M. Sekijima

发表

Molecular dynamics simulation of dimeric and monomeric forms of human prion protein: insight into dynamics and properties.

Y. Akiyama, M. Sekijima, C. Motono, 2003, Biophysical journal.

Web Molecular Graphics: Emerging Technologies & Standards

S. O’Donoghue, M. Sekijima, M. Baaden, 2019 .

Crystal structure of a ten-amino acid protein.

Shinya Honda, Masakazu Sekijima, Yoshito Sawada, 2008, Journal of the American Chemical Society.

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 .

Analysis of motion features for molecular dynamics simulation of proteins

M. Takata, K. Joe, M. Sekijima, 2011 .

A prospective compound screening contest identified broader inhibitors for Sirtuin 1

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

Molecular dynamics simulations of cognate and non-cognate AspRS-tRNAAsp complexes

M. Sekijima, M. Michael Gromiha, C. Ramakrishnan, 2020, Journal of biomolecular structure & dynamics.

Molecular Dynamics Simulation of a Biomolecule with High Speed , Low Power and Accuracy Using GPU-Accelerated TSUBAME 2 . 0 Supercomputer

Toshio Endo, M. Sekijima, Shiqiao Du, 2011 .

Large-Scale Computing for Protein-Protein Binding Free Energy Calculation

Yoichi Muraoka, Sayaka Akioka, Tamotsu Noguchi, 2008, PDPTA.

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 .

Structural modeling of mutant α-glucosidases resulting in a processing/transport defect in Pompe disease

M. Sekijima, M. Kroos, K. Ohno, 2009, Journal of Human Genetics.

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).

Dephospho-Coenzyme A Kinase Is an Exploitable Drug Target against Plasmodium falciparum: Identification of Selective Inhibitors by High-Throughput Screening of a Large Chemical Compound Library

Kazuki Z. Yamamoto, M. Sekijima, T. Nozaki, 2022, Antimicrobial agents and chemotherapy.

Biochemical Studies of Mitochondrial Malate: Quinone Oxidoreductase from Toxoplasma gondii

M. Sekijima, T. Nozaki, K. Shiomi, 2021, International journal of molecular sciences.

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.

Identification of type I and type II inhibitors of c-Yes kinase using in silico and experimental techniques

Masakazu Sekijima, Yutaka Akiyama, M Michael Gromiha, 2018, Journal of biomolecular structure & dynamics.

Highlights from the 11th ISCB Student Council Symposium 2015

Giovanni Felici, Farzana Rahman, M. Michael Gromiha, 2016, BMC Bioinformatics.

Molecular Dynamics Simulation of Prion Protein by Large Scale Cluster Computing

Masakazu Sekijima, Yutaka Akiyama, Chie Motono, 2003, ISHPC.

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.

Membrane Phospholipid Analogues as Molecular Rulers to Probe the Position of Hydrophobic Contact Point of Lysophospholipid Ligands on the Surface of G-Protein-coupled Receptor during Membrane Approach.

M. Sekijima, J. Aoki, A. Inoue, 2020, Biochemistry.

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

M. Sekijima, Nobuaki Yasuo, 2015 .

Structure based approach for understanding organism specific recognition of protein-RNA complexes

M. Gromiha, M. Sekijima, C. Ramakrishnan, 2015, Biology Direct.

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.

Multidimensional analyses of the pathomechanism caused by the non-catalytic GNE variant, c.620A>T, in patients with GNE myopathy

Kazuki Z. Yamamoto, Y. Okada, M. Sekijima, 2022, 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..

Novel Calcium-Binding Ablating Mutations Induce Constitutive RET Activity and Drive Tumorigenesis

A. Okamoto, A. Ui, A. Otsuka, 2022, Cancer research.

Tackling Covid‐19 using disordered‐to‐order transition of residues in the spike protein upon angiotensin‐converting enzyme 2 binding

M. Gromiha, M. Sekijima, Dhanusha Yesudhas, 2021, Proteins.

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 .

Molecular mechanisms underlying oseltamivir resistance mediated by an I117V substitution in the neuraminidase of subtype H5N1 avian influenza A viruses.

Kimihito Ito, M. Sekijima, Ryo Takano, 2013, The Journal of infectious diseases.

Molecular Mechanisms Underlying Oseltamivir Resistance Mediated by an I 117 V Substitution in the Neuraminidase of Subtype H 5 N 1 Avian In fl uenza AViruses

Kimihito Ito, M. Sekijima, Ryo Takano, 2012 .

substitution in the NA of H5N1 avian influenza viruses

Kimihito Ito, M. Sekijima, Ryo Takano, 2012 .

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).

ProAffiMuSeq: sequence-based method to predict the binding free energy change of protein-protein complexes upon mutation using functional classification

Masakazu Sekijima, Sherlyn Jemimah, M Michael Gromiha, 2019, Bioinform..

Highlights from the 11th ISCB Student Council Symposium 2015

Zdenka Kuncic, Westa Domanova, Dan F. DeBlasio, 2016, BMC Bioinformatics.

Highlights from the eleventh ISCB Student Council Symposium 2015

Dan F. DeBlasio, Sean J. Humphrey, P. Bertolazzi, 2016 .

Impact of AlphaFold on structure prediction of protein complexes: The CASP15‐CAPRI experiment

Johnathan D. Guest, Adam K. Sieradzan, Charles W Christoffer, 2023, Proteins.

Free Energy Landscape Analysis System Based on Parallel Molecular Dynamics Simulation

Shinya Honda, Tamotsu Noguchi, Masakazu Sekijima, 2007 .

Enhancing the Performance of AlphaFold Through Modified Storage Method and Optimization of HHblits on TSUBAME3.0 Supercomputer

M. Sekijima, Hayato Fujita, Akihiro Nomura, 2023, 2023 Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE).

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 .