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Potensi anti-kanker payudara tanaman songga (Strychnos lucida R.Br): Tinjauan interaksi molekuler terhadap reseptor estrogen-α in silico Muhammad Andre Reynaldi; Arif Setiawansyah
Sasambo Journal of Pharmacy Vol. 3 No. 1 (2022): April
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/sjp.v3i1.149

Abstract

Songga (Styrchnos lucida R.Br) is a plant that has potential to be developed as an anti-breast cancer against. This study was conducted to predict the secondary metabolite derived from songga, which potential as anti-breast cancer through inhibition of estrogen receptor-α. A molecular docking study was carried out using Autodock Vina assisted by AutodockTool and Biovia Discovery Studio. The study used estrogen receptor-α as a protein and ten compounds from songga as ligands. The 3D structure of estrogen receptor-α and ten ligands were obtained from Protein Data Bank and the PubChem database. The result revealed that strychnine N-oxide is the compound that has the lowest free binding energy and inhibition constant with the value 9.6 kcal/mol and 0.09 µM, respectively. This indicated that strychnine N-oxide has an excellent affinity for estrogen receptor-α. Thus, this compound is predicted to inhibit the estrogen receptor-α and can be developed as anti-breast cancer. However, further investigations such as molecular dynamics simulation, in vitro and in vivo assays should be undertaken.
Molecular docking-based virtual screening of antidiabetic agents from Songga (Strychnos lucida R.Br.): an Indonesian native plant Arif Setiawansyah; Muhammad Andre Reynaldi; Daryono Hadi Tjahjono; Sukrasno
Current Research on Bioscences and Biotechnology Vol. 3 No. 2 (2022)
Publisher : Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/crbb.2022.3.2/82KYTCPW

Abstract

This study was carried out to predict the compounds derived from Songga that have potential as antidiabetic and predict their mechanism of action on various pathways of glucose regulation in diabetes mellitus by molecular docking. Molecular docking-based virtual screening was done by using AutoDock Vina software assisted by AutoDockTools. The test compounds used for virtual screening were obtained from literature studies and were combined with Lipinski’s rule to select the compounds for the prediction of lead candidates that can be used in oral administration. The receptors used in this study were human aldose reductase, human maltase-glucoamylase, PPAR-gamma, pancreatic beta-cell SUR1, and human DPP-IV. The validation of the molecular docking method of five target receptors showed that RMSD values of human aldose reductase, human maltase-glucoamylase, PPAR-gamma, pancreatic beta-cell SUR1, and human DPP-IV were 0.6446 Å, 1.8668 Å, 0.2527 Å, 1.7452 Å, and 1.7439 Å, respectively. From the molecular docking-based virtual screening, we discovered that for each target protein, there were one to three optimal compounds that have the best interaction in our investigation. Those compounds were chlorogenic acid on human aldose reductase, phyllamycin A, chlorogenic acid, and brucine N-oxide on human maltase-glucoamylase, phyllamycin A on PPAR-gamma, strychnine N-oxide on pancreatic beta-cell SUR1 and strychnine on human DPP-IV with binding affinity value of -9.9 kcal/mol, -7.6 kcal/mol, -9.9 kcal/mol, -8.8 kcal/mol, and -6.2 kcal/mol, respectively. Several compounds are predicted to have potential to be developed as antidiabetic agents. However, further laboratory investigations like in vitro and in vivo assays need to be conducted.