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Computational Screening of Some Phytochemicals to Identify Best Modulators for Ligand Binding Domain of Estrogen Receptor Alpha.
Alagarsamy, Veerachamy; Sundar, Pottabathula Shyam; Solomon, Viswas Raja; Murugesan, Sankaranarayanan; Muzaffar-Ur-Rehman, Mohammed; Kulkarni, Vishaka Sumant; Sulthana, Mohaideen Thasthagir; Narendhar, Bandi; Sabarees, Govindraj.
Affiliation
  • Alagarsamy V; Medicinal Chemistry Research Laboratory, MNR College of Pharmacy, Sangareddy 502 294, Gr. Hyderabad, India.
  • Sundar PS; Department of Pharmaceutical Chemistry, Vasantidevi Patil Institute of Pharmacy, Kodoli, Panahala, Kolhapur, Maharashtra 416114, India.
  • Solomon VR; Medicinal Chemistry Research Laboratory, MNR College of Pharmacy, Sangareddy 502 294, Gr. Hyderabad, India.
  • Murugesan S; Department of Pharmacy, BITS Pilani, Pilani Campus, Pilani 333031, India.
  • Muzaffar-Ur-Rehman M; Department of Pharmacy, BITS Pilani, Pilani Campus, Pilani 333031, India.
  • Kulkarni VS; Medicinal Chemistry Research Laboratory, MNR College of Pharmacy, Sangareddy 502 294, Gr. Hyderabad, India.
  • Sulthana MT; Medicinal Chemistry Research Laboratory, MNR College of Pharmacy, Sangareddy 502 294, Gr. Hyderabad, India.
  • Narendhar B; Medicinal Chemistry Research Laboratory, MNR College of Pharmacy, Sangareddy 502 294, Gr. Hyderabad, India.
  • Sabarees G; Department of Pharmaceutical Chemistry, SRM College of Pharmacy, SRM Institute of Science and Technology, Kattankulathur, Chennai 603203, India.
Curr Pharm Des ; 30(20): 1599-1609, 2024.
Article in En | MEDLINE | ID: mdl-38698754
ABSTRACT

OBJECTIVE:

The peculiar aim of this study is to discover and identify the most effective and potential inhibitors against the most influential target ERα receptor by in silico studies of 45 phytochemicals from six diverse ayurvedic medicinal plants.

METHODS:

The molecular docking investigation was carried out by the genetic algorithm program of AutoDock Vina. The molecular dynamic (MD) simulation investigations were conducted using the Desmond tool of Schrödinger molecular modelling. This study identified the top ten highest binding energy phytochemicals that were taken for drug-likeness test and ADMET profile prediction with the help of the web-based server QikpropADME.

RESULTS:

Molecular docking study revealed that ellagic acid (-9.3 kcal/mol), emodin (-9.1 kcal/mol), rhein (-9.1 kcal/mol), andquercetin (-9.0 kcal/mol) phytochemicals showed similar binding affinity as standard tamoxifen towards the target protein ERα. MD studies showed that all four compounds possess comparatively stable ligand-protein complexes with ERα target compared to the tamoxifen-ERα complex. Among the four compounds, phytochemical rhein formed a more stable complex than standard tamoxifen. ADMET studies for the top ten highest binding energy phytochemicals showed a better safety profile.

CONCLUSION:

Additionally, these compounds are being reported for the first time in this study as possible inhibitors of ERα for treating breast cancer, according to the notion of drug repurposing. Hence, these phytochemicals can be further studied and used as a parent core molecule to develop innovative lead molecules for breast cancer therapy.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Estrogen Receptor alpha / Molecular Docking Simulation / Phytochemicals Limits: Humans Language: En Journal: Curr Pharm Des Journal subject: FARMACIA Year: 2024 Document type: Article Affiliation country: India Country of publication: United Arab Emirates

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Estrogen Receptor alpha / Molecular Docking Simulation / Phytochemicals Limits: Humans Language: En Journal: Curr Pharm Des Journal subject: FARMACIA Year: 2024 Document type: Article Affiliation country: India Country of publication: United Arab Emirates