Exploration of conformational switching in Aβ16-22 peptide analogues via Molecular dynamics simulations

Jaypee University of Information Technology, Waknaghat, Solan, Himachal Pradesh-173234. Department of Biotechnology and Bioinformatics

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Abstract

Neurodegenerative disorders (ND) such as Alzheimer’s (AD) remain a major incurable problem largely due to an opaque mechanistic understanding of pathogenic protein aggregation at the molecular level. While amyloid beta (A0) fibrils are the main culprits in AD pathology, recent evidence indicates that early oligomers are neurotoxic. The K16-E22 hydrophobic core governs 0-sheet formation, cross-seeding interactions with tau, and nucleation kinetics, thereby regulating A0 conformational switching. In this study, a rational peptide-analogue strategy was adopted to explore how sequence-level mutations within the K16-E22 segment regulate conformational stability and aggregation. Initially, 18 peptide analogues were designed and screened using PROTPARAM (hydrophobicity) and WALTZ (beta-propensity). Following the evaluation of these metrics, five representative analogues were selected to systematically evaluate specific molecular attributes such as enhanced hydrophobicity (ALVFFAE: GRAVY +1.957, WALTZ 98.66), increased 0-propensity (KIVFFAE: GRAVY +1.243, WALTZ 98.327), 0-sheet disruption via proline insertion (KLPFFAE: GRAVY +0.314, WALTZ 0), charge density effects (KKVFFAE: GRAVY +0.043, WALTZ 0), and positional charge redistribution without hydrophobicity change (LVFKFAE: GRAVY +1.143, WALTZ 94.31), using the native KLVFFAE (GRAVY +1.143, WALTZ 97.8) sequence as a control. Three-dimensional structures of these selected peptides were generated using PEP-FOLD and validated using QMEAN scores before molecular dynamics (MD) simulations (GROMACS) to link sequence properties to conformational switching pathways. This work aims to pinpoint which molecular feature drives peptide aggregation and which helps them resist it. The results of this study are hypothesised to illuminate mechanistic details of disease progression and to enable the rational design of peptide-based aggregation modulators.