Mitsugu Araki

According to our database, Mitsugu Araki authored at least 10 papers between 2016 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Elucidating Ligand Charge Effects in MR1 Cell-Surface Translocation Using Molecular Simulations.

Toshiki Fujii, Mitsugu Araki, Shigeyuki Matsumoto, Biao Ma, Takao Otsuka, Gert-Jan Bekker, Narutoshi Kamiya, Hiroaki Ohno, Shinsuke Inuki, Yasushi Okuno

J. Chem. Inf. Model., 2026

2024

Binding Mechanism between Platelet Glycoprotein and Cyclic Peptide Elucidated by McMD-Based Dynamic Docking.

Gert-Jan Bekker, Kanji Oshima, Mitsugu Araki, Yasushi Okuno, Narutoshi Kamiya

J. Chem. Inf. Model., 2024

2022

Protein-ligand binding affinity prediction of cyclin-dependent kinase-2 inhibitors by dynamically averaged fragment molecular orbital-based interaction energy.

Kenichiro Takaba, Chiduru Watanabe, Atsushi Tokuhisa, Yoshinobu Akinaga, Biao Ma, Ryo Kanada, Mitsugu Araki, Yasushi Okuno, Yusuke Kawashima, Hirotomo Moriwaki, Norihito Kawashita, Teruki Honma, Kaori Fukuzawa, Shigenori Tanaka

J. Comput. Chem., 2022

2021

Extraction of protein dynamics information from cryo-EM maps using deep learning.

Shigeyuki Matsumoto, Shoichi Ishida, Mitsugu Araki, Takayuki Kato, Kei Terayama, Yasushi Okuno

Nat. Mach. Intell., 2021

Structure-Based de Novo Molecular Generator Combined with Artificial Intelligence and Docking Simulations.

Biao Ma, Kei Terayama, Shigeyuki Matsumoto, Yuta Isaka, Yoko Sasakura, Hiroaki Iwata, Mitsugu Araki, Yasushi Okuno

J. Chem. Inf. Model., 2021

Accurate Binding Configuration Prediction of a G-Protein-Coupled Receptor to Its Antagonist Using Multicanonical Molecular Dynamics-Based Dynamic Docking.

Gert-Jan Bekker, Mitsugu Araki, Kanji Oshima, Yasushi Okuno, Narutoshi Kamiya

J. Chem. Inf. Model., 2021

2020

Exhaustive search of the configurational space of heat-shock protein 90 with its inhibitor by multicanonical molecular dynamics based dynamic docking.

Gert-Jan Bekker, Mitsugu Araki, Kanji Oshima, Yasushi Okuno, Narutoshi Kamiya

J. Comput. Chem., 2020

2018

Improving the Accuracy of Protein-Ligand Binding Mode Prediction Using a Molecular Dynamics-Based Pocket Generation Approach.

Mitsugu Araki, Hiroaki Iwata, Biao Ma, Atsuto Fujita, Kei Terayama, Yukari Sagae, Fumie Ono, Koji Tsuda, Narutoshi Kamiya, Yasushi Okuno

J. Comput. Chem., 2018

Machine learning accelerates MD-based binding pose prediction between ligands and proteins.

Kei Terayama, Hiroaki Iwata, Mitsugu Araki, Yasushi Okuno, Koji Tsuda

Bioinform., 2018

2016

The Effect of Conformational Flexibility on Binding Free Energy Estimation between Kinases and Their Inhibitors.

Mitsugu Araki, Narutoshi Kamiya, Miwa Sato, Masahiko Nakatsui, Takatsugu Hirokawa, Yasushi Okuno

J. Chem. Inf. Model., 2016