Design of some Apigenin derivatives as selective DPP-IV Inhibitors by Pharmacophore Modelling and its Validation through Molecular Dynamics Simulation

 

Ritika Sahu1, Surendra Jain2, Deepti Jain1

1School of Pharmaceutical Sciences, Rajiv Gandhi Proudyogiki Vishwavidyalaya,

Airport Road, Gandhi Nagar, Bhopal (M.P.) 462033.

2Truba Institute of Pharmacy, Karond-Gandhi Nagar Bypass Road, Bhopal (M.P.) 462038.

*Corresponding Author E-mail: ritikasahu15@gmail.com

 

ABSTRACT:

One of the most common forms of diabetes, type-2 diabetes mellitus is a chronic metabolic condition brought on by problems with insulin production or insulin resistance. By modifying blood glucose homeostasis, dipeptidyl peptidase-IV (DPP-IV) inhibition has the potential to treat type 2 diabetes. The quick development of computational drug design provided a fantastic opportunity to both discover and forecast the effectiveness of potential DPP-IV inhibitors. The current investigation supports and verifies the identification of new Apigenin derivatives as selective DPP-IV inhibitors. Schrodinger software was used to perform virtual screening (VS) of created compounds against DPP-IV, and the most promising hits were chosen. Out of 110 substances, 56 new apigenin derivatives were chosen for additional docking investigations using Glide based on their selectivity threshold followed by validation by pose selection method which is found to be below 2 Ǻ based on their superimposion with co-crystallized lgand. The DPP-IV protein was used as the target of molecular dynamic (MD) simulation studies to evaluate the correct binding mechanisms and stability of their complexes with enzyme. Structural chemistry was utilised to guide and considerably speed up the drug discovery process during the back-up development stages. It was also used to analyse in-silico suggestions and screening results, as well as to come up with fresh ideas. The study thus demonstrates the possibility of apigenin derivatives as highly specific DPP-IV inhibitors.

 

KEYWORDS: Dipeptidyl Peptidase-Iv, Molecular Dynamic, Apigenin Derivatives.

 

 


INTRODUCTION: 

Diabetes is a serious health issue that is spreading quickly. Over 170 million people with type 2 diabetes are thought to exist worldwide1. For the treatment of type 2 diabetes, dipeptidyl peptidase IV (DPP-4) inhibition is a well-established strategy. The inactivation of the incretin hormones glucose dependent insulinotropic polypeptide (GIP) and glucagon-like peptide 1 (GLP-1) by the enzyme DPP-4 is crucial for maintaining glucose homeostasis.

 

Humans with DPP-4 inhibition have higher levels of GLP-1 and GIP in their blood, which lowers blood sugar, haemoglobin A1c, and glucagon levels2. Sitagliptin phosphate, which was approved by the FDA in 2006 as a novel drug for the treatment of type 2 diabetes, is a powerful, orally bioavailable, and highly selective small molecule DPP-4 inhibitor. It contains a trifluoro phenyl group attached to a b-amino butanoyl moiety coupled to a triazolopiperazine3.

 

Fig 1: Sitagliptin

 

Sitagliptin's structure, bound to DPP4 along with the structures of a second class of inhibitors, served as the basis for the structure-driven compound design that was utilised to create various back-up molecules prior to approval, over the course of sitagliptin's clinical trials One of the qualities that needed to be preserved and improved upon was selectivity. In order to design viable backup chemicals, it was necessary to address the possibility of off-target toxicity. Up until Sitagliptin's approval, many backup molecules were created and tested as a result of this4. Here, we will discuss how structural chemistry was utilised throughout the stages of backup development and how a logical approach, carried out by molecular modelling with the assistance of structure data, may considerably speed up and lead drug discovery.One of the most common flavonoids (subclass- Flavone) is apigenin (5,7-dihydroxy-2-(4-hydroxyphenyl)chromen-4-one), which is found in plants like Cynodon dactylon, chamomile, etc. Numerous studies have noted apigenin's antioxidant qualities, coupled with its anti-hyperglycemic, anti-inflammatory, and (in myocardial ischemia) anti-apoptotic activities. Flavonoids are generally well known for their antioxidant characteristics5.

