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Identification of distant co-evolving residues in antigen 85C from Mycobacterium tuberculosis using statistical coupling analysis of the esterase family proteins 被引量:2
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作者 Veeky Baths Utpal Roy 《The Journal of Biomedical Research》 CAS 2011年第3期165-169,共5页
A fundamental goal in cellular signaling is to understand allosteric communication, the process by which sig-nals originating at one site in a protein propagate reliably to affect distant functional sites. The general... A fundamental goal in cellular signaling is to understand allosteric communication, the process by which sig-nals originating at one site in a protein propagate reliably to affect distant functional sites. The general principles of protein structure that underlie this process remain unknown. Statistical coupling analysis (SCA) is a statistical technique that uses evolutionary data of a protein family to measure correlation between distant functional sites and suggests allosteric communication. In proteins, very distant and small interactions between collections of amino acids provide the communication which can be important for signaling process. In this paper, we present the SCA of protein alignment of the esterase family (pfam ID: PF00756) containing the sequence of antigen 85C secreted by Mycobacterium tuberculosis to identify a subset of interacting residues. Clustering analysis of the pairwise correlation highlighted seven important residue positions in the esterase family alignments. These resi-dues were then mapped on the crystal structure of antigen 85C (PDB ID: 1DQZ). The mapping revealed corre-lation between 3 distant residues (Asp38, Leu123 and Met125) and suggests allosteric communication between them. This information can be used for a new drug against this fatal disease. 展开更多
关键词 antigen 85C Mycobacterium tuberculosis clustering analysis COVARIANCE statistical coupling analy-sis esterase family multiple sequence alignments PFAM protein data Bank.
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Computational Analyses of Docosahexaenoic Acid (DHA, C22:6, n-3) with Alzheimer’s Disease-Causing Amyloid Peptide Aβ1-42 Reassures Its Therapeutic Utility
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作者 Michio Hashimoto Shahdat Hossain +3 位作者 Kentaro Matsuzaki Abdullah Al Mamun Hiroyuki Arai Osamu Shido 《Advances in Alzheimer's Disease》 2016年第2期73-86,共14页
The accumulation of amyloid β peptide<sub>1-42</sub> (Aβ<sub>1-42</sub>) masses in the brains of Alzheimer’s Disease (AD) patients is associated with neuronal loss and memory deficits. We ha... The accumulation of amyloid β peptide<sub>1-42</sub> (Aβ<sub>1-42</sub>) masses in the brains of Alzheimer’s Disease (AD) patients is associated with neuronal loss and memory deficits. We have previously reported that oral administration of docosahexaenoic acid (DHA, C22:6, n-3) significantly decreases Aβ burden in the brains of AD model rats and that direct in vitro incubation of DHA with Aβ<sub>1-42</sub> curbs the progression of amyloid fibrillation. In the present in silico study, we investigated whether DHA computationally binds with amyloid peptides. The NMR solution structures of Aβ<sub>1-42</sub> were downloaded from the Protein Data Bank (PDB IDs: 1Z0Q and 2BEG). The binding of DHA to Aβ peptides was assessed by molecular docking using both a flexible and rigid docking system. Thioflavin T (ThT) was used as positive control. The chemical structures of ThT and DHA were modeled and converted to the PDB format using PRODRUG. Drug-like properties of DHA were evaluated by ADME (Absorption, Distribution, Metabolism, and Excretion). DHA was found to successfully dock with Aβ<sub>1-42</sub>. Computational analyses of the binding of DHA to Aβ<sub>1-42</sub>, as evaluated by docking studies, further corroborated the inhibitory effect of DHA on in vitro Aβ<sub>1-42</sub> fibrillogenesis and might explain the in vivo reduction of amyloid burden observed in the brains of DHA-administered AD model rats demonstrated in our previous study. These computational data suggest the potential utility of DHA as a preventive medication in Aβ-induced neurodegenerative diseases, including AD. 展开更多
关键词 Docosahexaenoic Acid Alzheimer’s Disease Amyloid Beta Peptide Molecular Docking In Silico Drug Design protein data Bank
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