Mechanism-Driven Features Enable Asn Deamidation Reactivity Prediction via Machine Learning Methods.

ABSTRACT: The spontaneous deamidation of Asparagine (Asn) residues is a common post-translational modification of proteins that can occur on disparate time scales, ranging from hours to thousands of years. This variability in the reaction rate reflects the influence of structural and environmental factors on the multistep mechanism of the deamidation reaction. Understanding the fine connection between reactivity and these modulating factors is essential to advance our knowledge of the deamidation kinetics in proteins and improve the prediction of deamidation-prone residues. In this work, we assessed the step-specific structural-dynamics parameters underlying the chemical basis of the first two reaction stages (the deprotonation and ring-closure steps) and developed novel descriptors derived from mol

SUBMITTER: De Sciscio ML 

PROVIDER: S-EPMC12529760 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature