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Sci Rep. 2015 Nov 26;5:17209. doi: 10.1038/srep17209.

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

Author information

1
Education Academy of Computational Life Sciences (ACLS), Tokyo Institute of Technology, 4259 Nagatsutacho, Midori-ku, Yokohama 226-8501 Japan.
2
Level Five Co. Ltd., Shiodome Shibarikyu Bldg., 1-2-3 Kaigan, Minato-ku, Tokyo 105-0022, Japan.
3
Department of Computer Science, Tokyo Institute of Technology, 2-12-1, Ookayama, Meguro-ku, Tokyo 152-8550 Japan.
4
Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai 600 036, Tamilnadu, India.
5
Department of Physics, Chuo University, 1-13-27 Kasuga, Bunkyo-ku, Tokyo 112-8551, Japan.
6
Department of Biological Sciences, Chuo University, 1-13-27 Kasuga, Bunkyo-ku, Tokyo 112-8551, Japan.
7
Okinawa Institute of Science and Technology Graduate University, 1919-1 Tancha, Onna-son, Kunigami, Okinawa 904-0495 Japan.
8
The Systems Biology Research Institute, Falcon Building 5F, 5-6-9 Shirokanedai, Minato-ku, Tokyo 108-0071 Japan.
9
Center for Integrative Medical Sciences, RIKEN, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama City, Kanagawa, 230-0045, Japan.
10
Research Center for Advanced Science and Technology, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8904 Japan.
11
PharmaDesign Inc., 2-19-8, Hatchobori, Chuo-ku, Tokyo 104-0032 Japan.
12
Department of Computational Science and Engineering, Nagoya University, Furocho, Chikusa, Nagoya 464-8603, Japan.
13
Division of Neurogenetics, Nagoya University Graduate School of Medicine, 65 Tsurumai, Showa-ku, Nagoya 466-8550, Japan.
14
Information and Mathematical Science and Bioinformatics Co., Ltd., Level 6 OWL TOWER, 4-21-1 Higashi-Ikebukuro, Toshima-ku, Tokyo 170-0013 Japan.
15
Global Scientific Information and Computing Center, Tokyo Institute of Technology 2-12-1, Ookayama, Meguro-ku, Tokyo 152-8550 Japan.
16
Department of Biotechnology, The University of Tokyo, 1-1-1 Yayoi, Nunkyo-ku, Tokyo, 113-8657.
17
Forerunner Pharma Research, Co., Ltd., Yokohama Bio Industry Center, 1-6 Shuehiro-cho, Tsurumi-ku, Yokohama 230-0045 Japan.
18
Centre of Advanced Study in Crystallography and Biophysics and Bioinformatics Infrastructure Facility (DBT Funded), University of Madras, Chennai 600025, Tamilnadu, India.
19
National Institutes of Biomedical Innovation, Health and Nutrition, 7-6-8 Saito-Asagi, Ibaraki, Osaka 567-0085 Japan.
20
Center for Life Science Technologies, RIKEN, 6-7-3 Minatojima-minamimachi, Chuo-ku, Kobe-shi, Hyogo 650-0047 Japan.
21
Molecular Profiling Research Center for Drug Discovery, National Institute of Advanced Industrial Science and Technology, 2-4-7 Aomi, Koto-ku, Tokyo, 135-0064, Japan.
22
Initiative for Parallel Bioinformatics, Level 14 Hibiya Central Building, 1-2-9 Nishi-Shimbashi Minato-Ku, Tokyo 105-0003 Japan.

Abstract

A search of broader range of chemical space is important for drug discovery. Different methods of computer-aided drug discovery (CADD) are known to propose compounds in different chemical spaces as hit molecules for the same target protein. This study aimed at using multiple CADD methods through open innovation to achieve a level of hit molecule diversity that is not achievable with any particular single method. We held a compound proposal contest, in which multiple research groups participated and predicted inhibitors of tyrosine-protein kinase Yes. This showed whether collective knowledge based on individual approaches helped to obtain hit compounds from a broad range of chemical space and whether the contest-based approach was effective.

PMID:
26607293
PMCID:
PMC4660442
DOI:
10.1038/srep17209
[Indexed for MEDLINE]
Free PMC Article

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