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.
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.
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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
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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