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Gene & Protein in Disease Effect of phytochemicals in diabetes

of proteins . The target protein nature was determined by of a ligand at the target region, chances of passage of the
[37]
the SOSUI (engine ver. 1.11) server . The SWISS-MODEL blood-brain barrier, toxicity, malignancy, etc.
[38]
server website was used for downloading a protein crystal
three-dimensional (3D) structure . SWISS-MODEL 2.6. Leads groundwork for docking
[35]
is a comparison modeling assistant processor and was Avogadro 1.2.on-win 32 was applied for force field and
applied to overlap proteins to assume its structural geometry maximization of ligand . Hydrogen and charge
[48]
sequence or arrangement, sequence identity, coverage, were then added with the help of The UCSF Chimera
model quality estimation (QMEAN SCORES), process, tool . Torsion or tortuosities and level of freedom,
[42]
and resolution facts of the target protein. Ramachandran followed by stereo-chemical distinction of ligands, were
Z-score and Ramachandran plot ZLab server were used to accustomed, Gasteiger charges were considered, and the
determine protein structure along with phi-psi background PDB file was saved.
[39]
probabilities . CASTp 3.0 software was used to identify
[40]
active sites and functional domains of targets . 2.7. Examination of target-lead interaction/docking
studies
2.3. Target protein preparation The finally prepared PDB file of the target protein and
Swiss-Pdb Viewer (aka Deep View) version 4.1.1 was applied lead was opened in the UCSF Chimera tool. The Vina tool
to reduce the target protein’s energy . UCSF Chimera tool was used to calculate the potential energy of the docked
[41]
is an extensible molecular modeling system and was used compound and the file was saved in PDBQT format.
for the addition of hydrogen and charges, to adjust atomic- BIOVIA Discovery Studio Visualizer 4.5 was used to
[49]
subatomic torsion, degree of free will/freedom and stereo- visualize target-ligand interactions . With the help of the
chemical difference, and Gasteiger charges . Auto Dock Discovery studio bonds detail, two-dimensional (2D) and
[42]
Vina and Chimera were used for grid preparation with 3D complex structures were analyzed.
20 Å × 20 Å × 20 Å grid dimensions , and the X, Y, and Z
[43]
coordinates of the grid box were −76.407, −36.793, 13.714 3. Results
for AMPK1, respectively, and −36.303, −82.337, −22.555 3.1. Target protein examination
for AMPK2, respectively .
[40]
To prepare a strong and stable model of the target protein,
2.4. The ligand library preparation the selected targets and their properties were examined
critically. 5’-AMPK protein was selected as a target, and
An extensive literature survey related to C. roseus its catalytic subunits AMPK1 and AMPK2 sequence and
revealed its major antihyperglycemic properties related to active site were taken from and analyzed by UniProt site
alkaloids [29,30,44] . The PubChem database was used to search (Table 1). AMPK1 is a globular protein with an enzyme
for alkaloid structure and control drug metformin. Eighty- commission number (EC) of 2.7.11.1 , whereas AMPK2 is
[38]
five compounds were selected from the database to prepare a transmembrane protein with an EC number of 2.7.11.1 .
[50]
a library and metformin (CID: 4091) as a control drug.
Followed by SDF, files were converted and saved in PDB The online tool ProtPram was used for AMPK1 and AMPK2
files by online software, Open Babel . sequence analysis and their physicochemical properties
[45]
identification (Table 1). ProtPram grand average of
2.5. Absorption, distribution, metabolism, hydropathicity (GRAVY) value indicates the globular (<0 for
excretion, and toxicity test hydrophilic protein) or membranous (>0 for hydrophobic
Absorption and assimilation through the mouth and protein) nature of the protein. The value for AMPK1 GRAVY
digestive tract, distribution, metabolism, excretion, was −0.461, whereas the value for AMPK2 GRAVY was
and toxicity (ADMET) test reveal the pharmacokinetic −0.295. The SOPMA tool was used to know about the target
properties of compounds, that is, what the body does with proteins’ secondary structures (Table 2). AMPK1 has more
compounds. The application programs OSIRIS Property α-helixes but fewer β turns and random coil than AMPK2.
Explorer and DruLiTo software were used to test the The soluble (AMPK1) and transmembrane (AMPK2) nature
ADMET property of all library compounds [46,47] . According of the target was identified by SOSUI prediction, software
to the drug-likeness rules, the log S value estimates solubility details are given in Table 3.
whereas the cLogP value tells about the Lipinski rule, total The soluble (AMPK1) and transmembrane (AMPK2)
polar surface area (TPSA), molecular mass, drug’s likeness nature of the target was identified by SOSUI prediction,
properties (functional portion of ligand), and drug score. software details are given in Table 3. Followed by validation
The pharmacodynamics activities of a compound (what the of the target protein was done by the Ramachandran
drug does in the body) are predicted by the bioavailability plot, which shows phi (φ) and psi (ψ) angle and protein

Volume 2 Issue 3 (2023) 3 https://doi.org/10.36922/gpd.0927