Molecular Simulation, Pharmacophore Mapping, and 3D QSAR Modeling on Chromene-Based SERDs.

INTRODUCTION

Estrogen receptor (ERα) is known to be a legitimate therapeutic target for the treatment of ER-positive breast cancer. Although selective estrogen receptor degraders (SERDs) like fulvestrant suppress ER signaling, their limited bioavailability challenges efficacy. Additionally, activating mutations in the ERα mediate resistance to endocrine therapy.

METHODS

To elucidate the structural activity relationship within a chromene-based scaffold, we conducted pharmacophore mapping and Gaussian field-based 3D QSAR modelling. The most active analogue was docked into the ERα ligand binding domain (PDB ID: 6V8T) and then subjected to molecular dynamics simulations and molecular mechanics generalized born surface area (MM/ GBSA) binding-free energy calculations.

RESULTS

The pharmacophore mapping produces a five-point hypothesis, of which HHHRR_1 achieved the highest survival score (6.423) with a fitness score close to 3. Using HHHRR_1, a Gaussian Field-based 3D QSAR model with strong internal predictivity (cross-validated q2 is 0.8) and an excellent external validation was developed (r2 is 0.94). Compound 18 demonstrated stable binding in the ERα pocket with a ΔGbind MM/GBSA value of -67.03 kcal/mol, outperforming fulvestrant with a ΔGbind MM/GBSA of -64.76 kcal/mol. These findings suggest compound 18 engages critical ERα interactions more effectively with the target.

DISCUSSION: The integrated modelling approach, like pharmacophore mapping, 3D QSAR, docking, and molecular dynamics, elucidated molecular characteristics essential for potent ERα degradation. Compound 18, having superior binding affinities, implies that optimizing these features on a chromene scaffold can yield new oral SERDs with enhanced therapeutic potential.

CONCLUSION

Based on the results of pharmacophore mapping, docking, molecular simulation, and 3D QSAR studies, we have designed a new set of chromene scaffold-based derivatives as potent SERDs along with their predicted activity.