Comparative Modeling and Molecular Dynamics Simulation of Substrate Binding in Human Fatty Acid Synthase: Enoyl Reductase and beta-Ketoacyl Reductase Catalytic Domains.
- Author:
Arun JOHN
1
;
Vetrivel UMASHANKAR
;
Subramanian KRISHNAKUMAR
;
Perinkulam Ravi DEEPA
Author Information
- Publication Type:Validation Studies ; Original Article
- Keywords: beta-ketoacyl reductase molecular dynamics simulation; comparative modeling; docking; enoyl reductase; fatty acid synthase
- MeSH: Catalytic Domain*; Humans; Lipogenesis; Models, Theoretical; Molecular Dynamics Simulation*; Obesity; Oxidoreductases*
- From:Genomics & Informatics 2015;13(1):15-24
- CountryRepublic of Korea
- Language:English
- Abstract: Fatty acid synthase (FASN, EC 2.3.1.85), is a multi-enzyme dimer complex that plays a critical role in lipogenesis. This lipogenic enzyme has gained importance beyond its physiological role due to its implications in several clinical conditions-cancers, obesity, and diabetes. This has made FASN an attractive pharmacological target. Here, we have attempted to predict the theoretical models for the human enoyl reductase (ER) and beta-ketoacyl reductase (KR) domains based on the porcine FASN crystal structure, which was the structurally closest template available at the time of this study. Comparative modeling methods were used for studying the structure-function relationships. Different validation studies revealed the predicted structures to be highly plausible. The respective substrates of ER and KR domains-namely, trans-butenoyl and beta-ketobutyryl-were computationally docked into active sites using Glide in order to understand the probable binding mode. The molecular dynamics simulations of the apo and holo states of ER and KR showed stable backbone root mean square deviation trajectories with minimal deviation. Ramachandran plot analysis showed 96.0% of residues in the most favorable region for ER and 90.3% for the KR domain, respectively. Thus, the predicted models yielded significant insights into the substrate binding modes of the ER and KR catalytic domains and will aid in identifying novel chemical inhibitors of human FASN that target these domains.
