Structure-Based In Silico Investigation of Agonists for Proteins Involved in Breast Cancer

Area of Science:

• Phytochemistry
• Computational Biology
• Oncology

Background:

• Cancer is a leading global cause of mortality, necessitating novel, cost-effective treatments.
• Current cancer therapies have limitations and high costs, driving the search for alternatives.

Purpose of the Study:

• To identify potential novel anti-breast cancer compounds from selected medicinal plants.
• To screen and evaluate compounds against key breast cancer targets using computational methods.

Main Methods:

• Selected 62 compounds from five medicinal plants (Tinospora cordifolia, Ocimum tenuiflorum, Podophyllum hexandrum, Andrographis paniculata, Beta vulgaris).
• Applied Lipinski's rule for drug-likeness, followed by molecular docking and dynamics studies against HER4/ErbB4 kinase and ERα receptors.
• Screened 44 compounds against two breast cancer-associated proteins.

Main Results:

• Identified isocolumbin, isopropylideneandrographolide, and 14-acetylandrographolide as potential lead compounds.
• These compounds demonstrated promising interactions with HER4/ErbB4 kinase and ERα breast cancer receptors.
• Computational screening identified specific plant-derived molecules with therapeutic potential.

Conclusions:

• Isocolumbin, isopropylideneandrographolide, and 14-acetylandrographolide are promising lead compounds for breast cancer therapy.
• Further in vitro studies are essential to validate the efficacy of these identified compounds.
• This study highlights the potential of medicinal plants in discovering new anti-cancer agents.