Computer-designed acridine compounds show predicted binding to breast cancer estrogen receptor

Estrogen receptor-alpha (ERα) remains one of the most consequential molecular targets in hormone-dependent breast cancer, driving tumour cell proliferation, survival and metastatic spread in roughly 70% of cases. Yet the endocrine therapies built around it — selective estrogen receptor modulators, selective estrogen receptor degraders and aromatase inhibitors — are steadily undermined by adverse effects and acquired resistance. A new computational study now reports the structure-based design and virtual evaluation of a 24-member library of 9-anilinoacridine derivatives against the ERα ligand-binding domain, identifying three computationally prioritized candidates whose fate now rests entirely on experiments that have not yet been performed.

The research team, publishing an entirely in silico investigation, constructed a series of acridine-based molecules in which electron-donating and electron-withdrawing substituents were systematically varied on the terminal phenyl ring of the 9-anilinoacridine scaffold. The acridine nucleus is a planar, tricyclic aromatic system long prized in medicinal chemistry for its capacity to engage in π–π stacking, hydrophobic contacts and DNA intercalation, and several acridine derivatives have previously shown anticancer activity through topoisomerase inhibition, disruption of DNA replication and apoptosis induction. What remained poorly explored, the authors argue, was how novel substitutions on this scaffold would shape predicted interactions with ERα.

To answer that question computationally, the researchers anchored their workflow to a high-resolution X-ray crystal structure of the human ERα ligand-binding domain, PDB ID 2IOG, determined at 1.60 Å and co-crystallized with the ligand IOG in an antagonist-associated receptor conformation. Chain A, spanning residues 309 to 554, was prepared in Schrödinger’s Protein Preparation Wizard: crystallographic waters beyond 5 Å of the active site were removed, bond orders and protonation states were assigned at physiological pH, missing loops were rebuilt with Prime, and the structure was restrained-minimized with the OPLS4 force field to a heavy-atom RMSD cutoff of 0.30 Å. Three C-terminal residues and part of the Arg335 side chain were unresolved in the deposited structure and were repaired during preparation.

All 24 derivatives — designated II(a) through II(x) — were sketched in ChemDraw and converted to three-dimensional conformers with LigPrep, generating relevant protonation and tautomeric states at pH 7.0 ± 0.2. Docking was performed with Glide in extra-precision (XP) mode, using a receptor grid defined by the co-crystallized ligand, which was removed before docking. The protocol was validated by redocking IOG into the binding site: the superposition of experimental and redocked poses yielded a heavy-atom RMSD of just 0.2086 Å, supporting the reliability of the setup. Crucially, the authors stress that docking scores were used only for comparative prioritization and were not interpreted as experimental binding affinities.

The docking results singled out two derivatives. Compound II(x), a phenylhydrazone-substituted analogue, achieved the most favourable Glide XP Gscore of −11.85 kcal/mol and the best docking score of the series at −9.80 kcal/mol, while compound II(e), bearing a 2-nitrophenyl substituent, followed closely with a Gscore of −11.78 kcal/mol and a docking score of −9.32 kcal/mol. Interaction analysis revealed that II(x) formed a hydrogen bond with ASP351 and significant π–π stacking with TRP383, supplemented by hydrophobic contacts with LEU346, LEU349, MET343, MET421, LEU525 and TYR526. Derivatives II(n), II(w), II(i) and II(j) also scored favourably, whereas II(o), II(l) and II(s) were the weakest performers, with Gscores between −5.28 and −5.93 kcal/mol.

Because docking scores alone can mislead, the team ran Prime MM-GBSA calculations on the minimized docked complexes using the VSGB 2.0 solvation model. Here the ranking shifted in an instructive way: compound II(f), an ortho-aminophenyl imine derivative with only a moderate Gscore of −8.71 kcal/mol, produced the most favourable calculated binding free energy of the entire library at −99.68 kcal/mol, ahead of II(q) at −88.69 and II(c) at −79.68 kcal/mol. Energy decomposition attributed II(f)’s advantage to a strong van der Waals contribution of −63.14 kcal/mol, a lipophilic term of −40.56 kcal/mol, Coulombic energy of −40.76 kcal/mol and a hydrogen-bonding contribution of −3.43 kcal/mol. By contrast, II(e) and II(x) yielded markedly less favourable MM-GBSA estimates of −40.91 and −33.50 kcal/mol respectively — a divergence the authors interpret as evidence that docking scores and post-docking energetics capture different aspects of ligand–receptor recognition.

