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QSAR, ADMET In Silico Pharmacokinetics, Molecular Docking and Molecular Dynamics Studies of Novel Bicyclo (Aryl Methyl) Benzamides as Potent GlyT1 Inhibitors for the Treatment of Schizophrenia

Mohamed El Fadili, Mohammed Er-Rajy, Mohammed Kara, Amine Assouguem, Assia Belhassan, Amal Alotaibi, Nidal Naceiri Mrabti, Hafize Fidan, Riaz Ullah, Sezai Ercişli, Sara Zarougui, Menana Elhallaoui

PHARMACEUTICALS Cilt 15 · Sayı 6 · 01.06.2022
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Özet

Forty-four bicyclo ((aryl) methyl) benzamides, acting as glycine transporter type 1 (GlyT1) inhibitors, are developed using molecular modeling techniques. QSAR models generated by multiple linear and non-linear regressions affirm that the biological inhibitory activity against the schizophrenia disease is strongly and significantly correlated with physicochemical, geometrical and topological descriptors, in particular: Hydrogen bond donor, polarizability, surface tension, stretch and torsion energies and topological diameter. According to in silico ADMET properties, the most active ligands (L6, L9, L30, L31 and L37) are the molecules having the highest probability of penetrating the central nervous system (CNS), but the molecule 32 has the highest probability of being absorbed by the gastrointestinal tract. Molecular docking results indicate that Tyr124, Phe43, Phe325, Asp46, Phe319 and Val120 amino acids are the active sites of the dopamine transporter (DAT) membrane protein, in which the most active ligands can inhibit the glycine transporter type 1 (GlyT1). The results of molecular dynamics (MD) simulation revealed that all five inhibitors remained stable in the active sites of the DAT protein during 100 ns, demonstrating their promising role as candidate drugs for the treatment of schizophrenia.

Anahtar kelimeler

DESIGN ABSORPTION DERIVATIVES Molecular docking DISCOVERY QSAR drug-likeness schizophrenia PREDICTION ADMET ALGORITHM GlyT1 DAT MD FORCE-FIELD

Atıf için künye

El Fadili, M., Er-Rajy, M., Kara, M., Assouguem, A., Belhassan, A., Alotaibi, A., Mrabti, N. N., Fidan, H., Ullah, R., Ercişli, S., Zarougui, S., & Elhallaoui, M. (2022). QSAR, ADMET In Silico Pharmacokinetics, Molecular Docking and Molecular Dynamics Studies of Novel Bicyclo (Aryl Methyl) Benzamides as Potent GlyT1 Inhibitors for the Treatment of Schizophrenia. PHARMACEUTICALS, 15(6). https://doi.org/10.3390/ph15060670

BibTeX
@article{elfadili2022-264585,
  author = {El Fadili, Mohamed and Er-Rajy, Mohammed and Kara, Mohammed and Assouguem, Amine and Belhassan, Assia and Alotaibi, Amal and Mrabti, Nidal Naceiri and Fidan, Hafize and Ullah, Riaz and Ercişli, Sezai and Zarougui, Sara and Elhallaoui, Menana},
  title = {QSAR, ADMET In Silico Pharmacokinetics, Molecular Docking and Molecular Dynamics Studies of Novel Bicyclo (Aryl Methyl) Benzamides as Potent GlyT1 Inhibitors for the Treatment of Schizophrenia},
  journal = {PHARMACEUTICALS},
  year = {2022},
  volume = {15},
  number = {6},
  issn = {1424-8247},
  doi = {10.3390/ph15060670},
  url = {https://akademik.atauni.edu.tr/yayinlar/264585-qsar-admet-in-silico-pharmacokinetics-molecular-docking-and-molecular-dynamics}
}