HTRA1-targeted small molecules as therapies for Alzheimer's disease.
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William Lin
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Alzheimer’s disease remains one of the most pressing neurodegenerative disorders, with limited treatment options, making the identification of novel therapeutic targets a crucial research challenge. In this study, we focused on the HtrA serine peptidase 1 (HTRA1) receptor, which plays a key role in disease pathology. First, we applied three complementary binding-site prediction tools—DogSiteScorer (DOG algorithm), FTSite (FFT solvent mapping), and PrankWeb (PRANK deep learning)—to the HTRA1 crystal structure, identifying five high-confidence pockets. Next, a pharmacophore model was built in Pharmit to capture key hydrogen bond donors/acceptors and hydrophobic/aromatic features; screening of a ~150,000-compound library yielded 15 diverse candidates. These 15 ligands were docked using SwissDock and ranked by estimated binding free energy (ΔG) and full‑fitness scores. The top five compounds (ΔG ≤ –7.5 kcal/mol, exhibiting consistent hydrogen bonds with active-site residues) advanced to ADME and toxicity evaluation. ADME properties were predicted via SwissADME, enforcing Lipinski’s Rule of Five and Veber’s rules (TPSA ≤ 140 Ų; ≤ 10 rotatable bonds), while toxicity risks were assessed using ProTox‑3 (hepatotoxicity, carcinogenicity, LD₅₀). Finally, molecular dynamics simulations (100‑ns GROMACS runs) on the best three candidates (GlideScores < –8.5 kcal/mol; RMSD < 2 Å; ≥ 80% key H‑bond occupancy) confirmed stable binding. These three lead molecules, selected for their optimal binding affinity, dynamic stability, and favorable ADME/toxicity profiles, now proceed to in vitro validation—paving the way toward a targeted Alzheimer’s therapy with high efficacy and minimal side effects.
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Authors
William Lin
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References:
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