Takako Sakano, Md. Iqbal Mahamood, Takefumi Yamashita and Hideaki Fujitani
"Molecular dynamics analysis to evaluate docking pose prediction"
Biophysics and Physicobiology, Vol.13, pp.181-194 (2016).
These days, molecular dynamics (MD) simulation becomes a useful and reliable tool to reveal the dynamic features of biological macromolecules, even when the static structures are known. In this article, the authors performed docking calculations for the two target proteins: one of GPCR membrane protein, β2 adrenergic receptor (β2AR), and a soluble protein, PR-Set7, which catalyzes the methylation of the H4 tail in the cell. For β2AR, the authors investigated the complex structures with the six ligand molecules, and for PR-Set7, they used two bound inhibitors. The former complex structures are rather rigid and, on the contrary, the latter ones are flexible. After all-atom MD simulations for longer than 100 ns, the trajectories for each MD run were calculated starting from the complex structures predicted with the docking software. The authors assessed the conventional docking predictions with MD simulations, and they show (1) for the rigid complex structures of β2AR with its ligands, the docking predictions could give the essential interactions and the MD simulations provide the details of the binding modes, depending on the individual ligand species, (2) for flexible complex structures of PR-Set7 with its ligands, the ligands greatly departed from the predicted docking poses during the MD simulations. Consequently, MD simulations can provide complementary information about the binding complex structure.
Thus, the authors succeeded in demonstrating that MD simulation can be used to assess binding structures predicted by docking, and to provide complementary information. They also found that stability of the predicted ligand pose was moderately correlated to ligand similarity. This article is, therefore, believed to pave the way for the reliable usage of MD simulation, in structural biology and applications to drug discovery.
July, 2020
Biophysics and Physicobiology Award Selection Committee
I am very honored to receive this award. Firstly, I appreciate the support of my great collaborators. The late Prof. Hideaki Fujitani is a pioneer in the massively parallel molecular dynamics (MD) simulation for drug design. We started a K computer project, which aimed at applying the MD simulation to drug design. Dr. Takako Sakano and Dr. Md. Iqbal Mahmood joined this project and conducted many MD simulations, which made us deeply realize how important the molecular dynamics is in the ligand-protein binding. In addition to our free energy calculation method, MP-CAFEE, we noticed that the MD simulation can be used to check the ligand-protein complex structure. Next, I am most grateful to the fruitful collaboration with experimentalists. Their discussion always deepened our understandings. Finally, we thank the support from many projects (especially the K computer project), which grew our MD simulation technique largely. Although the K computer was decommissioned in 2019, Fugaku (the successor to K) has already started operation partly. Due to the high computational performance of Fugaku, our massively parallel MD methods (partly reported in our award-winning article) will be more and more important for designing drugs including antibodies in the next decade.
October 4th, 2020
Takefumi Yamashita