岩田 浩明

Last Update: 2019/06/25 07:43:14

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Name(Kanji/Kana/Abecedarium Latinum)
岩田 浩明/イワタ ヒロアキ/Iwata, Hiroaki
Primary Affiliation(Org1/Job title)
Graduate Schools Medicine/Program-Specific Assistant Professor
Academic Degree
Field(Japanese) Field(English) University(Japanese) University(English) Method
修士(情報科学) 北海道大学
博士(情報学) 京都大学
researchmap URL
https://researchmap.jp/iwata97
Research Topics
(Japanese)
人工知能を用いたビッグデータ解析や分子動力学シミュレーションによる創薬関連手法の開発
(English)
Development of in silico drug discovery method using big data analysis with artificial intelligence and molecular dynamics simulation
Overview of the research
(Japanese)
我々の研究の目的は、化合物構造から標的タンパク質・薬効・フェノタイプ等を予測する機械学習モデルを構築することである。任意の化学構造式を入力することによりその予測結果を出力するAIシステムの開発を目指す。また、標的タンパク質と薬剤候補分子のドッキング計算における結合様式の予測、バーチャルスクリーニングの高精度化を目指している。これらの技術開発により、新薬開発の成功確率の向上を実現する。
(English)
The purpose of our research is to construct a machine learning model that predicts target proteins, efficacies, phenotypes, etc. from chemical structures. We aim to develop an AI system that outputs the prediction result by inputting an arbitrary chemical structural formula. In addition, we aim to predict binding modes of target proteins and drug candidate molecules by docking simulation and to improve the accuracy of virtual screening methods. These technological developments will improve the success rate of new drug development.
Fields of research (key words)
Key words(Japanese) Key words(English)
ケモインフォマティクス chemoinformatics
バイオインフォマティクス bioinformatics
インシリコ創薬 In silico drug discovery
target protein 標的タンパク質
分子動力学シミュレーション molecular dynamics simulation
機械学習 machine learning
製剤 pharmaceutical formulation
Published Papers
Author Author(Japanese) Author(English) Title Title(Japanese) Title(English) Bibliography Bibliography(Japanese) Bibliography(English) Publication date Refereed paper Language Publishing type Disclose
Kei Terayama, Hiroaki Iwata, Mitsugu Araki, Yasushi Okuno, Koji Tsuda Kei Terayama, Hiroaki Iwata, Mitsugu Araki, Yasushi Okuno, Koji Tsuda Kei Terayama, Hiroaki Iwata, Mitsugu Araki, Yasushi Okuno, Koji Tsuda Machine Learning Accelerates MD-based Binding-Pose Prediction between Ligands and Proteins Machine Learning Accelerates MD-based Binding-Pose Prediction between Ligands and Proteins Machine Learning Accelerates MD-based Binding-Pose Prediction between Ligands and Proteins Bioinformatics, 34, 5, 770-778 Bioinformatics, 34, 5, 770-778 Bioinformatics, 34, 5, 770-778 2018 Refereed English Research paper(scientific journal) Disclose to all
Mitsugu Araki*, Hiroaki Iwata* Biao Ma, Atsuto Fujita, Kei Terayama, Yukari Sagae, Fumie Ono, Koji Tsuda, Narutoshi Kamiya, Yasushi Okuno Mitsugu Araki*, Hiroaki Iwata* Biao Ma, Atsuto Fujita, Kei Terayama, Yukari Sagae, Fumie Ono, Koji Tsuda, Narutoshi Kamiya, Yasushi Okuno Mitsugu Araki*, Hiroaki Iwata* Biao Ma, Atsuto Fujita, Kei Terayama, Yukari Sagae, Fumie Ono, Koji Tsuda, Narutoshi Kamiya, Yasushi Okuno Improving the accuracy of protein-ligand binding mode prediction using a molecular dynamics-based pocket generation approach Improving the accuracy of protein-ligand binding mode prediction using a molecular dynamics-based pocket generation approach Improving the accuracy of protein-ligand binding mode prediction using a molecular dynamics-based pocket generation approach Journal of Computational Chemistry, 39, 2679-2689 Journal of Computational Chemistry, 39, 2679-2689 Journal of Computational Chemistry, 39, 2679-2689 2018 Refereed English Research paper(scientific journal) Disclose to all
