Structural characterization of codon 129 polymorphism in prion peptide segments (PrP127-132) using the Markov State Models

Publication Type

Journal Article

Publication Date (Issue Year)

2025

Journal Name

Journal of Molecular Graphics and Modelling

Abstract

The human prion protein gene (PRNP) consists of two common alleles that encode either methionine or valine residues at codon 129. Polymorphism at codon 129 of the prion protein (PRNP) gene is closely associated with genetic variations and susceptibility to specific variants of prion diseases. The presence of these different alleles, known as the PRNP codon 129 polymorphism, plays a significant role in disease susceptibility and progression. For instance, the prion fragment 127-132 (PrP127-132) has been implicated in the development of variant Creutzfeldt–Jakob disease (vCJD), due to the presence of methionine or valine at codon 129. This study aims to unravel the early structural changes brought by the presence of polymorphism at codon 129. Using molecular dynamics (MD) simulations, we present evidence highlighting a spectrum of structural transitions, uncovering the nuanced conformational heterogeneity governing the polymorphic behavior of the PrP127-132 chain. The Markov state model (MSM) analysis was able to predict several metastable states of these chains and established a kinetic network that describes transitions between these states. Additionally, the MSM analysis showed extra stability of the PrP-M129 polymorph due to less random-coiled motions, the formation of a salt bridge, and an increase in the number of native contacts. The pathogenicity of PrP-V129 can be attributed to enhanced random motion and the absence of a salt bridge.

Keywords

Molecular dynamics simulations, Markov state models, PrP127-132, PrP-M129, PrP-V129

Grantee Name(s)

Robinson Juma Musembi

Project Title

Self-cleaning solar module for enhanced electrical output

Type of Grant

Research Award

Thematic Area

Energy including Renewables

Funding Statement

The authors gratefully acknowledge the Centre for High Performance Computing (CHPC), Cape Town, South Africa, for allowing us to use their computational resources. The authors would also like to thank Charles Ndegwa for reading and improving the manuscript.

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