The Experts below are selected from a list of 1380 Experts worldwide ranked by ideXlab platform
Shuntaro Chiba - One of the best experts on this subject based on the ideXlab platform.
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An iterative compound screening contest method for identifying target Protein inhibitors using the tyrosine-Protein Kinase Yes
Scientific Reports, 2017Co-Authors: Shuntaro Chiba, Kazuyoshi Ikeda, Takashi Ishida, Y-h. Taguchi, Mitsuo Iwadate, Hideaki Umeyama, Masahiro Mochizuki, Reiji Teramoto, Chandrasekaran Ramakrishnan, A. Mary ThangakaniAbstract:We propose a new iterative screening contest method to identify target Protein inhibitors. After conducting a compound screening contest in 2014, we report results acquired from a contest held in 2015 in this study. Our aims were to identify target enzyme inhibitors and to benchmark a variety of computer-aided drug discovery methods under identical experimental conditions. In both contests, we employed the tyrosine-Protein Kinase Yes as an example target Protein. Participating groups virtually screened possible inhibitors from a library containing 2.4 million compounds. Compounds were ranked based on functional scores obtained using their respective methods, and the top 181 compounds from each group were selected. Our results from the 2015 contest show an improved hit rate when compared to results from the 2014 contest. In addition, we have successfully identified a statistically-warranted method for identifying target inhibitors. Quantitative analysis of the most successful method gave additional insights into important characteristics of the method used.
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Identification of potential inhibitors based on compound proposal contest: Tyrosine-Protein Kinase Yes as a target
Scientific Reports, 2015Co-Authors: Shuntaro Chiba, Kazuyoshi Ikeda, Takashi Ishida, M. Michael Gromiha, Y-h. Taguchi, Mitsuo Iwadate, Hideaki Umeyama, Kun-yi Hsin, Hiroaki Kitano, Kazuki YamamotoAbstract: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.
A. Mary Thangakani - One of the best experts on this subject based on the ideXlab platform.
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An iterative compound screening contest method for identifying target Protein inhibitors using the tyrosine-Protein Kinase Yes
Scientific Reports, 2017Co-Authors: Shuntaro Chiba, Kazuyoshi Ikeda, Takashi Ishida, Y-h. Taguchi, Mitsuo Iwadate, Hideaki Umeyama, Masahiro Mochizuki, Reiji Teramoto, Chandrasekaran Ramakrishnan, A. Mary ThangakaniAbstract:We propose a new iterative screening contest method to identify target Protein inhibitors. After conducting a compound screening contest in 2014, we report results acquired from a contest held in 2015 in this study. Our aims were to identify target enzyme inhibitors and to benchmark a variety of computer-aided drug discovery methods under identical experimental conditions. In both contests, we employed the tyrosine-Protein Kinase Yes as an example target Protein. Participating groups virtually screened possible inhibitors from a library containing 2.4 million compounds. Compounds were ranked based on functional scores obtained using their respective methods, and the top 181 compounds from each group were selected. Our results from the 2015 contest show an improved hit rate when compared to results from the 2014 contest. In addition, we have successfully identified a statistically-warranted method for identifying target inhibitors. Quantitative analysis of the most successful method gave additional insights into important characteristics of the method used.
Y-h. Taguchi - One of the best experts on this subject based on the ideXlab platform.
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An iterative compound screening contest method for identifying target Protein inhibitors using the tyrosine-Protein Kinase Yes
Scientific Reports, 2017Co-Authors: Shuntaro Chiba, Kazuyoshi Ikeda, Takashi Ishida, Y-h. Taguchi, Mitsuo Iwadate, Hideaki Umeyama, Masahiro Mochizuki, Reiji Teramoto, Chandrasekaran Ramakrishnan, A. Mary ThangakaniAbstract:We propose a new iterative screening contest method to identify target Protein inhibitors. After conducting a compound screening contest in 2014, we report results acquired from a contest held in 2015 in this study. Our aims were to identify target enzyme inhibitors and to benchmark a variety of computer-aided drug discovery methods under identical experimental conditions. In both contests, we employed the tyrosine-Protein Kinase Yes as an example target Protein. Participating groups virtually screened possible inhibitors from a library containing 2.4 million compounds. Compounds were ranked based on functional scores obtained using their respective methods, and the top 181 compounds from each group were selected. Our results from the 2015 contest show an improved hit rate when compared to results from the 2014 contest. In addition, we have successfully identified a statistically-warranted method for identifying target inhibitors. Quantitative analysis of the most successful method gave additional insights into important characteristics of the method used.
