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In SilicoStructure Prediction of Human Fatty Acid Synthase–Dehydratase: A Plausible Model for Understanding Active Site Interactions
Author(s) -
Arun John,
Umashankar Vetrivel,
A. Samdani,
Manoharan Sangeetha,
Subramanian Krishnakumar,
Perinkulam Ravi Deepa
Publication year - 2016
Publication title -
bioinformatics and biology insights
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.556
H-Index - 23
ISSN - 1177-9322
DOI - 10.4137/bbi.s38317
Subject(s) - fatty acid synthase , ramachandran plot , in silico , dehydratase , active site , virtual screening , docking (animal) , chemistry , molecular dynamics , biochemistry , enzyme , protein data bank (rcsb pdb) , acyl carrier protein , computational biology , protein structure , biology , drug discovery , computational chemistry , biosynthesis , medicine , gene , nursing
Fatty acid synthase (FASN, UniProt ID: P49327) is a multienzyme dimer complex that plays a critical role in lipogenesis. Consequently, this lipogenic enzyme has gained tremendous biomedical importance. The role of FASN and its inhibition is being extensively researched in several clinical conditions, such as cancers, obesity, and diabetes. X-ray crystallographic structures of some of its domains, such as β-ketoacyl synthase, acetyl transacylase, malonyl transacylase, enoyl reductase, β-ketoacyl reductase, and thioesterase, (TE) are already reported. Here, we have attempted an in silico elucidation of the uncrystallized dehydratase (DH) catalytic domain of human FASN. This theoretical model for DH domain was predicted using comparative modeling methods. Different stand-alone tools and servers were used to validate and check the reliability of the predicted models, which suggested it to be a highly plausible model. The stereochemical analysis showed 92.0% residues in favorable region of Ramachandran plot. The initial physiological substrate β-hydroxybutyryl group was docked into active site of DH domain using Glide. The molecular dynamics simulations carried out for 20 ns in apo and holo states indicated the stability and accuracy of the predicted structure in solvated condition. The predicted model provided useful biochemical insights into the substrate-active site binding mechanisms. This model was then used for identifying potential FASN inhibitors using high-throughput virtual screening of the National Cancer Institute database of chemical ligands. The inhibitory efficacy of the top hit ligands was validated by performing molecular dynamics simulation for 20 ns, where in the ligand NSC71039 exhibited good enzyme inhibition characteristics and exhibited dose-dependent anticancer cytotoxicity in retinoblastoma cancer cells in vitro.

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