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In silico analysis of detrimental mutations in ADD domain of chromatin remodeling protein ATRX that cause ATR-X syndrome: X-linked disorder
P. Chandrasekaran, J. Nisha, R. Sethumadhavan, , , ,
Published in Springer Verlag
2013
Volume: 2
   
Issue: 3
Pages: 123 - 135
Abstract
Many biological functions involve specific interactions of proteins. Mutations in ATRX gene can change the sequence and structure of a protein thereby impairing its function. Thus, the dysfunction of chromatin remodeling protein ATRX as a result of amino acid substitution in ADD domain often underlies the human disease, ATR-X syndrome. In general, it is mainly caused by amino acid substitution that interfered with the interactions of interest at the interface level. Hence, the study of protein-protein interactions and the interface that mediate the interactions stand important for understanding of biological function. In this work, we address the loss of function in chromatin remodeling protein ATRX due to loss of structural stability that affect the functional activity in mutant ADD domain by 17 missense mutations viz., G175E, N179S, P190A, P190L, P190S, L192F, V194I, C200S, Q219P, C220R, C220Y, W222S, C243F, R246C, R246L, G249C, and G249D. Furthermore, the loss of binding affinity of ADD domain with their interacting partner namely histone H3-peptide were investigated by (1) computing the RMSD (root mean square deviation) for the ADD domain of native with all the 17 mutants, (2) computing intra-molecular interactions in ADD domain of native with all the mutants, (3) computing binding affinity of native and mutant structures of ADD domain with histone H3-peptide through docking studies, and (4) cross validating the loss of function on binding affinity through inter-molecular interactions and normal mode analysis. Finally, as from our computational result, we concluded that all the parameters mentioned above used for studying ADD domain of mutant structures showed the decreased potential values compared to native structure that underlie ATR-X syndrome. © 2013 Springer-Verlag Wien.
About the journal
JournalData powered by TypesetNetwork Modeling and Analysis in Health Informatics and Bioinformatics
PublisherData powered by TypesetSpringer Verlag
ISSN21926670
Open AccessNo
Authors (4)