Identification of new pentapeptides as potential inhibitors of amyloid–β42 aggregation using virtual screening and molecular dynamics simulations

Abstract

Alzheimer's disease (AD) is a multifactorial neurodegenerative disease mainly characterized by extracellular accumulation of amyloid-β (Aβ) peptide. Previous studies reported pentapeptide RIIGL as an effective inhibitor of Aβ aggregation and neurotoxicity induced by Aβ aggregates. In this work, a library of 912 pentapeptides based on RIIGL has been designed and assessed for their efficacy to inhibit Aβ42 aggregation using computational techniques. The top hit pentapeptides revealed by molecular docking were further assessed for their binding affinity with Aβ42 monomer using MM-PBSA (molecular mechanics Poisson-Boltzmann surface area) method. The MM-PBSA analysis identified RLAPV, RVVPI, and RIAPA, which bind to Aβ42 monomer with a higher binding affinity −55.80, −46.32, and −44.26 kcal/mol, respectively, as compared to RIIGL (ΔGbinding = −41.29 kcal/mol). The residue-wise binding free energy predicted hydrophobic contacts between Aβ42 monomer and pentapeptides. The secondary structure analysis of the conformational ensembles generated by molecular dynamics (MD) depicted remarkably enhanced sampling of helical and no β–sheet conformations in Aβ42 monomer on the incorporation of RVVPI and RIAPA. Notably, RVVPI and RIAPA destabilized the D23–K28 salt bridge in Aβ42 monomer, which plays a crucial role in Aβ42 oligomer stability and fibril formation. The MD simulations highlighted that the incorporation of proline and arginine in pentapeptides contributed to their strong binding with Aβ42 monomer. Furthermore, RVVPI and RIAPA prevented conformational conversion of Aβ42 monomer to aggregation-prone structures, which, in turn, resulted in a lower aggregation tendency of Aβ42 monomer.