Identification and in silico screening of natural phloroglucinols as potential PI3Kα inhibitors: A computational approach for drug discovery

Abstract

Breast cancer is the biggest cause of death among women worldwide. Natural chemicals from medicinal plants offer promise for cancer therapy. This research screens 29 Dryopteris species plant-derived chemicals, mostly phloroglucinols, for breast cancer therapy potential. First, we used Gaussian09 and DFT/B3LYP/6-311+G(d, p) calculations to evaluate compound stability and reactivity. We conducted molecular docking experiments to identify drugs with high binding affinity for the PI3Kα protein’s active pocket. DJ1–DJ22 were found to be the most effective PI3Kα inhibitors, with energies ranging from −8.0 to −9.2 kJ/mol. From in silico pharmacokinetic and bioactivity screening, DJ3, DJ7, and DJ18 were identified as promising PI3Kα inhibitors. PI3Kα backbone stability was tested in a water model using molecular dynamics simulations employing DJ3, DJ7, DJ18, and Trastuzumab as a pharmacological reference. Synthesis of target-hit DJ3, DJ7, and DJ18 derivatives may lead to breast cancer drug-like molecules for related cancers. The work uses in silico methods to find natural phloroglucinols for breast cancer therapy, enabling new chemotherapeutic drugs.

Keywords

• breast cancer
• phloroglucinols
• dryopteris species
• dft
• molecular docking
• molecular dynamics