 

Fig 2: Apigenin

 

The flavone subclass of flavonoids, which apigenin [2-(4-hydroxyphenyl)-5,7-dihydroxy-4H-chromen-4-one] belongs to, is present in a variety of fruits, vegetables, and traditional medicines such as parsley, onion, orange, tea, chamomile, wheat sprouts, and seasonings. Apigenin exhibits a range of anti-tumor properties in various cells, including the activation of gap junctional and intracellular communication and the suppression of mutagenesis, transformation, angiogenesis, and tumorigenesis. Apigenin is a strong antioxidant that can increase insulin release from the pancreas as well as the transport of glucose in peripheral tissues6. Studying the structure-activity relationships of apigenin analogues made by inserting various functional groups into various places in the apigenin skeleton is a quick and efficient method. A number of novel apigenin analogues with aminomethyl groups on the C-8 position were produced in the current work because the 8-position of apigenin has not previously been extensively studied7,8. By replacing the functional groups important for the protein's activity towards DPP-IV inhibition, we are interested in creating analogues of apigenin (ID:6B1E).

 

Fig 3: Different Modifications of Apigenin

 

2.Target structure setup for protein–ligand docking:

 

2.1. In silico: Molecular modeling:

By molecular docking with the crystal structure of DPP-IV, the inhibitory capability of API against DPP-IV was evaluated. By using Glide software (Maestro, version 8.5, Schrödinger, LLC, 2008), the docking score of API and its variations were compared9,10.

 

2.2. Selection and Preparation of proteins and ligand

The database was searched for DPP-IV (PDB: 6B1E). Using the recommended procedure in the Glide software, the protein structures were pre-processed, fine-tuned, and the geometries were optimised. Using LigPrep 2.5 (Schrödinger LLC, Portland, USA;)11, the structure of was modified and altered.First, using the Epik software, all the protonation states between pH 2.0 and 7.0 were constructed. Schrodinger's Optimization Potential for Ligand Simulation (OPLS-2005) force field is used to minimise the ligand's geometries.

 

2.3. Ligand Docking:

The Glide XP extra precision mode was used to carry out the protein-ligand docking. While the protein structure was hard, the ligand structure was kept flexible.

The ligand binding energy was considered using:

Ligand Binding energy, ∆E = Ecomplex – Eligand – Eprotein

The negative binding score indicates higher affinity of the ligand to the protein.

 

2.4. Docking Validation:

Pose Selection is a frequently used technique used to re-dock a substance with a known conformation and orientation, generally from a co-crystal structure, into the target's active site. Programs are deemed effective if they can produce poses with an RMSD (Root Mean Square Deviation) value below a certain threshold (often 1.5 or 2 depending on ligand size) from the known conformation.

 

2.5. Molecular Simulation:

Using the Desmond package, an MD simulation investigation was conducted on three chosen hits (RSBS35.RSMS14, RSPS1) and co-crystallized ligand for 10 ns. The three steps of this work were system builder, minimization, and molecular dynamics. For the purpose of running MD simulations, the system was equilibrated using an NPT ensemble at 300K temperature and 1 bar pressure. The final file with the extension "out.cms" was assessed for protein qualitative and quantitative analysis using RMSD, protein-ligand contact, etc.

 

2.6. Predicted ADME studies:

The Swiss Institute of Bioinformatics' online tool SwissADME (http://www.sib.swiss) was used to predict the ADME properties of compounds (SSSK 16–20), including predicted GI absorption, P-glycoprotein, blood–brain barrier, and drug-likeness prediction using Lipinski, Ghose, and Veber rules and bioavailability score

 

2.7.ProTox-II:

It serves as a virtual laboratory for predicting small chemical toxicity.The LD50 values for toxic dosages are frequently expressed in mg/kg body weight.

 

3. RESULTS AND DISCUSSION:

3.1.In silico study:

Using Schrodinger software, molecular docking was used to determine how the API and its derivatives interacted with the DPP-IV enzyme. Hydrogen bond interaction, docking score, and gliding score were examined. Tables 1, 2, and 3 list the binding affinities of API and its derivatives with the DPP-IV enzyme, and figure 3.1 shows a visual representation of the same. Tables 1, 2, and 3 also list the docking score and hydrogen bond formation of the docked proteins. Of all the substances examined, API binds to the DPP-IV enzyme at Glu206, Tyr662, Arg358 and Phe357.