Michio Iwata, Ryusuke Sawada, Hiroaki Iwata, Masaaki Kotera, Yoshihiro Yamanishi Michio Iwata, Ryusuke Sawada, Hiroaki Iwata, Masaaki Kotera, Yoshihiro Yamanishi Michio Iwata, Ryusuke Sawada, Hiroaki Iwata, Masaaki Kotera, Yoshihiro Yamanishi Elucidating the modes of action for bioactive compounds in a cell-specific manner by large-scale chemically-induced transcriptomics Elucidating the modes of action for bioactive compounds in a cell-specific manner by large-scale chemically-induced transcriptomics Elucidating the modes of action for bioactive compounds in a cell-specific manner by large-scale chemically-induced transcriptomics Scientific Reports, 7 Scientific Reports, 7 Scientific Reports, 7 2017 Refereed English Research paper(scientific journal) Disclose to all
Masatoshi Hamanaka, Kei Taneishi, Hiroaki Iwata, Jun Ye, Jianguo Pei, Jinlong Hou, Yasushi Okuno Masatoshi Hamanaka, Kei Taneishi, Hiroaki Iwata, Jun Ye, Jianguo Pei, Jinlong Hou, Yasushi Okuno Masatoshi Hamanaka, Kei Taneishi, Hiroaki Iwata, Jun Ye, Jianguo Pei, Jinlong Hou, Yasushi Okuno CGBVS‐DNN: Prediction of Compound‐protein Interactions Based on Deep Learning CGBVS‐DNN: Prediction of Compound‐protein Interactions Based on Deep Learning CGBVS‐DNN: Prediction of Compound‐protein Interactions Based on Deep Learning Molecular Informatics, 36, 1-2 Molecular Informatics, 36, 1-2 Molecular Informatics, 36, 1-2 2017 Refereed English Research paper(scientific journal) Disclose to all
Hiroaki Iwata, Ryusuke Sawada, Sayaka Mizutani, Yoshihiro Yamanishi Hiroaki Iwata, Ryusuke Sawada, Sayaka Mizutani, Yoshihiro Yamanishi Hiroaki Iwata, Ryusuke Sawada, Sayaka Mizutani, Yoshihiro Yamanishi Systematic Drug Repositioning for a Wide Range of Diseases with Integrative Analyses of Phenotypic and Molecular Data Systematic Drug Repositioning for a Wide Range of Diseases with Integrative Analyses of Phenotypic and Molecular Data Systematic Drug Repositioning for a Wide Range of Diseases with Integrative Analyses of Phenotypic and Molecular Data Journal of chemical information and modeling, 55, 2, 446-459 Journal of chemical information and modeling, 55, 2, 446-459 Journal of chemical information and modeling, 55, 2, 446-459 2015 Refereed English Research paper(scientific journal) Disclose to all
Hiroaki Iwata, Ryusuke Sawada, Sayaka Mizutani, Masaaki Kotera, Yoshihiro Yamanishi Hiroaki Iwata, Ryusuke Sawada, Sayaka Mizutani, Masaaki Kotera, Yoshihiro Yamanishi Hiroaki Iwata, Ryusuke Sawada, Sayaka Mizutani, Masaaki Kotera, Yoshihiro Yamanishi Large-Scale Prediction of Beneficial Drug Combinations Using Drug Efficacy and Target Profiles Large-Scale Prediction of Beneficial Drug Combinations Using Drug Efficacy and Target Profiles Large-Scale Prediction of Beneficial Drug Combinations Using Drug Efficacy and Target Profiles Journal of chemical information and modeling, 55, 12, 2705-2716 Journal of chemical information and modeling, 55, 12, 2705-2716 Journal of chemical information and modeling, 55, 12, 2705-2716 2015 Refereed English Research paper(scientific journal) Disclose to all
