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Target prediction by docking simulation

RS Ryusuke Sawada
MI Michio Iwata
MU Masahito Umezaki
YU Yoshihiko Usui
TK Toshikazu Kobayashi
TK Takaki Kubono
SH Shusaku Hayashi
MK Makoto Kadowaki
YY Yoshihiro Yamanishi
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We performed a target prediction by performing a docking simulation. Protein 3D structures were obtained from the PDB database35 and SAHG36. In this study, we used AutoDock, which is a suite of automated docking tools, to predict how compounds bind to a target protein37. We performed a large-scale docking simulation for all possible pairs of the constituent compounds and about 40,000 human proteins. The predicted protein–ligand complexes were optimized and ranked according to the empirical scoring function, which estimates the binding free energy of the ligand receptor complex. We stored the calculated numerical results in the platform.

Copyright and License information: The Author(s) ©2018
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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