 


Table 1: Docking Scores of designed compounds and Standard drug (Sitagliptin)

Compounds

Structures

Docking Scores

No. of H-Bonds

Residues involved in the hydrogen bonding

Sitagliptin

 

-6.9

3

Tyr 547,Glu 205,Glu 206

RSBS1

 

-8.4

4

Tyr 547,Glu 205,Arg 125,Tyr 666

RSBS2

 

-6.5

6

Phe 357,Glu 206,Glu 205

Arg 669,Tyr 666,Arg 125

RSBS3

 

-6.7

3

Glu 205,Phe 357,Tyr 666

RSBS4

 

-8.1

3

Ser 630,0Arg 125,Glu 206

RSBS5

 

-6.3

3

Glu 206,Glu 205,Arg 669

 

RSBS6

 

-7.0

2

Glu 205,Tyr 666

 

RSBS7

 

-6.9

5

Glu 205,Glu 206,Tyr 666

Ser 209,Arg 669

RSMS8

 

-6.0

3

Glu 205,Phe 357,Gln 553

RSBS9

 

-3.8

3

Tyr 542,Gln 553,Lys 554

RSBS10

 

-4.2

4

Phe 357,Glu 205,Glu 206

Tyr 585

RSBS11

 

-7.1

1

Glu 206,Gln 553,Glu 205

Ser 209

RSBS12

 

-6.7

3

Glu 206,Ser 630,Gln 553

RSBS13

 

-7.1

4

Glu 205,Glu 206,Gln 553

Ser 209

RSBS14

 

-5.2

4

Gln 553,Glu 205,Glu 206

Ser 209

RSBS15

 

-6.9

2

Glu 206,Ser 630

RSBS16

 

-2.3

2

Glu 206,Ser 630

RSBS17

 

-6.4

4

Glu 205,Glu 206,Gln 553

Ser 553

RSBS18

 

-6.9

2

Glu 206,Ser 630

RSBS19

 

-4.2

3

Arg 125,Phe 357,Tyr 547

RSBS20

 

-5.3

2

Ser 630,Gln 553

RSBS21

 

-7.4

4

Glu 206,Tyr 547,Gln 553

Arg 125

RSBS22

 

-2.4

3

Ser 630,Tyr 547,Arg 669

RSBS23

 

-3.5

3

Tyr 666,Tyr 547,Glu 206

RSBS24

 

-6.1

3

Tyr 547,Glu 206,Tyr 666

RSBS25

 

-4.3

3

Tyr 547,Glu 206,Tyr 666

RSBS26

 

-7.2

1

Gln 553

RSBS27

 

-4.7

3

Tyr 547,Glu 206,Tyr 666

RSBS28

 

-5.1

3

Gln 553,Tyr 547,Glu 205

RSBS29

 

-5.4

2

Ser 630,Tyr 547

RSBS30

 

-8.6

5

Glu 206,Glu 205,Asn 710

Gln 553,00Tyr 547

RSBS31

 

-3.5

3

Tyr 547,Glu 206,Tyr 666

RSBS32

 

-8.8

1

Tyr 547

 

RSBS33

 

-5.6

4

Glu 205,Ser 357,Tyr 547

Ser 630

RSBS34

 

-5.2

8

Arg 125,Ser 209,His 126

Tyr 666,Arg 669,Ser 630

Glu 205,Glu 206

RSBS35

 

-9.5

7

Arg 125,Ser 209,Val 207

Glo 205,Glu 206,Arg 669

Ser 630

RSBS36

 

-7.8

6

Arg 669,Glu 205,Glu 206

Tyr 547,Phe 357,Cys 551

RSBS37

 

-7.6

2

Glu 205,Glu 206

RSBS38

 

-3.8

3

Ser 630,Glu 206,Phe 357

RSBS39

 

-4.6

3

Tyr 666,Glu 206,Tyr 547

RSBS40

 

-3.3

3

Tyr 547,Ser 630,Phe 357

 

RSBS41

 

5.2

5

Glu 205,Glu 206,Arg 669

Ser 209,Phe 357

RSBS42

 

-7.6

3

Glu 205,Glu 206,Arg 669

RSBS43

 

-8.8

5

Glu 205,Glu 206,Tyr 666

Arg 669,Ser 209

RSBS44

 

