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Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web
Published on: July 16, 2017
Computational exploration of protein structure dynamics and RNA structural consequences of PKD1 missense variants:
Chandra Devi1, Prashant Ranjan1, Sonam Raj2
1Centre for Genetic Disorders, Institute of Science, Banaras Hindu University, Varanasi, Uttar Pradesh 221005 India.
Abstract:
We analyzed the impact of nine previously identified missense PKD1 variants from our studies, including c.6928G > A p.G2310R, c.8809G > A p.E2937K, c.2899 T > C p.W967R, c.6284A > G p.D2095G, c.6644G > A p.R2215Q, c.7810G > A p.D2604N, c.11249G > C p.R3750P, c.1001C > T p.T334M, and c.3101A > G p.N1034S on RNA structures and PC1 protein structure dynamics utilizing computational tools. RNA structure analysis was done using short RNA snippets of 41 nucleotides with the variant position at the 21st nucleotide, ensuring 20 bases on both sides. The secondary structures of these RNA snippets were predicted using RNAstructure. Structural changes of the mutants compared to the wild type were analyzed using the MutaRNA webserver. Molecular dynamics (MD) simulation of PC1 wild-type and mutant protein regions were performed using GROMACS 2018 (GROMOS96 54a7 force field). Findings revealed that five variants including c.8809G > A (p.E2937K), c.11249G > C (p.R3750P), c.3101A > G (p.N1034S), c.6928G > A (p.G2310R), c.6644G > A (p.R2215Q) exhibited major alterations in RNA structures and thereby their interactions with other proteins or RNAs affecting protein structure dynamics. While certain variants have minimal impact on RNA conformations, their observed alterations in MD simulations indicate impact on protein structure dynamics highlighting the importance of evaluating the functional consequences of genetic variants by considering both RNA and protein levels. The study also emphasizes that each missense variant exerts a unique impact on RNA stability, and protein structure dynamics, potentially contributing to the heterogeneous clinical manifestations and progression observed in Autosomal Dominant Polycystic Kidney Disease (ADPKD) patients offering a novel perspective in this direction. Thus, the utility of studying the structure dynamics through computational tools can help in prioritizing the variants for their functional implications, understanding the molecular mechanisms underlying variability in ADPKD presentation and developing targeted therapeutic interventions.
Supplementary Information:
The online version contains supplementary material available at 10.1007/s13205-024-04057-9.
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