Identification of Leads From the In-House Developed Molecules Targeting the Tumor Hypoxia Via the Inhibition of Hypoxia-Inducible Factor-1 Alpha (HIF-1α): Exploring the Anticancer Potential
摘要
The hypoxic sites within tumors are characterized by increased oxidative stress and inflammation, which cumulatively lead to tumor progression, metastasis, and the development of resistance to chemotherapy. Among various pathways and enzymatic systems associated with it, Hypoxia-Inducible Factor-1 alpha (HIF-1α) is a key regulator of the cellular response to low oxygen, commonly referred to as hypoxia. The HIF-1α degrades rapidly under normoxic conditions, whereas in the tumour microenvironment (TME) associated with hypoxia, it is linked to angiogenesis, glycolysis, cancer cell survival, and resistance to anticancer therapeutics
ObjectivesConsidering this, HIF-1α is a key druggable target, the inhibition of which could alter the TME and offer synergistic benefits with other anticancer drugs and targets
MethodsTo identify a plausible lead for the present research, we have employed a drug repurposing strategy using a pool of in-house-developed molecules. The molecules were screened using a high-throughput virtual screening approach followed by molecular docking, mechanics, and dynamics
ResultsThe collective in silico investigation led us to identify compound 4 as the top lead. The anticancer potential analysis revealed that compound 4 inhibited the proliferation of MDAMB-231 cells. Compound 4 exhibited a 2.1-fold increase in anticancer potential under hypoxic conditions and displayed an IC50 of 1.32 µM. The HIF-1α inhibitory assay further revealed HIF-1α inhibition with IC₅₀ values of 496.23 nM for LW6 and 514.13 nM for compound 4
ConclusionThe oxidative stress analysis revealed a sharp elevation in oxidative stress under hypoxic conditions, presumably due to the nitro group, which may undergo preferential bioreduction, thereby increasing oxidative stress and conferring a profound anticancer potential under such conditions.
Graphical Abstract