COMPUTATIONAL IDENTIFICATION OF NOVEL BACE1 MODULATORS FOR ALZHEIMER'S DISEASE: A STRUCTURE DRIVEN DRUG DISCOVERY APPROACH

Abstract

Aim: Amyloid beta deposition in the neural tissue, which leads to neural detrioration and escalating cognitive deterioration are major signatures of Alzheimer disease, a chronic neurodegenerative disorder. Since BACE1 sparks the amyloidogenic pathway fueling Amyloid beta generation and plaque augmentation, inhibiting BACE 1 is a promising approach to curb its accumulation in AD. This study used a computational approach where 5HTZ a co crystallised molecular structure which showcases a potent inhibitor bound or complexed at the catalytic pocket or binding site of the BACE1 was utilized as reference structure to find promising BACE 1 inhibitors. The primary objective was to shortlist better suited compounds for BACE 1 inhibition and thus Alzheimer treatment to that was formely found. Here, a large number of compounds were Shortlisted on the basis of structural similarity to the reference molecule which Were filtered by ADME analysis. A carefully chosen compound library was docked into the catalytic pocket of BACE1 after protein preparation and active-site mapping in order to assess interaction potency and interaction stability. Top hits having strong interactions with key residues were profiled for ADME, including drug –likeness, GI absorption, BBB permeability and CNS relevant characteristics. Numerous compounds demonstrated advantageous pharmacokinetic profiles and binding energies, making them prime candidates for pharmacological and biochemical verification. These findings supports the use of computational techniques to accelerate the discovery of novel BACE1 modulators for the disease. Further they also highlight promising lead candidates to carry out additional trial and confirmation. Keywords— Alzheimers disease, BACE1, amyloid beta generation, virtual screening, ADME analysis, catalytic pocket, active site mapping, pharmacokinetic profiles, computational strategies.

Result: During the course of this study, an initial pool of 400 structurally similar compounds was screened, from which ADME evaluation refined the selection to 81 candidates, all exhibiting blood–brain barrier permeability. Subsequent molecular docking analysis revealed that five of these compounds demonstrated stronger binding affinities than the reference compound ,with the top-performing compound showing a binding affinity of −8.7 kcal/mol. Conclusion: From the set of five shortlisted candidates, Compound 5 demonstrated the strongest performance, showing the highest binding affinity along with the ability to cross the blood–brain barrier. Further validation of these results through in vivo studies is recommended to confirm its potential.