Computational bioisosteric investigation of sulindac derivatives for targeted inhibition in Alzheimer’s disease: DFT, molecular docking, and ADME/T profiling

Alzheimer’s disease (AD) is characterized by the formation of amyloid plaques and neurofibrillary tangles, resulting in neurodegenerative symptoms in the elderly. Amyloid beta and its precursor proteins along with their several mutations cause early-onset AD. Though, a well-known nonsteroidal anti-inflammatory drug, Sulindac has been found to block the A\(\beta \)42 peptide’s production in cultured cells, it has a questionable blood–brain barrier (BBB) permeability, which is necessary for AD-inhibiting drugs. In this paper, we use computational bioisosteric replacement of Sulindac to detect the derivatives with better pharmacokinetics and lead activity. Replacing important fragments of the parent molecule, structural modifications of Sulindac have been done with the aim of finding prospective drug candidates using consecutive screenings with quantum mechanical DFT calculations and protein–ligand docking. Finally, we shortlist 12 new drug candidates out of the huge spectrum of probable bioisosters, based on optimal stability, better docking energy, and desired ADME/T properties, highlighting BBB permeability. All these 12 derivatives, when computationally probed, have shown better BBB permeability as well as increased activity in A\(\beta \)42 inhibition and reduction of neuroinflammation.