-5.8

4

Glu 206,Arg 669,Tyr 547

Phe 357

RSBS45

 

-5.3

5

Tyr 666,Tyr 547,Glu 206

Glu 206,Arg 669

RSBS46

 

-5.7

4

Glu 206,Tyr 347,Phe 357

Arg 669

RSBS47

 

-6.2

5

Ser 630,Ser 209,Glu 206

Glu 205,His 126

 

RSBS48

 

-6.3

3

Ser 630,Glu 205,Ser 209

RSBS49

 

-6.2

6

Glu 205,Glu 206,Phe 357

Tyr 547,Arg 669,Ser 209

RSBS50

 

-5.8

5

Ser 630,Tyr 666,Phe 357

Glu 206,Arg 666

RSBS51

 

-5.9

5

Tyr 662,Tyr 666,Glu 206

Arg 669,Phe 357

RSBS52

 

-10.2

5

Glu 206,Tyr 666,Tyr 547

Val 207,Arg 125

RSBS53

 

-8.0

4

Glu 205,Glu 206,Arg 669

Ser 209

RSBS54

 

-6.6

6

Phe 357,Ser 630,Glu 206

Glu 205,Arg 669,Ser 209

RSBS55

 

-6.6

4

Ser 630,Glu 206,Glu 205

Ser 209

 

Fig 3. 1: 2D and 3D Docking interaction of RSBS with minimized protein 6BIE:

 

Table 2: Docking Scores of designed compounds (Scheme 2):

Compounds

Structures

Docking Scores

No. of H-Bonds

Residues involved in the hydrogen bonding

RSMS1

 

-4.6

5

Ser 630,Val 207,Phe 357,Iue 405

Arg 358

RSMS2

 

-7.6

4

Ser 209,Arg 358,Phe 357,Glu 205

RSMS3

 

-7.7

5

Glu 205,Glu 206,Arg 358,Ser 209

Phe 357

RSMS4

 

-2.6

4

Phe 357,Ser 209,Glu 205,Glu 206

RSMS5

 

-5.2

2

Ser 630,Tyr 383

RSMS6

 

-4.7

4

Glu 205,Ser 630,Arg 358,Ser 209

RSMS7

 

-5.8

2

Ser 630,Gln 553

RSMS8

 

-6.5

5

Trp 627,Tyr 547,Gln 553,Phe 357

Glu 206

RSMS9

 

-6.0

3

Ser 630,Phe 357,Tyr 585

 

RSMS10

 

-6.7

5

Arg 125,Glu 205,Ser 209,Tyr 547

Gln 553

RSMS11

 

-4.9

3

Phe 357,Arg 125,Gln 553

RSMS12

 

-4.4

4

Ser 630,Glu 205,Arg 358,Ser 209

RSMS13

 

-5.1

5

Glu 206,Tyr 662,Tyr 666,Tyr 547

Cys 551

RSMS14

 

-5.0

5

Tyr 662,Tyr 666,Glu 206,Phe 357

Tyr 631

RSMS15

 

-6.0

3

Glu 205,Glu 206,Gln 553

RSMS16

 

-5.5

3

Ser 630,Glu 205,Ser 209

RSMS17

 

-3.4

3

Ser 630,Ser 209,Glu 205

RSMS18

 

-4.2

2

Phe 357,Gln 553

RSMS19

 

-4.9

3

Arg 125,Phe 357,Tyr 585

RSMS20

 

-5.2

3

Glu 205,Ser 530,Tyr 585

RSMS21

 

-5.2

2

Glu 206,His 126

RSMS22

 

-5.9

4

Ser 209,Val 207,Glu 205,Arg 358

RSMS23

 

-3.3

3

Ser 630,Glu 205,Ser 209

RSMS24

 

-4.7

3

Ser 630,Gln 553,Phe 357

RSMS25

 

-4.8

3

Ser 630,Glu 205,Ser 209

   

Table 3: Docking Scores of designed compounds (Scheme 3):

Compounds

Structures

Docking Scores

No. of H-Bonds

Residues involved in the hydrogen bonding

RSPS1

 

-4.2

6

Phe 357,Arg 125,Glu 205,Glu 206,Ser 630

Ser 209

RSPS2

 

-4.7

4

Phe 357,Ser 630,Ser 209,Glu 205

RSPS3

 

