	[19]
4	PDBsum	Software	Protein-Ligand Interaction Study	[20]
5	PyMOL	Software	Modify protein &3D Protein-Ligand Complex Analysis	[21]
6	UCSF ChimeraX	Software	Protein Structure visualization and molecular interaction analysis	[22]
7	CB-Dock2	Web Tool	Docking of Ligands to Protein	[23]
8	Pharmit	Web Tool	Pharmacophore Study	[24]
9	ChemMaster Basic	Software	Molecular Descriptors Calculation	[25]
10	SwissADME	Web Tool	Molecular Descriptors Calculation	[26]
11	pkCSM	Web Tool	ADMET Prediction	[27]
12	ProTox 3.0	Web Tool	Carcinogenicity Prediction	[28]

RESULT:

Sl. No.	Standard Compound Name	Structure
1	Sitagliptin
2	Gemigliptin
3	Teneligliptin
4	Gosogliptin

Table 3: List of the Test Compounds

Sl. No.	Test Compounds	Structure
1	C1
2	C2
3	C3
4	C4
5	C5
6	C6
7	C7
8	C8
9	C9
10	C10
11	C11
12	C12
13	C13
14	C14
15	C15
16	C16
17	C17
18	C18
19	C19
20	C20

Sl. No.	Name of the Standard Compound	Docking Result [Binding Energy (Kcal/mol)]	Molecular Docking
1	Sitagliptin	-8.1
2	Gemigliptin	-8.3
3	Teneligliptin	-8.0
4	Gosogliptin	-7.7

Table 6: Docking of Test Molecules to the Active Site of 5T4E

Sl. No.	Name of the Test Compound	ZINC20 ID	Docking Result [Binding Energy (Kcal/mol)]	Molecular Docking
1	C1	ZINC28967916	-7.9
2	C2	ZINC3962167	-8.4
3	C3	ZINC14959011	-7.8
4	C4	ZINC14959014	-8.1
5	C5	ZINC28967321	-8.4
6	C6	ZINC28967349	-8.2
7	C7	ZINC28967362	-8.7
8	C8	ZINC28967367	-8.5
9	C9	ZINC28967377	-8.5
10	C10	ZINC28967407	-8.4
11	C11	ZINC28967412	-8.3
12	C12	ZINC28967417	-8.0
13	C13	ZINC28967422	-8.8
14	C14	ZINC28967651	-8.4
15	C15	ZINC28967658	-8.8
16	C16	ZINC28967826	-8.3
17	C17	ZINC28967833	-8.0
18	C18	ZINC28967868	-8.0
19	C19	ZINC28967888	-9.0
20	C20	ZINC28967893	-7.4

Table 7: Screening of Test Compounds (1^st Time) Based on Molecular Docking

Test Compounds (Screened)	Pharmacophoric Structure	Pharmacophoric Features
C4		Aromatic, Hydrogen Bond Donor, Hydrogen Bond Acceptor, Hydrophobic
C7		Aromatic, Hydrogen Bond Donor, Hydrogen Bond Acceptor, Hydrophobic
C9		Aromatic, Hydrogen Bond Donor, Hydrogen Bond Acceptor, Hydrophobic
C14		Aromatic, Hydrogen Bond Donor, Hydrogen Bond Acceptor, Hydrophobic
C18		Aromatic, Hydrogen Bond Donor, Hydrogen Bond Acceptor, Hydrophobic
C19		Aromatic, Hydrogen Bond Donor, Hydrogen Bond Acceptor, Hydrophobic

Table 9: Molecular Formula and Molecular Weight of Standard Compounds

DISCUSSION:

As we can see in result section, we have screened 20 substructures of Sitagliptin moiety from the chemical databases and docked them against the 5T4E enzyme. The protein structure was downloaded from RCSB Protein Data Bank and then modified in PyMOL software to ensure uninterpted docking. Six best test candidates (C4, C7, C9, C14, C18, C19) among twenty were selected based on their binding energy obtained from docking. As only from the binding energy or fitting score is not enough to ensure the effective biological action, we have gone through furthurmore for the study of Molecular Descriptors along with Physicochemical properties to obtain a more reliable evaluation. Application of various Medicinal Chemistry filters and screening criteria (Lipinski’s Rule, Veber’s Rule, PAINS Filter, SA Score) then used to remove undesirable compounds from the list. Applying the rules and on the basis of comparison of molecular descriptors, physicochmical propertiesthreetest candidates out of six were taken to study furthur. Furthurmore to get best one molecule, previously screened three test candidates were studied on the basis of ADMET. One best test candidate (C7 or (2R)-4-[(8S)-8-methyl-3-(trifluoromethyl)-5,6-dihydro[[1,-2,4]triazolo[4,3-a]pyrazin-7(8H)-yl]-4-oxo-1-(2,4,5-trifluorophenyl)butan-2-amine hydrochloride) was obtained among four standard compounds (Sitagliptin, Gemigliptin, Teneligliptin and Gosogliptin).

CONCLUSION:

The C7 Molecule ((2R)-4-[(8S)-8-methyl-3-(trifluoromethyl)-5,6-dihydro[[1,-2,4]triazolo[4,3-a]pyrazin-7(8H)-yl]-4-oxo-1-(2,4,5-trifluorophenyl)butan-2-amine hydrochloride) which was obtained from a long research of  computational chemistry studies found promising compound among other test molecules. That C7 molecule represents nearly same report as what standard drug molecule Sitagliptin produces. The binding energy, Synthetic Accessibility (SA) score suggest a smooth molecule fitting in protein and easier synthetic strategy. Furthermore the ADMET study involves many important physiological parameters prediction which indicates suitable pharmacokinetic and toxicity properties. Overall, this in silico study demonstrated the efficacy of drug design in finding new and safe DPP4 inhibitors.

ACKNOWLEDGEMENT:

All authors are grateful to Global College of Pharmaceutical Technology for providing us the opportunities to perform this research work.

CONFLICT OF INTEREST: None

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