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Identification of potential inhibitors based on compound proposal contest: Tyrosine-Protein Kinase Yes as a target
Scientific Reports, 2015Co-Authors: Shuntaro Chiba, Kazuyoshi Ikeda, Takashi Ishida, M. Michael Gromiha, Y-h. Taguchi, Mitsuo Iwadate, Hideaki Umeyama, Kun-yi Hsin, Hiroaki Kitano, Kazuki YamamotoAbstract: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.
Hideaki Umeyama - One of the best experts on this subject based on the ideXlab platform.
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An iterative compound screening contest method for identifying target Protein inhibitors using the tyrosine-Protein Kinase Yes
Scientific Reports, 2017Co-Authors: Shuntaro Chiba, Kazuyoshi Ikeda, Takashi Ishida, Y-h. Taguchi, Mitsuo Iwadate, Hideaki Umeyama, Masahiro Mochizuki, Reiji Teramoto, Chandrasekaran Ramakrishnan, A. Mary ThangakaniAbstract:We propose a new iterative screening contest method to identify target Protein inhibitors. After conducting a compound screening contest in 2014, we report results acquired from a contest held in 2015 in this study. Our aims were to identify target enzyme inhibitors and to benchmark a variety of computer-aided drug discovery methods under identical experimental conditions. In both contests, we employed the tyrosine-Protein Kinase Yes as an example target Protein. Participating groups virtually screened possible inhibitors from a library containing 2.4 million compounds. Compounds were ranked based on functional scores obtained using their respective methods, and the top 181 compounds from each group were selected. Our results from the 2015 contest show an improved hit rate when compared to results from the 2014 contest. In addition, we have successfully identified a statistically-warranted method for identifying target inhibitors. Quantitative analysis of the most successful method gave additional insights into important characteristics of the method used.
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Identification of potential inhibitors based on compound proposal contest: Tyrosine-Protein Kinase Yes as a target
Scientific Reports, 2015Co-Authors: Shuntaro Chiba, Kazuyoshi Ikeda, Takashi Ishida, M. Michael Gromiha, Y-h. Taguchi, Mitsuo Iwadate, Hideaki Umeyama, Kun-yi Hsin, Hiroaki Kitano, Kazuki YamamotoAbstract: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.
Mitsuo Iwadate - One of the best experts on this subject based on the ideXlab platform.
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An iterative compound screening contest method for identifying target Protein inhibitors using the tyrosine-Protein Kinase Yes
Scientific Reports, 2017Co-Authors: Shuntaro Chiba, Kazuyoshi Ikeda, Takashi Ishida, Y-h. Taguchi, Mitsuo Iwadate, Hideaki Umeyama, Masahiro Mochizuki, Reiji Teramoto, Chandrasekaran Ramakrishnan, A. Mary ThangakaniAbstract:We propose a new iterative screening contest method to identify target Protein inhibitors. After conducting a compound screening contest in 2014, we report results acquired from a contest held in 2015 in this study. Our aims were to identify target enzyme inhibitors and to benchmark a variety of computer-aided drug discovery methods under identical experimental conditions. In both contests, we employed the tyrosine-Protein Kinase Yes as an example target Protein. Participating groups virtually screened possible inhibitors from a library containing 2.4 million compounds. Compounds were ranked based on functional scores obtained using their respective methods, and the top 181 compounds from each group were selected. Our results from the 2015 contest show an improved hit rate when compared to results from the 2014 contest. In addition, we have successfully identified a statistically-warranted method for identifying target inhibitors. Quantitative analysis of the most successful method gave additional insights into important characteristics of the method used.
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Identification of potential inhibitors based on compound proposal contest: Tyrosine-Protein Kinase Yes as a target
Scientific Reports, 2015Co-Authors: Shuntaro Chiba, Kazuyoshi Ikeda, Takashi Ishida, M. Michael Gromiha, Y-h. Taguchi, Mitsuo Iwadate, Hideaki Umeyama, Kun-yi Hsin, Hiroaki Kitano, Kazuki YamamotoAbstract: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.
