Akademik Veri Yönetim Sistemi
3rd ML4NGP meeting on Machine Learning and Non-globular proteins, Vilniaus, Litvanya, 20 - 23 Mayıs 2025, (Yayınlanmadı)
Lamin A (LMNA) is a critical component of the nuclear lamina, playing an essential role in maintaining nuclear integrity and regulating gene expression. Mutations, particularly missense non-synonymous single-nucleotide polymorphisms (nsSNPs), in the LMNA gene have been implicated in a wide spectrum of laminopathies, including muscular dystrophies, cardiomyopathies, and premature aging syndromes. This study aimed to identify and characterize potentially deleterious nsSNPs in the LMNA gene using an integrative in silico approach. Functional annotations were conducted using multiple predictive algorithms (e.g., SIFT, PolyPhen-2, PROVEAN), while structural impacts were assessed through homology modeling and stability prediction tools. Selected high-risk variants were further subjected to molecular dynamics (MD) simulations to explore their influence on protein stability, flexibility, and conformational dynamics. Our findings highlight several critical mutations that may disrupt the structural and functional integrity of the LMNA protein, providing insights into their potential pathogenic mechanisms.