-6.4

3

Glu 205,Ser 209,Gln 553

RSPS4

 

-5.2

3

Glu 205,Ser 209,Gln 553

RSPS5

 

-4.9

5

Glu 205,Glu 206,Gln 553,Arg 358,Val 207

RSPS6

 

-6.5

5

Glu 205,Glu 206,Phe 357,Ser 209,Gln 553

RSPS7

 

-8.1

6

Phe 357,,Glu 205,Tyr 666,Gln 553,Ser 209

Arg 125

RSPS8

 

-4.8

6

Arg 125,Ser 630,Gln 553,Phe 357,Glu 205

Ser 209

RSPS9

 

-4.9

6

Arg 358,Phe 357,Ser 630,Arg 125,Glu 205

Glu 206

RSPS10

 

-5.6

6

Ser 630,Arg 125,Ser 209,Phe 357,Glu 206

Glu 205

RSPS11

 

-4.8

5

Arg 125,Glu 205,Glu 206,Ser 630,Phe 357

RSPS12

 

-4.9

5

Tyr 666,Ser 630,Gln 553,Ser 209,Glu 205

RSPS13

 

-6.2

4

Tyr 666,Gln 553,Glu 205,Ser 209

RSPS14

 

-5.2

6

Tyr 666,Ser 630,Glu 205,Phe 357,Gln 553

Ser 209

RSPS15

 

-3.3

6

Phe 357,Glu 205,Glu 206,Ser 209,Ser 630

Arg 125

RSPS16

 

-4.3

1

Gln 553

RSPS17

 

-6.5

5

Asn 710,Glu 205,Val 207,Phe 357,Arg 358

 

RSPS18

 

-5.5

4

Glu 205,Ser 209,His 126,Arg 125

RSPS19

 

-3.6

3

Glu 205,Glu 206,Arg 356

RSPS20

 

-3.5

5

Tyr 666,Tyr 547,Phe 357,Tyr 585,Asp 556

RSPS21

 

-6.1

6

Tyr 547,Ser 209,Glu 205,Glu 206,Arg 125

 

RSPS22

 

-4.0

5

Glu 205,Glu 206,Arg 358,Phe 357,Arg 356

RSPS23

 

-5.4

3

Gln 553,Arg 125,Ser 209

 

RSPS24

 

-5.8

5

Arg 125,Tyr 547,Gln 553,Glu 206,Tyr 456

RSPS25

 

-4.4

5

Arg 125,Glu 205,Glu 206,Tyr 547,Gln 553

 

 Table 4: Pharmacokinetic studies (ADME) of Selected compounds:

