Preclinical Advances in Small-Molecule Drug Discovery for Alzheimer's Disease: Computational Strategies and Emerging Compounds

A computational chemistry team has prioritized an amidine-based BACE‑1 inhibitor — Compound 9.7 — that combines strong predicted binding, favorable PK features, and stable molecular dynamics, sharpening early Alzheimer’s lead selection and justifying rapid synthesis and biochemical follow-up.

Prior docking campaigns generated many hits but left unresolved gaps in selectivity and ADME predictivity, especially versus the related BACE‑2 isoform and for CNS penetration. This work closes that gap by coupling multi-criterion ADME filtering with rigorous MD evaluation, creating a direct computational-to-prioritization bridge for medicinal chemistry teams.

Compound 9.7 ranked top in docking with a predicted binding affinity near −5.5 kcal·mol−1, anchors to catalytic ASP32, and maintains persistent contacts with TRP115 and PHE108. MD integrity was supported by low ligand RMSD and conserved low-to-medium RMSF across active‑site residues during a 200 ns production run. (Docking: AutoDock Vina v1.2 with consensus scoring; MD: AMBER ff14SB and GAFF2 ligand parameters in TIP3P water, 2 ns equilibration followed by 200 ns at 310 K.) Compound 9.7 therefore carries the computational profile that merits synthesis and enzymatic testing.

In-silico profiling of the amidine scaffold returned a CNS-biased physicochemical window (consensus logP ≈ 2.0–3.5), acceptable bioavailability scores, limited predicted P‑gp liability, and manageable CYP inhibition flags. Polar surface area and the cationic amidine motif remain clear medicinal-chemistry levers to tune permeability and off‑target risk. (Predictions derived from a pkCSM and QikProp consensus using default thresholds for P‑gp and CYP alerts.) Amidine ADME analysis supports prioritization while highlighting lipophilicity and PSA as optimization handles.

Some potential next steps include rapid synthesis scale-up; enzymatic IC50 determination against BACE‑1 with parallel selectivity testing versus BACE‑2 and other aspartyl proteases; cellular permeability and transwell BBB surrogate assays; and early metabolic stability using liver microsomes and CYP panels. These assays will validate the computational predictions and define go/no‑go criteria. Key challenges will be achieving sufficient cell and brain exposure without increasing off‑target protease activity — milestones that will determine readiness for in vivo studies.

Looking forward, integrated computational prioritization should shorten validation timelines and clarify primary optimization goals for this scaffold.

Key Takeaways:

• Compound 9.7 demonstrates robust docking, catalytic ASP32 anchoring, and 200 ns MD stability.
• The amidine scaffold shows a CNS‑focused ADME profile with modifiable lipophilicity and PSA risks.
• Immediate next steps: synthesize, measure IC50/selectivity, and test permeability and metabolic stability.