Nobuaki Yasuo

发表

Identification of potential inhibitors based on compound proposal contest: Tyrosine-protein kinase Yes as a target

Kun-Yi Hsin, Hiroaki Kitano, Y-h. Taguchi, 2015, Scientific Reports.

Tuning of Bayesian optimization for materials synthesis: simulation of the one-dimensional case

M. Sekijima, Shigeru Kobayashi, Y. Ando, 2022, Science and Technology of Advanced Materials: Methods.

Bayesian statistics-based analysis of AC impedance spectra

M. Sekijima, K. Nishio, Y. Ando, 2020 .

A prospective compound screening contest identified broader inhibitors for Sirtuin 1

Shogo D. Suzuki, Hironori K. Nakamura, Kazuki Z. Yamamoto, 2019, Scientific Reports.

Automatic determination of LQR weighting matrices for active structural control

Jinhua She, Daiki Sato, Nobuaki Yasuo, 2018, Engineering Structures.

Identification of key interactions between SARS-CoV-2 main protease and inhibitor drug candidates

M. Sekijima, Nobuaki Yasuo, Ryunosuke Yoshino, 2020, Scientific Reports.

Discovering a hidden binding site of spermidine synthase inhibitors for Chagas disease by combining molecular simulations and X-ray crystallography

T. Ishida, Y. Akiyama, M. Sekijima, 2021 .

MERMAID: an open source automated hit-to-lead method based on deep reinforcement learning

M. Sekijima, Nobuaki Yasuo, Daiki Erikawa, 2021, Journal of Cheminformatics.

Molecular Dynamics Simulation reveals the mechanism by which the Influenza Cap-dependent Endonuclease acquires resistance against Baloxavir marboxil

M. Sekijima, Nobuaki Yasuo, Ryunosuke Yoshino, 2019, Scientific Reports.

In silico, in vitro, X-ray crystallography, and integrated strategies for discovering spermidine synthase inhibitors for Chagas disease

T. Ishida, Y. Akiyama, M. Sekijima, 2017, Scientific Reports.

Toxicokinetic analysis of the anticoagulant rodenticides warfarin & diphacinone in Egyptian fruit bats (Rousettus aegyptiacus) as a comparative sensitivity assessment for Bonin fruit bats (Pteropus pselaphon).

M. Sekijima, T. Hashimoto, M. Ishizuka, 2022, Ecotoxicology and environmental safety.

An Improved Model for Predicting Compound Retrosynthesizability Using Machine Learning

M. Sekijima, Nobuaki Yasuo, Mami Ozawa, 2022, 2022 IEEE 22nd International Conference on Bioinformatics and Bioengineering (BIBE).

An iterative compound screening contest method for identifying target protein inhibitors using the tyrosine-protein kinase Yes

Daisuke Kihara, Takashi Ishida, Masakazu Sekijima, 2017, Scientific Reports.

Computer aided drug discovery review for infectious diseases with case study of anti-Chagas project.

T. Ishida, M. Sekijima, Nobuaki Yasuo, 2021, Parasitology international.

In silico, in vitro, X-ray crystallography, and integrated strategies for discovering spermidine synthase inhibitors for Chagas disease

T. Ishida, Y. Akiyama, M. Sekijima, 2017, Scientific Reports.

Compound property enhancement by virtual compound synthesis

Masakazu Sekijima, Nobuaki Yasuo, Naoki Arai, 2018, J. Bioinform. Comput. Biol..

Predicting Strategies for Lead Optimization via Learning to Rank

Masakazu Sekijima, Keisuke Watanabe, Nobuaki Yasuo, 2018 .

Exploring the selectivity of inhibitor complexes with Bcl-2 and Bcl-XL: A molecular dynamics simulation approach.

M. Sekijima, M. Ohue, Nobuaki Yasuo, 2018, Journal of molecular graphics & modelling.

Pharmacophore Modeling for Anti-Chagas Drug Design Using the Fragment Molecular Orbital Method

M. Sekijima, T. Honma, Yohsuke Hagiwara, 2015, PloS one.

Application for Evaluating and Visualizing the Sequence Conservation of Ligand-binding Sites

M. Sekijima, Nobuaki Yasuo, 2015 .

Improved Method of Structure-Based Virtual Screening via Interaction-Energy-Based Learning

Masakazu Sekijima, Nobuaki Yasuo, M. Sekijima, 2019, J. Chem. Inf. Model..

Effect of charged mutation on aggregation of a pentapeptide: Insights from molecular dynamics simulations

M. Sekijima, Sandeep Kumar, Puneet Rawat, 2021, Proteins.

Statistical potentials for RNA-protein interactions optimized by CMA-ES.

M. Sekijima, B. Lustig, Nobuaki Yasuo, 2021, Journal of molecular graphics & modelling.

An iterative compound screening contest method for identifying target protein inhibitors using the tyrosine-protein kinase Yes

Shogo D. Suzuki, Kazuki Z. Yamamoto, D. Kihara, 2017, Scientific Reports.

Tuning Bayesian optimization for materials synthesis: simulating two- and three-dimensional cases

M. Sekijima, Shigeru Kobayashi, Y. Ando, 2023, Science and Technology of Advanced Materials: Methods.

Screening for Inhibitors of Main Protease in SARS-CoV-2: In Silico and In Vitro Approach Avoiding Peptidyl Secondary Amides

Kazuki Z. Yamamoto, M. Sekijima, Nobuaki Yasuo, 2022, J. Chem. Inf. Model..

Screening for inhibitors of main protease in SARS-CoV-2: in silico and in vitro approach avoiding secondary amides

Kazuki Z. Yamamoto, M. Sekijima, Nobuaki Yasuo, 2021 .

CoDe-DTI: Collaborative Deep Learning-based Drug-Target Interaction Prediction

Yusuke Nakashima, Masakazu Sekijima, Nobuaki Yasuo, 2018, 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Gargoyles: An Open Source Graph-Based Molecular Optimization Method Based on Deep Reinforcement Learning

M. Sekijima, Shogo Nakamura, Nobuaki Yasuo, 2023, ACS omega.

Brain Wave (EEG) AI Analysis for the DX Era

A. Konagaya, E. Yonemochi, Kazuma Kaitoh, 2022 .

Development of FMODB and Auto -FMO protocol through 2022

Ryusuke Sawada, Michio Iwata, M. Sekijima, 2022 .

Prediction of CO2 absorbing performance of amine aqueous solution using random forest models

Nobuaki Yasuo, Takashi Makino, Tatsuya Fujii, 2024, Gas Science and Engineering.

Discovery of a Hidden Trypanosoma cruzi Spermidine Synthase Binding Site and Inhibitors through In Silico, In Vitro, and X-ray Crystallography

T. Ishida, Y. Akiyama, M. Sekijima, 2023, ACS omega.