Compounds

Mol.wt

Water solubility

logP

BBB permeability

Lipinski rule

GI Absorption

RSBS1

402.40 g/mol

POORLY SOLUBLE

3.31

No

Yes

High

RSBS2

371.34 g/mol

SOLUBLE

2.14

No

Yes

Low

RSBS3

385.37 g/mol

SOLUBLE

2.25

No

Yes

Low

RSBS5

454.45 g/mol

Moderately Soluble

2.64

No

Yes

Low

RSBS7

342.30 g/mol

Soluble

1.96

No

Yes

High

RSBS9

429.38 g/mol

Moderately soluble

2.74

No

Yes

High

RSBS10

431.36 g/mol

Moderately soluble

3.20

No

Yes

High

RSBS11

388.37 g/mol

Moderately soluble

2.93

No

Yes

High

RSBS13

284.26 g/mol

Moderately soluble

2.48

No

Yes

High

RSBS14

302.25 g/mol

Moderately soluble

2.46

No

Yes

High

RSBS15

366.41 g/mol

Moderately soluble

3.65

No

Yes

High

RSBS19

388.37 g/mol

Moderately soluble

2.89

No

Yes

High

RSBS21

397.81 g/mol

Moderately

Soluble

2.20

No

Yes

High

RSBS35

404.41 g/mol

Soluble

3.54

No

Yes

High

RSMS1

327.33 g/mol

Moderately

Soluble

2.46

No

Yes

High

RSMS3

341.36 g/mol

Moderately

Soluble

2.71

No

Yes

High

RSMS6

313.30 g/mol

Soluble

2.13

No

Yes

High

RSMS7

369.41 g/mol

Moderately

Soluble

3.06

No

Yes

High

RSMS8

409.82 g/mol

Moderately

Soluble

2.85

No

Yes

High

RSMS10

355.27 g/mol

Soluble

1.69

No

Yes

High

RSMS12

420.41 g/mol

Soluble

2.52

No

Yes

High

RSMS13

406.39 g/mol

Soluble

1.94

No

Yes

Low

RSMS14

456.37 g/mol

Soluble

2.68

No

Yes

High

RSMS16

424.35 g/mol

Soluble

1.57

No

Yes

High

RSMS17

406.36 g/mol

Soluble

2.61

No

Yes

High

RSMS18

388.37 g/mol

Soluble

2.61

No

Yes

High

RSMS19

397.38 g/mol

Soluble

2.08

No

Yes

High

RSMS20

397.81 g/mol

 

Moderately

Soluble

2.70

No

Yes

High

RSMS21

397.81 g/mol

Moderately

Soluble

2.20

No

Yes

High

RSMS22

459.37 g/mol

Moderately

Soluble

2.32

No

Yes

High

RSMS32

379.36 g/mol

Soluble

1.82

No

Yes

High

RSMS35

407.42 g/mol

Moderately

Soluble

2.40

No

Yes

High

RSMS37

377.39 g/mol

Soluble

2.06

No

Yes

High

RSMS39

407.46 g/mol

Moderately

Soluble

2.35

No

Yes

High

RSMS40

342.35 g/mol

Soluble

2.53

No

Yes

High

RSMS42

329.35 g/mol

Soluble

2.16

No

Yes

High

RSMS43

377.39 g/mol

Moderately

Soluble

2.60

No

Yes

High

RSMS44

382.41 g/mol

Soluble

1.90

No

Yes

High

RSMS47

340.33 g/mol

Soluble

1.81

No

Yes

High

RSMS48

329.31 g/mol

Soluble

1.37

No

Yes

High

RSMS49

314.29 g/mol

Soluble

0.97

No

Yes

High

RSMS50

426.44 g/mol

Moderately Soluble

1.22

No

Yes

Low

RSMS52

386.40 g/mol

Soluble

1.66

No

Yes

Low

RSMS53

372.37 g/mol

Very soluble

1.73

No

Yes

Low

RSMS54

327.37 g/mol

Moderately Soluble

2.89

No

Yes

High

RSMS55

366.37 g/mol

Moderately Soluble

2.41

No

Yes

High

RSPS1

375.42 g/mol

Soluble

3.13

No

Yes

High

RSPS4

375.42 g/mol

Moderately Soluble

3.28

No

Yes

High

RSPS6

363.36 g/mol

Moderately Soluble

2.14

No

Yes

High

RSPS7

379.36 g/mol

Moderately Soluble

2.35

No

Yes

High

RSPS10

392.36 g/mol

Moderately Soluble

2.60

No

Yes

High

RSPS14

426.81 g/mol

Moderately Soluble

2.66

No

Yes

Low

RSPS17

447.48 g/mol

Moderately Soluble

3.66

No

Yes

High

RSPS18

481.50 g/mol

Moderately Soluble

3.06

No

Yes

High

RSPS21

485.44 g/mol

Moderately Soluble

1.48

No

Yes

Low

RSPS23

458.42 g/mol

Moderately Soluble

2.27

No

Yes

Low

RSPS24

488.92 g/mol

Poorly soluble

2.94

No

Yes

High

 


Table 5: Toxicity study (PROTOX) of Selected compounds:

