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To let you know about our research, this area contains 4 types of information about CLST; “Article”, “Videos”, “Event” and “Study”.
At “Article”, you can read articles on interviews and lectures, and you can enjoy the videos about CLST at “Videos”. If you want to meet and talk directly with the researcher, “Visit” give you some information of such events. You can find more difficult contents to know about our research deeply at “Study”.
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Structural Bioinformatics Team _Publication List

Structural Bioinformatics Team

1

Identification of new SUMO activating enzyme 1 inhibitors using virtual screening and scaffold hopping

Kumar A, Ito A, Hirohama M, Yoshida M, Zhang KY.
Bioorg Med Chem Lett, 26(4), 1218-1223 (2016).
2

Biomineralization of a Cadmium Chloride Nanocrystal by a Designed Symmetrical Protein.

Voet AR, Noguchi H, Addy C, Zhang KYJ, Tame JR.
Angew Chem Int Ed Engl., 54(34), 9857-9860 (2015).
3

Application of Shape Similarity in Pose Selection and Virtual Screening in CSARdock2014 Exercise

Kumar A, Zhang KY.
J Chem Inf Model,, (2015).
4

Advances in the development of SUMO specific protease (SENP) inhibitors

Kumar A, Zhang KY
Comput Struct Biotechnol J, 13, 204-211 (2015).
5

Quality assessment of predicted protein models using energies calculated by the fragment molecular orbital method

Simoncini D, Nakata H, Ogata K, Nakamura S, Zhang KYJ.
Mol Inform, 34(2-3), 97-104 (2015).
6

A fragmentation and reassembly method for ab initio phasing.

Shrestha R, Zhang KYJ.
Acta Crystallogr Sect D-Biol Crystallogr, 71(2), 304-312 (2015).
7

Computational design of a self-assembling symmetrical β-propeller protein

Voet AR, Noguchi H, Addy C, Simoncini D, Terada D, Unzai S, Park SY, Zhang KYJ, Tame JR.
Proc Natl Acad Sci USA, 111(42), 15102-15107 (2014).
8

Identification of sumoylation inhibitors targeting a predicted pocket in Ubc9

Kumar A, Ito A, Hirohama M, Yoshida M, Zhang KYJ.
J Chem Inf Model, 54, 2784-2793 (2014).
9

Hierarchical virtual screening approaches in small molecule drug discovery.

Kumar A, Zhang KY.
Methods,(71), 26-37 (2014).
10

Discovery of small molecule inhibitors targeting the SUMO–SIM interaction using a protein interface consensus approach

Voet ARD, Ito A, Hirohama M, Matsuoka S, Tochio N, Kigawa T, Yoshida M, Zhang KYJ.
Med Chem Commun, 5(6), 783-786 (2014).
11

Identification of 1,2,5-oxadiazoles as a new class of SENP2 inhibitors using structure based virtual screening.

Kumar A, Ito A, Takemoto M, Yoshida M, Zhang KYJ.
J Chem Inf Model, 54(3), 870-880 (2014).
12

A rotation-translation invariant molecular descriptor of partial charges and its use in ligand-based virtual screening

Berenger F, Voet A, Lee XY, Zhang KYJ.
Journal of Cheminformatics, 6(23), (2014).
13

Combining in silico and in cerebro approaches for virtual screening and pose prediction in SAMPL4

Voet AR, Kumar A, Berenger F, Zhang KYJ.
J Comput Aided Mol Des, 28(4), 363-373 (2014).
14

Electrostatic similarities between protein and small molecule ligands facilitate the design of protein-protein interaction inhibitors.

Voet A, Berenger F, Zhang KYJ.
PLoS One, 8(10), e75762 (2013).
15

Identification of quinazolinyloxy biaryl urea as a new class of SUMO activating enzyme 1 inhibitors.

Kumar A, Ito A, Hirohama M, Yoshida M, Zhang KYJ.
Bioorg Med Chem Lett, 23(18), 5145-5149 (2013).
16

Improving fragment quality for de novo structure prediction

Shrestha R, Zhang KYJ.
Proteins, 82(9), 2240-2252 (2013).
17

Efficient sampling in fragment-based protein structure prediction using an estimation of distribution algorithm.

Simoncini D, Zhang KYJ.
PLoS One, 8(7), e68954 (2013).
18

Investigation on the Effect of Key Water Molecules on Docking Performance in CSARdock Exercise

Kumar A, Zhang KYJ.
J Chem Inf Model, 53(8), 1880-1892 (2013).
19

Identification of sumoylation activating enzyme 1 inhibitors by structure-based virtual screening.

Kumar A, Ito A, Hirohama M, Yoshida M, Zhang KYJ.
J Chem Inf Model, 53(4), 809-820 (2013).
20

The discovery of novel hAR receptor antagonist chemotypes using a combined pharmacophore screening procedure.

Voet A, Helsen C, Zhang KYJ.
Chem Med Chem, 8(4), 644-651 (2013).
21

Error-estimation-guided rebuilding of de novo models increases the success rate of ab initio phasing.

Shrestha R, Simoncini D, Zhang KYJ.
Acta Crystallogr Sect D-Biol Crystallogr, 68(Pt11), 1522-1534 (2012).
22

A probabilistic fragment-based protein structure prediction algorithm.

Simoncini D, Berenger F, Shrestha R, Zhang KYJ.
PLoS One, 7(7), e38799 (2012).
23

Computational fragment-based screening using RosettaLigand: the SAMPL3 challenge.

Kumar A, Zhang KYJ.
J Comput Aided Mol Des, 26(5), 603-616 (2012).
24

Durandal: fast exact clustering of protein decoys.

Berenger F, Shrestha R, Zhou Y, Simoncini D, Zhang KYJ.
J Comput Chem, 33(4), 471-474 (2012).
25

Fragment based drug design: from experimental to computational approaches.

Kumar A, Voet A, Zhang KYJ.
Curr Med Chem, 19(30), 5128-5147 (2012).
26

Accelerating ab initio phasing with de novo models.

Shrestha R, Berenger F, Zhang KYJ.
Acta Crystallogr Sect D-Biol Crystallogr, 67(Pt9), 804-812 (2011).
27

Entropy-accelerated exact clustering of protein decoys.

Berenger F, Zhou Y, Shrestha R, Zhang KYJ.
Bioinformatics, 27(7), 939-945 (2011).

和文論文

CLST was reorganized into three centers according to the RIKEN 4th Medium-Term Plan from April 1, 2018. For the latest information of Structural Bioinformatics Team, please visit the following websites.


> The webpage of Laboratory for Structural Bioinformatics, Center for Biosystems Dynamics Research [http://www.bdr.riken.jp/en/research/labs/zhang-k/index.html]


> If you continue to browse this site, click here.