In-silico investigation of the molecular disruption of Aβ42 protofibril by stilbenoids

Chandraniv Dey1, Praval Pratap Singh1, Sudip Chakraborty1

  • 1Department of Computational Sciences, School of Basic Sciences, Central University of Punjab, Bathinda, India.

Insights

Rhapontigenin effectively destabilizes amyloid-beta (Aβ)42 protofibrils, offering a promising therapeutic strategy for Alzheimer's disease (AD). This natural compound disrupts Aβ42 aggregation, highlighting stilbenoids as potential anti-amyloid drug scaffolds.

Area of Science:

  • Biochemistry
  • Neuroscience
  • Computational Chemistry

Background:

  • Alzheimer's disease (AD) is characterized by amyloid-beta (Aβ) aggregation.
  • Targeting Aβ42 protofibrils is a key therapeutic strategy for AD.
  • Naturally occurring stilbenoids are explored for their anti-amyloid properties.

Purpose of the Study:

  • To evaluate the potential of five natural stilbenoids (Resveratrol, Piceid, Astringin, Piceatannol, Rhapontigenin) to destabilize Aβ42 protofibrils.
  • To identify the most effective stilbenoid for disrupting Aβ42 fibril structure using in silico methods.

Main Methods:

  • Integrated in silico approach combining molecular docking, 500 ns all-atom molecular dynamics simulations, and MM-PBSA binding free energy calculations.
  • Structural analyses including RMSD, RMSF, radius of gyration, hydrogen-bond/salt-bridge dynamics, intersheet contacts, and principal component analysis.

Main Results:

  • Rhapontigenin showed the most favorable binding free energy and significantly disrupted Aβ42 protofibril structure, including hydrogen bonds, salt bridges, and compactness.
  • Rhapontigenin induced chain-terminal deformation and loss of fibril rigidity.
  • Piceatannol and Piceid had moderate effects, while Astringin and Resveratrol had minimal impact.

Conclusions:

  • Rhapontigenin is a potent destabilizer of Aβ42 protofibrils.
  • Naturally derived stilbenoids are promising scaffolds for developing anti-amyloid drugs.
  • Simulation-driven strategies are valuable for targeting protein aggregates in neurodegenerative diseases.