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ORIGINAL ARTICLE
Year : 2022  |  Volume : 13  |  Issue : 3  |  Page : 207-215  

Dipeptidyl peptidase IV inhibition of phytocompounds from Artocarpus champeden (Lour.) Stokes: In silico molecular docking study and ADME-Tox prediction approach


1 Department of Pharmaceutical Analysis, Faculty of Pharmacy and Science, Universitas Muhammadiyah Prof. Dr. HAMKA, South Jakarta, Indonesia
2 Department of Pharmaceutical Sciences, Faculty of Pharmacy, Universitas Mulawarman, Samarinda, East Kalimantan, Indonesia
3 Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Surabaya, Surabaya, Indonesia
4 Research Center for Pre-Clinical and Clinical Medicine, Indonesian Research and Innovation Agency, East Jakarta, Jakarta, Indonesia
5 Department of Cosmetology, Engineering Faculty, Universitas Negeri Jakarta, East Jakarta, Jakarta, Indonesia
6 Department of Medical Chemistry, Faculty of Medicine, Universitas Indonesia, South Jakarta, Indonesia
7 Laboratory of Biopharmacy and Pharmacology, Faculty of Pharmacy, Universitas Muslim Indonesia, Makassar, South Sulawesi, Indonesia
8 Department of Community Medicine, Faculty of Medicine, and Research Center of Natural Products from Tropical Rainforest, Universitas Mulawarman, Samarinda, East Kalimantan, Indonesia

Date of Submission14-May-2022
Date of Decision18-May-2022
Date of Acceptance23-May-2022
Date of Web Publication05-Jul-2022

Correspondence Address:
Dr. Islamudin Ahmad
Jl. Kuaro Gn. Kelua, Samarinda 75119 East Kalimantan
Indonesia
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/japtr.japtr_376_22

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  Abstract 


The present study examines the potential activity prediction based on free binding energy (ΔG) and interaction confirmation of phytocompounds from Artocarpus champeden (Lour.) Stokes with macromolecule protein receptor of dipeptidyl peptidase IV (DPP-IV) using in silico molecular docking studies and physicochemical and pharmacokinetic properties (ADME-Tox) prediction approaches. The active subsites of the DPP-IV receptor macromolecule protein Protein Data Bank (ID: 1 × 70) were docked using Autodock v4.2.6 (100 docking runs). A grid box of 52 × 28 × 26 Å points spaced by 0.37 Å was centered on the active site of x = 40.926 Å; y = 50.522 Å; z = 35.031 Å. For ADME-Tox prediction, Swiss ADME online-based application programs were used. The results show that 12 pythocompounds from A. champeden have the potential as DPP-IV inhibitors based on ΔG value and interaction conformation. There are five pythocompounds with lower ΔG values and inhibition constants than the native ligand and seven pythocompounds with ΔG values and inhibition constants close to the native ligand. The 12 compounds form an interaction conformation at the active subsites of the DPP-IV receptor. At the same time, the results of the ADME-Tox prediction analysis showed that the 12 compounds had different physicochemical and pharmacokinetic properties.

Keywords: ADME-tox, Artocarpus champeden (Lour.) stokes, dipeptidyl peptidase IV, free binding energy, in silico molecular docking


How to cite this article:
Supandi S, Wulandari MS, Samsul E, Azminah A, Purwoko RY, Herman H, Kuncoro H, Ibrahim A, Silfi Ambarwati NS, Rosmalena R, Azizah RN, Paramita S, Ahmad I. Dipeptidyl peptidase IV inhibition of phytocompounds from Artocarpus champeden (Lour.) Stokes: In silico molecular docking study and ADME-Tox prediction approach. J Adv Pharm Technol Res 2022;13:207-15

How to cite this URL:
Supandi S, Wulandari MS, Samsul E, Azminah A, Purwoko RY, Herman H, Kuncoro H, Ibrahim A, Silfi Ambarwati NS, Rosmalena R, Azizah RN, Paramita S, Ahmad I. Dipeptidyl peptidase IV inhibition of phytocompounds from Artocarpus champeden (Lour.) Stokes: In silico molecular docking study and ADME-Tox prediction approach. J Adv Pharm Technol Res [serial online] 2022 [cited 2022 Aug 14];13:207-15. Available from: https://www.japtr.org/text.asp?2022/13/3/207/349839




  Introduction Top


Artocarpus champeden (Lour.) Stokes belongs to the Moraceae family, locally known as “Chempedak,” an annual fruit plant with a tall, strong woody tree. This fruit plant is a native that grows wild in tropical forests, mainly in India, Vietnam, Myanmar, Thailand, Malaysia, and Indonesia.[1] This plant is widespread in Sumatran, Kalimantan, Sulawesi, Maluku, and West Papua in Indonesia. Traditionally, this plant treats diarrhea, fever, malaria, and diabetes mellitus. However, no scientific evidence has been reported of A. champeden as a potential antidiabetic agent to the best of our knowledge. Therefore, our team is interested in researching the potential of this plant.