Compound Name

Hydrogen bond

donor

Hydrogen Bond Acceptor

Predicted LD50

Predicted toxicity class

RSBS1

02

23

4000mg/kg

5

RSBS2

04

24

4000mg/kg

5

RSBS3

04

26

4000mg/kg

5

RSBS5

04

26

3919mg/kg

5

RSBS7

04

21

5919mg/kg

5

RSBS9

02

22

2570mg/kg

5

RSBS10

02

21

4000mg/kg

5

RSBS11

02

22

4000mg/kg

5

RSBS13

02

16

3919mg/kg

5

RSBS14

02

15

3919mg/kg

5

RSBS15

02

26

4000mg/kg

5

RSBS19

02

22

5006mg/kg

6

RSBS21

04

22

2120mg/kg

5

RSBS35

03

25

5001mg/kg

6

RSMS1

04

22

12mg/kg

2

RSMS3

04

24

12mg/kg

2

RSMS6

04

20

12mg/kg

2

RSMS7

04

28

161mg/kg

3

RSMS8

04

21

2000mg/kg

4

RSMS10

04

18

5105mg/kg

6

RSMS12

05

28

2000mg/kg

4

RSMS13

05

26

2000mg/kg

4

RSMS14

04

22

5010mg/kg

6

RSMS16

04

21

2120mg/kg

5

RSMS17

04

22

2120mg/kg

5

RSMS18

04

23

2120mg/kg

5

RSMS19

04

26

44mg/kg

2

RSMS20

03

21

145mg/kg

3

RSMS21

04

22

2120mg/kg

5

RSMS22

04

23

1000mg/kg

5

RSMS32

05

24

2120mg/kg

5

RSMS35

05

28

800mg/kg

4

RSMS37

03

26

288mg/kg

3

RSMS39

04

32

2000mg/kg

4

RSMS40

04

25

500mg/kg

4

RSMS42

05

25

500mg/kg

4

RSMS43

05

25

773mg/kg

4

RSMS44

04

29

2200mg/kg

5

RSMS47

04

23

2000mg/kg

4

RSMS48

06

23

500mg/kg

4

RSMS49

05

21

500mg/kg

4

RSMS50

05

26

4000mg/kg

5

RSMS52

06

30

500mg/kg

4

RSMS53

06

28

500mg/kg

4

RSMS54

03

26

773mg/kg

4

RSMS55

04

25

500mg/kg

4

RSPS1

04

26

5008mg/kg

6

RSPS4

04

26

750mg/kg

4

RSPS6

05

23

500mg/kg

4

RSPS7

06

24

500mg/kg

4

RSPS10

04

22

500mg/kg

4

RSPS14

04

21

3000mg/kg

5

RSPS17

04

32

500mg/kg

4

RSPS18

05

31

2125mg/kg

5

RSPS21

04

29

1000mg/kg

4

RSPS23

04

28

500mg/kg

4

RSPS24

05

28

1000mg/kg

4

 

3.2. Docking Validation output:

Docking results were validated by redocking of co-crystallized ligand in the proposed protein structure. In this study comparable interactions were observed between the redocked ligand and protein as was observed in the original co-crystallized structure i.e., related orientations of the groups and binding interactions with reported residues. The RMSD(Root Mean Square Deviation) between the predicted conformation and the original conformation of compound as existed in the X-ray crystallographic structure was restricted to 0.30 Ǻ in our docking protocol. 6B1E showing RMSD of 1.9176 Ǻ calculated by superimposition tool of Schrodinger.

 

4.0 RESULTS AND DISCUSSION:

Proteins that have an amino acid sequence with proline or alanine at the N-terminal penultimate position are specifically inactivated by the proteolytic enzyme DPP-IV. S1, S2, and S3 are the three distinct binding pockets or active sites on DPP-IV. While the S2 active site (Glu205, Glu206, and Tyr662) is located close to the cavity of DPP-IV, the S1 active site (Ser630, Asn710, and His740) is made up of side chains of the catalytic triad involved in strong hydrophobic interactions. Larger groups are permitted outside the pocket by the S3 active site (Ser209, Arg358, and Phe357), whereas smaller groups are preferred in the inside position. By constructing salt bridges, DPP-4 inhibitors communicate with the S2 pocket at Glu205 and Glu206. The enzyme is significantly inhibited by this interaction. Interestingly, docking study revealed that API could bind to residues Glu206, Tyr662, Arg358 and Phe357 at the active sites of DPP-IV to dock into S2 and S3 pockets (Figures 3.1, 3.2 and 3.3). The nitrogen group is shown to be more active than an electron-releasing group when an electron-withdrawing group is added. The substituent group linked to the phenyl ring's lipophilic nature and electrical environment played a significant influence in the DPP-IV inhibitory effect. Resveratrol, luteolin, API, and flavones exhibit high affinity to the active site of DPP-IV because they have low Ki values to inhibit DPP-IV activity, according to a study by Fan et al. We assume that DPP-IV undergoes conformational changes as a result of API's attachment to the enzyme. A more stronger inhibitory action of API was shown by its lower binding energy in the current docking investigation compared to its derivatives.