Ryusuke Sawada, Hiroaki Iwata, Sayaka Mizutani, Yoshihiro Yamanishi Ryusuke Sawada, Hiroaki Iwata, Sayaka Mizutani, Yoshihiro Yamanishi Ryusuke Sawada, Hiroaki Iwata, Sayaka Mizutani, Yoshihiro Yamanishi Target-based drug repositioning using large-scale chemical-protein interactome data Target-based drug repositioning using large-scale chemical-protein interactome data Target-based drug repositioning using large-scale chemical-protein interactome data Journal of chemical information and modeling, 55, 12, 2717-2730 Journal of chemical information and modeling, 55, 12, 2717-2730 Journal of chemical information and modeling, 55, 12, 2717-2730 2015 Refereed English Research paper(scientific journal) Disclose to all
Kazuhiro Sakamaki, Naoyuki Iwabe, Hiroaki Iwata, Kenichiro Imai, Chiyo Takagi, Kumiko Chiba, Chisa Shukunami, Kentaro Tomii, Naoto Ueno Kazuhiro Sakamaki, Naoyuki Iwabe, Hiroaki Iwata, Kenichiro Imai, Chiyo Takagi, Kumiko Chiba, Chisa Shukunami, Kentaro Tomii, Naoto Ueno Kazuhiro Sakamaki, Naoyuki Iwabe, Hiroaki Iwata, Kenichiro Imai, Chiyo Takagi, Kumiko Chiba, Chisa Shukunami, Kentaro Tomii, Naoto Ueno Conservation of structure and Function in vertebrate c-FLIP proteins despite rapid evolutionary change Conservation of structure and Function in vertebrate c-FLIP proteins despite rapid evolutionary change Conservation of structure and Function in vertebrate c-FLIP proteins despite rapid evolutionary change Biochemistry and Biophysics Reports, 3, 175-189 Biochemistry and Biophysics Reports, 3, 175-189 Biochemistry and Biophysics Reports, 3, 175-189 2015 Refereed English Research paper(scientific journal) Disclose to all
Kazuhiro Sakamaki, Kouhei Shimizu, Hiroaki Iwata, Kenichiro Imai, Yutaka Satou, Noriko Funayama, Masami Nozaki, Mamiko Yajima, Osamu Nishimura, Mayura Higuchi, Kumiko Chiba, Michi Yoshimoto, Haruna Kimura, Andrew Y. Gracey, Takashi Shimizu, Kentaro Tomii, Osamu Gotoh, Koji Akasaka, Tatsuya Sawasaki, David J. Miller Kazuhiro Sakamaki, Kouhei Shimizu, Hiroaki Iwata, Kenichiro Imai, Yutaka Satou, Noriko Funayama, Masami Nozaki, Mamiko Yajima, Osamu Nishimura, Mayura Higuchi, Kumiko Chiba, Michi Yoshimoto, Haruna Kimura, Andrew Y. Gracey, Takashi Shimizu, Kentaro Tomii, Osamu Gotoh, Koji Akasaka, Tatsuya Sawasaki, David J. Miller Kazuhiro Sakamaki, Kouhei Shimizu, Hiroaki Iwata, Kenichiro Imai, Yutaka Satou, Noriko Funayama, Masami Nozaki, Mamiko Yajima, Osamu Nishimura, Mayura Higuchi, Kumiko Chiba, Michi Yoshimoto, Haruna Kimura, Andrew Y. Gracey, Takashi Shimizu, Kentaro Tomii, Osamu Gotoh, Koji Akasaka, Tatsuya Sawasaki, David J. Miller The apoptotic initiator caspase-8: its functional ubiquity and genetic diversity during animal evolution The apoptotic initiator caspase-8: its functional ubiquity and genetic diversity during animal evolution The apoptotic initiator caspase-8: its functional ubiquity and genetic diversity during animal evolution Molecular Biology and Evolution Molecular Biology and Evolution Molecular Biology and Evolution 2014 Refereed English Research paper(scientific journal) Disclose to all