Meanwhile, several studies have isolated and identified phytocompounds found in A. champeden.[2],[3],[4],[5] However, data regarding the potential pharmacological activity of phytocompounds from A. champeden is still minimal, mainly as antidiabetic, whereas it has traditionally been used for generations. This series of work fills research gaps by examining the potential activity and interactions of phytocompound from A. champeden using the in silico molecular docking study and ADME-Tox prediction approach.

In silico molecular docking is a modeling method based on computer simulation to search for possible bindings of the test ligand and receptor-interacting under topographical conditions and the match between both molecules with the conformation that has the best interaction.[6],[7],[8],[9] ADME-Tox prediction is performed using an online-based application such as SWISSADME, which aims to study physicochemical and pharmacokinetic properties.[10],[11] Some studies that have been reported successfully related to the use of these application programs include ADMET analysis of three relevant natural components of the medicinal plant,[12] ADMET prediction of mangosteen derivates,[13] ADME-Tox prediction of phytocompounds from Merremia peltata,[14] and drug-likeness prediction of bioactive compounds from Punica granatum L.[15]

The current study predicts the interaction conformation and the potential activity of phytocompounds from A. champeden with macromolecules protein of dipeptidyl peptidase IV (DPP-IV) as a receptor target, hoping to fill research gaps on an in silico assay scale, thereby accelerating the development of further studies.


  Materials and Methods Top


Hardware and software

The analysis of molecular docking was carried out by a computer HP Pavilion, Autodock-v4.2.6, AutodockTools, ChemOffice-Pro-v15.00 PerkinElmer, Phyton Molecular Viewer (PMV-1.5.6), OpenBabel GUI, Accelrys Discovery Studio Visualizer 4.0. Software, and SWISSADME (http://www.swissadme.ch/) online tools program.

In silico molecular docking study

Native ligand and receptor preparation

The protein structure of macromolecule DPP-IV complexes with native ligand sitagliptin Protein Data Bank (PDB ID: 1 × 70, with 2.1Å resolution) was downloaded from the Research Collaboratory for Structural Bioinformatics PDB via the website: https://www.rcsb.org/. Macromolecule DPP-IV receptors and native ligand were separated using PMV-1.5.6. Gasteiger charges were added to each ligand atom. Water molecules were eliminated from each protein receptor and protonated. Then, a native ligand and protein receptor was prepared and converted in the PDBQT format (.pdbqt) using AutodockTools and OpenBabel programs.[7],[16]

Preparation of phytocompounds as a test ligand

In this study, the structure of phytocompounds from A. champeden was collected from some literature,[2],[3],[4],[5] as shown in [Figure 1]. Each phytocompounds were prepared as a test ligand using ChemDraw® Pro v15 to build a two-dimension structure of each phytocompounds. Chem three-dimensional (3D)® Pro v15 was converted to a 3D structure, minimized using the MMFF94 force field, and saved to PDB (.pdb).[8]
Figure 1: 2D structure of phytocompounds from Artocarpus champeden. 2D: Two-dimension

Click here to view


Analysis of in silico molecular docking

According to its protocols, the analysis of in silico molecular docking of 41 phytocompounds from A. champeden was conducted using Autodock 4.2.6.[7] Using the Lamarckian Genetic Algorithm (LGA) based on the lowest free energy of binding (ΔG), the native ligand was simulated in various conformations for best binding to the protein DPP-IV receptor binding site. The parameters of LGA were: elitism of 1, crossover rate of 0.8, the mutation rate of 0.02, the population size of 150, energy evaluation of 2500,000, and 100 runs. Moreover, the grid box comprised of 52 × 28 × 26Å points spaced by 0.375Å was centered on the active site of x = 40.926Å; y = 50.522Å; z = 35.031Å (XYZ-coordinates) according to a previous study.[17] The grid condition was used for molecular docking analysis of 41 phytocompounds from A. champeden. The results of molecular docking data were visualized using Accelrys Discovery Studio Visualizer-4.0.[18]

Determination of ADME-tox prediction

According to the literature, ADME-Tox prediction of the best docking results was determined using SWISSADME online tools.[11] Briefly, each phytocompounds (PDB format) structure was converted in SMILES format using OpenBabel GUI. SWISSADME online tools program was used to determine ADME-Tox of 12 phytocompounds.[18]


  Results Top


In silico molecular docking study

Validation of molecular docking method

In the present study, the docking results of the native ligand (sitagliptin) demonstrated a root mean square deviation (RMSD) value of 0.55 Å (<2 Å) with a binding free energy (ΔG) value of −8.59 kcal/mol (inhibition constant of 508.58 nM) and clusters of 82% for 100 times running. [Figure 2] shows that the overlay position between the docking results and the original native ligand does not significantly different positions according to the RMSD value <2 Å, indicating that the grid size and grid center of the docking process was different valid.
Figure 2: Visualization of original (yellow) and re-docked (green) native ligand overlay position