 

5.0 CONCLUSIONS:

Target-based and ligand-based techniques, carried out by molecular modelling with the assistance of structural data, can greatly speed up drug discovery by giving Eight substances showed strong DPP-IV inhibitory activity: RSBS7, RSBS9, RSBS10, RSMS10, RSMS14, RSMS19, RSPS1, and RSPS25. Docking, in silico ADME, and toxicity study outcomes were also good for chemical synthesis. Apigenin's inclusion as an API and its replacement with an amine group were advantageous for binding and anti-diabetic efficacy. It is necessary to conduct more analysis of the specific mechanism pathway involved in an action.

 

6.0 REFERENCES:

1.      WHO, 2006, http://www.who.int/diabetes/en.

2.      Mentlein R, Gallwitz B, Schmidt WE Dipeptidyl-peptidase IV hydrolyses gastric inhibitory polypeptide, glucagon-like peptide-1(7–36)amide, peptide histidine methionine and is responsible for their degradation in human serum. Eur J Biochem.1993.214(3): 829–835. https://doi.org/10.1111/j.1432-1033.1993.tb17986.x 

3.      Zerilli T, Pyon EY Sitagliptin phosphate: a DPP-4 inhibitor for the treatment of type 2 diabetes mellitus. Clin Ther. 2007.29(12):2614–2634. https://doi.org/10.1016/j.clinthera.2007.12.034

4.      Deacon CF, Carr RD, Holst JJ DPP-4 inhibitor therapy: new directions in the treatment of type 2 diabetes. Front Bio sci.2008. 13(5):1780–1794. https://doi.org/10.2741/2799

5.      Choi JS, Islam MN, Ali MY, Kim EJ, Kim YM, Jung HA. Effects of C-glycosylation on Anti-diabetic, Anti-Alzheimer’s Disease and Anti-inflammatory Potential of Apigenin. 2016.64:27-33. https://doi.org/10.1016/j.fct.2013.11.020

6.      Ali F, Rahul, Naz F, Jyoti S, Siddique YH. Health Functionality of Apigenin: A Review. International Journal of Food Properties. 2017. 20(6):1197-238. https://doi.org/10.1080/10942912.2016.1207188

7.      Lee H, Kim BG, Kim M, Ahn JH. Biosynthesis of Two Flavones, Apigenin and Genkwanin in Escherichia coli. J Microbiol Biotechnol. 2015. 25(9): 1442-8 https://doi.org/10.4014/jmb.1503.03011

8.      Edmondson SD, Mastracchio A, Mathvink RJ et al (2S,3S)-3-amino-4-(3,3- difluoropyrrolidin-1-yl)-N,N-dimethyl-4-oxo-2-(4-[1,2,4]triazolo[1,5-a]-pyridin-6-ylphenyl) butanamide: a selective alpha-amino amide dipeptidyl peptidase IV inhibitor for the treatment of type 2 diabetes. J Med Chem. 2006.49(12):3614–3627.https://doi.org/10.1021/jm060015t

9.      Biftu T, Scapin G, Singh S et al Rational design of a novel, potent, and orally bioavailable cyclohexylamine DPP-4 inhibitor by application of molecular modeling and X- ray crystallography of sitagliptin. Bioorg Med Chem Lett 17. 2007.(12):3384–3387. https://doi.org/10.1016/j.bmcl.2007.03.095

10.   CiociolaAA ,CohenLB,Prasad KulkarniP Howdrugsare developed and approved by the FDA: current process and future directions. Am J Gastroenterol, 2014; 109(5): 620–623. https://doi.org/10.1038/ajg.2013.407

11.   Rasmussen HB, Branner S, WibergFC, Wagtmann NRCrystal structure of human dipeptidyl peptidase IV/CD26 incomplex with a substrate analog. Nat Struct Biol. 2009.10:19–25. https://doi.org/10.1038/nsb882

12.   Kulkarni, V.M., Design of New Chemical Entities as Therapeutic Agents. Indian Journal of Pharmaceutical Sciences. 1997;59(5),205.

 

 

 

Received on 06.08.2022            Modified on 09.10.2022

Accepted on 07.12.2022           © RJPT All right reserved

Research J. Pharm. and Tech 2023; 16(8):3535-3543.

DOI: 10.52711/0974-360X.2023.00584