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Tohru Terada

Showing results (51-60 of 113) with videos related to

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Biochemistry|November 20, 2013
Heme binding mechanism of structurally similar iron-regulated surface determinant near transporter domains of Staphylococcus aureus exhibiting different affinities for hemeYoshitaka Moriwaki, Tohru Terada, Jose M M Caaveiro, et al.
Journal of Structural and Functional Genomics|July 13, 2016
Development of a protein-ligand-binding site prediction method based on interaction energy and sequence conservationHiroto Tsujikawa, Kenta Sato, Cao Wei, et al.
Elife|March 7, 2018
Energetics and conformational pathways of functional rotation in the multidrug transporter AcrBYasuhiro Matsunaga, Tsutomu Yamane, Tohru Terada, et al.
The FEBS Journal|November 3, 2010
Molecular defect of isovaleryl-CoA dehydrogenase in the skunk mutant of silkworm, Bombyx moriKei Urano, Takaaki Daimon, Yutaka Banno, et al.
Plos One|August 20, 2014
Oligomerization mechanisms of an H-NS family protein, Pmr, encoded on the plasmid pCAR1 provide a molecular basis for functions of H-NS family membersChiho Suzuki, Kohei Kawazuma, Shoichiro Horita, et al.
Nature Chemical Biology|September 22, 2022
Chemigenetic indicators based on synthetic chelators and green fluorescent proteinWenchao Zhu, Shiori Takeuchi, Shosei Imai, et al.
Science Advances|June 17, 2021
Cryo-EM structure of the photosynthetic RC-LH1-PufX supercomplex at 2.8-Å resolutionLaura Bracun, Atsushi Yamagata, Bern M Christianson, et al.
FEBS Letters|October 7, 2016
Structural similarities and differences in H-NS family proteins revealed by the N-terminal structure of TurB in Pseudomonas putida KT2440Chiho Suzuki-Minakuchi, Kohei Kawazuma, Jun Matsuzawa, et al.
Computational Biology and Chemistry|November 28, 2016
Development of a sugar-binding residue prediction system from protein sequences using support vector machineMasaki Banno, Yusuke Komiyama, Wei Cao, et al.
Biophysical Reviews|March 13, 2020
Development of a deep learning-based method to identify "good" regions of a cryo-electron microscopy gridYuichi Yokoyama, Tohru Terada, Kentaro Shimizu, et al.
Pageof 12

Showing results (51-60 of 113) with videos related to

Sort By:
Pageof 12
Biochemistry|November 20, 2013
Heme binding mechanism of structurally similar iron-regulated surface determinant near transporter domains of Staphylococcus aureus exhibiting different affinities for hemeYoshitaka Moriwaki, Tohru Terada, Jose M M Caaveiro, et al.
Journal of Structural and Functional Genomics|July 13, 2016
Development of a protein-ligand-binding site prediction method based on interaction energy and sequence conservationHiroto Tsujikawa, Kenta Sato, Cao Wei, et al.
Elife|March 7, 2018
Energetics and conformational pathways of functional rotation in the multidrug transporter AcrBYasuhiro Matsunaga, Tsutomu Yamane, Tohru Terada, et al.
The FEBS Journal|November 3, 2010
Molecular defect of isovaleryl-CoA dehydrogenase in the skunk mutant of silkworm, Bombyx moriKei Urano, Takaaki Daimon, Yutaka Banno, et al.
Plos One|August 20, 2014
Oligomerization mechanisms of an H-NS family protein, Pmr, encoded on the plasmid pCAR1 provide a molecular basis for functions of H-NS family membersChiho Suzuki, Kohei Kawazuma, Shoichiro Horita, et al.
Nature Chemical Biology|September 22, 2022
Chemigenetic indicators based on synthetic chelators and green fluorescent proteinWenchao Zhu, Shiori Takeuchi, Shosei Imai, et al.
Science Advances|June 17, 2021
Cryo-EM structure of the photosynthetic RC-LH1-PufX supercomplex at 2.8-Å resolutionLaura Bracun, Atsushi Yamagata, Bern M Christianson, et al.
FEBS Letters|October 7, 2016
Structural similarities and differences in H-NS family proteins revealed by the N-terminal structure of TurB in Pseudomonas putida KT2440Chiho Suzuki-Minakuchi, Kohei Kawazuma, Jun Matsuzawa, et al.
Computational Biology and Chemistry|November 28, 2016
Development of a sugar-binding residue prediction system from protein sequences using support vector machineMasaki Banno, Yusuke Komiyama, Wei Cao, et al.
Biophysical Reviews|March 13, 2020
Development of a deep learning-based method to identify "good" regions of a cryo-electron microscopy gridYuichi Yokoyama, Tohru Terada, Kentaro Shimizu, et al.
Pageof 12