Click here to view


The docking results of 41 phytocompounds from A. champeden in [Table 1] show that five compounds had a lower ΔG value and inhibition constant than the native ligand. Seven compounds have ΔG value and inhibition constant close to the native ligand.
Table 1: Docking results characteristic and ligand-receptor interaction

Click here to view


Studies on molecular interaction

[Figure 3] demonstrates visualization of native ligand interaction with active site residue of DPP-IV macromolecule receptors.
Figure 3: Visualization of (a) two-dimension and (b) three-dimension of molecular interaction between native ligand against macromolecule of DPP-IV receptor (PDB ID: 1X70). PDB: Protein Data Bank, DPP-IV: Dipeptidyl peptidase IV

Click here to view


In [Figure 4], it was shown that 12 phytocompounds have conformational interactions with subsites of the DPP-IV receptor.
Figure 4: Interaction visualization of twelve best docking results of phytocompounds from Artocarpus champeden against macromolecule of DPP-IV receptor. DPP-IV: Dipeptidyl peptidase IV

Click here to view


ADME-tox prediction

The ADME-Tox properties prediction of selected 12 phytocompounds from A. champeden according to the molecular docking study is presented in [Table 2]. The physicochemical properties prediction provides an overview of bioavailability levels of phytocompounds, as shown in [Figure 5].
Figure 5: Bioavailability radar representation of the 12 best docking findings of Artocarpus champeden phytocompounds

Click here to view
Table 2: ADME-Tox properties prediction of twelve best docking results using SWISSADME online tools software

Click here to view



  Discussion Top


The result of re-docking of native ligand indicates the level of validity of grid box and box size used with an RSMD value of 0.55 Å (<2 Å), which refers to the previous study,[17],[19] indicating that the grid size and grid center of the docking process was different valid. The docking result demonstrated native ligand and test ligand interaction with the active site of DPP-IV receptor macromolecules. The DPP-IV receptor has some active site areas at subsites area of amino acid residues known as S1, S1', S2', S2, and S2 extensive.[20],[21],[22] The test ligand activity can generally be predicted based on interactions at subsites (S1, S2, and S2 ext.) of the DPP-IV receptor.[21],[22]

In this study, it was found that five phytocompounds had lower ΔG values than the native ligand, including 24-methylencycloartanon, cycloartenon, cycloartenol, β-sitosterol, and cycloeucalenol, and seven phytocompounds that had an ΔG value close to the native ligand include cudraflavon C, artoindonesianin A, 5'-hydroxycudraflavon A, artoindonesianin B, artoindonesianin R, artoindonesianin A3, and cyclocommunim. In addition, the 12 phytocompounds showed conformational interactions that were specific to the active subsite of the DPP-VI receptor. Each amino acid residue of the active subsites of the DPP-IV receptor can form seven different interaction conformations with the test ligand.[23]

The ADME-Tox properties play a crucial role in the drug industry. They are generally used in drug development, mainly using the computer-aided drug design approach to reduce unwanted effects. 24-Methylencycloartanon has an MW value that is in the unacceptable range, while the others are in the acceptable range. Artoindonesianin A, artoindonesianin A3, artoindonesianin B, artoindonesianin R, cudraflavon C, cyclocommunin, and 5'-hydroxycudraflavon A obey the Lipinski rule, except six other compounds (RO5 value >0).[24] All phytocompounds showed the H-bond (acceptor and donor) and skin permeant value in the acceptable range. Based on the topological polar surface area (TPSA) value, which reveals that 24-methylencycloartanon, β-sitosterol, cycloartenol, cycloartenon, and cycloeucalenol have an excellent brain penetration (TPSA <70Å2), and seven other compounds have good gastrointestinal penetration (with TPSA <140Å2).[25] XLOGP3 shows the lipophilicity and polarity value prediction of phytocompounds. The higher the value, the lower the polarity.[26],[27] ESOL indicates the solubility levels of phytocompounds. The lower the values,[28] the lower solubility.[29] [Figure 5] demonstrated that the phytocompounds of artonindonesianin (A3, B, and R), β-sitosterol, cycloartenol, and 5'-hydroxycudraflavon A were the acceptable/optimal range of ADME-Tox/physicochemical space for oral bioavailability.


  Conclusion Top


Analysis of in silico molecular docking and ADME-Tox prediction were performed to study the potential pharmacological activity of phytocompounds from A. champeden as DPP-IV inhibitors. Our findings show that almost all phytocompounds have potential interaction with the receptor at the active subsites. Nevertheless, 12 phytocompounds have the most similar interaction with the DPP-IV receptor and have different physicochemical properties for bioavailability and pharmacokinetics prediction.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
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    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5]
 
 
    Tables

  [Table 1], [Table 2]



 

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