Discovery of High Affinity Receptors for Dityrosine through Inverse Virtual Screening and Docking and Molecular Dynamics.

Fangfang Wang, Wei Yang, Xiaojun Hu

Journal: International journal of molecular sciences 2019;20(1):115

PMID: 30597963

Abstract

Dityrosine is the product of oxidation that has been linked to a number of serious pathological conditions. Evidence indicates that high amounts of dityrosine exist in oxidized milk powders and some milk related foodstuffs, further reducing the nutritional value of oxidized proteins. Therefore, we hypothesize that some receptors related to special diseases would be targets for dityrosine. However, the mechanisms of the interaction of dityrosine with probable targets are still unknown. In the present work, an inverse virtual screening approach was performed to screen possible novel targets for dityrosine. Molecular docking studies were performed on a panel of targets extracted from the potential drug target database (PDTD) to optimize and validate the screening results. Firstly, two different conformations cis- and trans- were found for dityrosine during minimization. Moreover, Tubulin (αT) (-11.0 kcal/mol) was identified as a target for cis-dityrosine (CDT), targets including αT (-11.2 kcal/mol) and thyroid hormone receptor beta-1 (-10.7 kcal/mol) presented high binding affinities for trans-dityrosine (TDT). Furthermore, in order to provide binding complexes with higher precision, the three docked systems were further refined by performing thermo dynamic simulations. A series of techniques for searching for the most stable binding pose and the calculation of binding free energy are elaborately provided in this work. The major interactions between these targets and dityrosine were hydrophobic, electrostatic and hydrogen bonding. The application of inverse virtual screening method may facilitate the prediction of unknown targets for known ligands, and direct future experimental assays.

Address: School of Life Science, Linyi University, Linyi 276000, China. [email protected].; Department of Microbiology, Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia. [email protected].; Arieh Warshel Institute of Computational Biology, the Chinese University of Hong Kong, 2001 Longxiang Road, Longgang District, Shenzhen 518000, China. [email protected].; School of Life Science, Linyi University, Linyi 276000, China. [email protected].
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