Turning down PI3K/AKT/mTOR signalling pathway by natural products: an in silico multi-target approach

The PI3K/AKT/mTOR pathway is a significant target for cancer drug discovery. Many efforts have focused on discovering new inhibitors against key kinase proteins involved in this pathway for cancer treatment. PI3K/mTOR dual inhibitors, such as PKI-179, have been reported to be more effective than agents that act only on a single protein target. The present computational study aimed to discover triple target inhibitors against PI3K, AKT, and mTOR proteins. Accordingly, the PI3K protein bound with the ligand was used as input for e-pharmacophore modelling to generate the pharmacophore hypothesis and then screened for a library of 270,540 natural products from the Zinc database resulting in 57,220 compounds that matched the hypothesis. These compounds were then docked into the active site of PI3K, resulting in 292 compounds with better docking scores than the co-crystallized ligand. These compounds were re-docked into AKT and mTOR proteins. Besides, MM-GBSA binding free energy calculations, MD simulations, and ADMET prediction were carried out, leading to 5 potential triple-target inhibitors namely, ZINC000014644152, ZINC000014760695, ZINC000014644839, ZINC000095099451, and ZINC000005998557. In conclusion, these inhibitors may be possible leads for inhibiting PI3K/AKT/mTOR pathway, and they may be further evaluated in vitro and clinically as anticancer agents.

Computational investigations of flavonoids as ALDH isoform inhibitors for treatment of cancer

Human aldehyde dehydrogenases (ALDHs) are a group of 19 isoforms often overexpressed in cancer stem cells (CSCs). These enzymes play critical roles in CSC protection, maintenance, cancer progression, therapeutic resistance, and poor prognosis. Thus, targeting ALDH isoforms offers potential for innovative cancer treatments. Flavonoids, known for their ability to affect multiple cancer-related pathways, have shown anticancer activity by downregulating specific ALDH isoforms. This study aimed to evaluate 830 flavonoids from the PubChem database against five ALDH isoforms (ALDH1A1, ALDH1A2, ALDH1A3, ALDH2, ALDH3A1) using computational methods to identify potent inhibitors. Extra precision (XP) Glide docking and MM-GBSA free binding energy calculations identified several flavonoids with high binding affinities. MD simulation highlighted flavonoids 1, 2, 18, 27, and 42 as potential specific inhibitors for each isoform, respectively. Flavonoid 10 showed high binding affinities for ALDH1A2, ALDH1A3, and ALDH3A1, emerging as a potential multi-ALDH inhibitor. ADMET property evaluation indicated that the promising hits have acceptable drug-like profiles, but further optimization is needed to enhance their therapeutic efficacy and reduce toxicity, making them more effective ALDH inhibitors for future cancer treatment.