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Homology modeling, molecular docking, and molecular dynamics simulations elucidated α-fetoprotein binding modes.

Abstract：

BACKGROUND:An important mechanism of endocrine activity is chemicals entering target cells via transport proteins and then interacting with hormone receptors such as the estrogen receptor (ER). α-Fetoprotein (AFP) is a major transport protein in rodent serum that can bind and sequester estrogens, thus preventing entry to the target cell and where they could otherwise induce ER-mediated endocrine activity. Recently, we reported rat AFP binding affinities for a large set of structurally diverse chemicals, including 53 binders and 72 non-binders. However, the lack of three-dimensional (3D) structures of rat AFP hinders further understanding of the structural dependence for binding. Therefore, a 3D structure of rat AFP was built using homology modeling in order to elucidate rat AFP-ligand binding modes through docking analyses and molecular dynamics (MD) simulations. METHODS:Homology modeling was first applied to build a 3D structure of rat AFP. Molecular docking and Molecular Mechanics-Generalized Born Surface Area (MM-GBSA) scoring were then used to examine potential rat AFP ligand binding modes. MD simulations and free energy calculations were performed to refine models of binding modes. RESULTS:A rat AFP tertiary structure was first obtained using homology modeling and MD simulations. The rat AFP-ligand binding modes of 13 structurally diverse, representative binders were calculated using molecular docking, (MM-GBSA) ranking and MD simulations. The key residues for rat AFP-ligand binding were postulated through analyzing the binding modes. CONCLUSION:The optimized 3D rat AFP structure and associated ligand binding modes shed light on rat AFP-ligand binding interactions that, in turn, provide a means to estimate binding affinity of unknown chemicals. Our results will assist in the evaluation of the endocrine disruption potential of chemicals.

journal_name

BMC Bioinformatics

journal_title

BMC bioinformatics

authors

Shen J,Zhang W,Fang H,Perkins R,Tong W,Hong H

doi

10.1186/1471-2105-14-S14-S6

subject

Has Abstract

pub_date

2013-01-01 00:00:00

pages

issn

1471-2105

pii

1471-2105-14-S14-S6

journal_volume

14 Suppl 14

pub_type

杂志文章

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Homology modeling, molecular docking, and molecular dynamics simulations elucidated α-fetoprotein binding modes.