Hiroaki Iwata*, Sayaka Mizutani*, Yasuo Tabei, Masaaki Kotera, Susumu Goto, Yoshihiro Yamanishi Hiroaki Iwata*, Sayaka Mizutani*, Yasuo Tabei, Masaaki Kotera, Susumu Goto, Yoshihiro Yamanishi Hiroaki Iwata*, Sayaka Mizutani*, Yasuo Tabei, Masaaki Kotera, Susumu Goto, Yoshihiro Yamanishi Inferring protein domains associated with drug side effects based on drug-target interaction network Inferring protein domains associated with drug side effects based on drug-target interaction network Inferring protein domains associated with drug side effects based on drug-target interaction network BMC Systems Biology, 7.Suppl 6 BMC Systems Biology, 7.Suppl 6 BMC Systems Biology, 7.Suppl 6 2013 Refereed English Research paper(scientific journal) Disclose to all
Hiroaki Iwata, Osamu Gotoh Hiroaki Iwata, Osamu Gotoh Hiroaki Iwata, Osamu Gotoh Benchmarking spliced alignment programs including Spaln2, an extended version of Spaln that incorporates additional species-specific features Benchmarking spliced alignment programs including Spaln2, an extended version of Spaln that incorporates additional species-specific features Benchmarking spliced alignment programs including Spaln2, an extended version of Spaln that incorporates additional species-specific features Nucleic Acids Research, 40, 20 Nucleic Acids Research, 40, 20 Nucleic Acids Research, 40, 20 2012 Refereed English Research paper(scientific journal) Disclose to all
Hiroaki Iwata, Osamu Gotoh Hiroaki Iwata, Osamu Gotoh Hiroaki Iwata, Osamu Gotoh Comparative analysis of information contents relevant to recognition of introns in many species Comparative analysis of information contents relevant to recognition of introns in many species Comparative analysis of information contents relevant to recognition of introns in many species BMC Genomics, 12, 45 BMC Genomics, 12, 45 BMC Genomics, 12, 45 2011 Refereed English Research paper(scientific journal) Disclose to all

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Title language:
Conference Activities & Talks
Title Title(Japanese) Title(English) Conference Conference(Japanese) Conference(English) Promotor Promotor(Japanese) Promotor(English) Date Language Assortment Disclose
Perfomance Evaluation of Compound-protein Interaction Prediction using Graph Convolutional Network Perfomance Evaluation of Compound-protein Interaction Prediction using Graph Convolutional Network Perfomance Evaluation of Compound-protein Interaction Prediction using Graph Convolutional Network 情報計算化学生物学会2018年大会(CBI 2018) 情報計算化学生物学会2018年大会(CBI 2018) 2018/10 Japanese Oral presentation(general) Disclose to all
化合物-タンパク質-フェノタイプの多階層モデルによる標的タンパク質予測[Invited] 化合物-タンパク質-フェノタイプの多階層モデルによる標的タンパク質予測 [Invited] 第39回ケモインフォマティクス討論会 第39回ケモインフォマティクス討論会 2016/09 Japanese Oral presentation(invited, special) Disclose to all
Title language:
Books etc
Author Author(Japanese) Author(English) Title Title(Japanese) Title(English) Publisher Publisher(Japanese) Publisher(English) Publication date Language Type Disclose
岩田浩明, 小島諒介, 玉田嘉紀 岩田浩明, 小島諒介, 玉田嘉紀 創薬とIT 創薬とIT ニューサイエンス社 ニューサイエンス社 2019/05 Joint Work Disclose to all
Title language:
External funds: competitive funds and Grants-in-Aid for Scientific Research (Kakenhi)
Type Position Title(Japanese) Title(English) Period
新学術領域研究(研究領域提案型) Representative 最適化アルゴリズムを用いたドラッガブルポケット構造の高速探索手法の開発 2018/04/01-2020/03/31