The pharmacokinetic picture, predicted with the QikProp module, was mixed. Molecular weights ranged from 325.41 to 492.49 g/mol, and predicted octanol/water partition coefficients (QPlogPo/w) spanned 3.46 to 7.30, indicating moderate-to-high lipophilicity across the series. Compound II(f) showed a molecular weight of 402.49 g/mol, a dipole moment of 3.00 D, hydrogen-bond donor/acceptor values of 2.5/3.5, a QPlogPo/w of 5.84 and one predicted Rule-of-Five violation. Most derivatives showed zero or one violation, but several displayed high lipophilicity and poor predicted aqueous solubility, with QPlogS values ranging from −4.67 to −8.48. Blood–brain barrier penetration was generally limited, and ProTox 3.0 predictions placed the compounds in toxicity classes 3 to 5, with predicted LD50 values of 160 to 2690 mg/kg; II(v) and II(w) showed the lowest predicted LD50 values, while hepatotoxicity and respiratory-toxicity alerts appeared for several derivatives.

The three top candidates — II(e) and II(x) for their docking scores, II(f) for its MM-GBSA energetics — were then subjected to 100 ns molecular dynamics simulations in Desmond, solvated in TIP3P water with 0.15 M salt and neutralizing counter ions. All four systems, including the co-crystallized ligand reference, showed an initial conformational adjustment followed by stable trajectories: protein RMSD settled around 1.8–2.2 Å for II(e), 2.0–2.4 Å for II(f), 2.5–2.9 Å for II(x) and 2.4–2.8 Å for the reference ligand in the latter half of the runs. Root-mean-square fluctuation analysis showed that the binding-site residues remained comparatively rigid, with the largest fluctuations confined to terminal and loop regions. Compound II(f) underwent a pronounced transient ligand rearrangement between roughly 20 and 45 ns, with ligand RMSD peaking near 4 Å before settling, yet it maintained recurrent contacts with Leu346, Ala350, Thr383, Leu387, Phe404 and Leu536, alongside intermittent hydrogen-bonding and water-mediated interactions, including recurring contacts with Glu353 and Asp351 across trajectory snapshots.

The authors are careful — unusually so for this genre — about what the results do and do not establish. The simulations comprised a single 100 ns trajectory per complex, so trajectory reproducibility remains untested. Docking was performed against a single antagonist-associated receptor conformation and therefore does not encompass the full conformational ensemble of ERα. No compound was synthesized, characterized or biologically tested: there are no NMR, mass spectrometric or purity data, no cytotoxicity assays, no receptor-binding or transactivation experiments, and no evidence of ERα antagonism or downstream signalling effects on the PI3K/AKT or MAPK pathways, which are discussed only as hypothetical consequences requiring validation. The authors also flag chemical-stability concerns, noting that II(f) and II(k) contain ortho-amino and ortho-hydroxy groups adjacent to imine functionalities that could permit hydrolysis, tautomerization or cyclization under experimental conditions.

Within those limits, the study delivers a concrete, hypothesis-generating shortlist. Compound II(f) emerges as the lead computational candidate on the strength of its favourable MM-GBSA energetics and persistent, dynamically rearranging contacts within the ERα pocket, flanked by II(e) and II(x). The next steps the authors propose are unambiguous: synthesize and fully characterize the prioritized structures, assess their solution-phase stability, then test ERα binding and functional activity, antiproliferative effects, selectivity and pharmacokinetic and toxicity profiles experimentally. Until that work is done, the computational evidence stands as a prioritization framework — a structural argument that these acridine derivatives can plausibly occupy the ERα ligand-binding cavity, awaiting the laboratory verdict on whether that occupancy translates into biology.

Subject of Research: Structure-based computational design and evaluation of 9-anilinoacridine derivatives targeting estrogen receptor-alpha in breast cancer

Article Title: Structure-based design and molecular modelling of 9-anilinoacridine derivatives targeting estrogen receptor-α in breast cancer

Article References: Rajagopal, K., Shanmugam, K., Raman, K., Uddandrao, V. V. S., Thakran, A., Dhevikarunaa, G. M., & Luseena, P. (2026). Structure-based design and molecular modelling of 9-anilinoacridine derivatives targeting estrogen receptor-α in breast cancer. Results in Chemistry, 31, Article 103975. https://doi.org/10.1016/j.rechem.2026.103975

Image Credits: AI Generated

DOI: 10.1016/j.rechem.2026.103975

Keywords: breast cancer, estrogen receptor-alpha, 9-anilinoacridine, molecular docking, MM-GBSA, molecular dynamics simulation, ADMET prediction, drug design, virtual screening, endocrine resistance, computational chemistry, Schrödinger Glide