深層学習によるタンパク質水和構造予測 (ミニ特集 AIがもたらす構造生物学研究の変革)
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- 資料種別
- 記事
- 著者・編者
- 佐藤 航地大出 真央中迫 雅由
- シリーズタイトル
- 並列タイトル等
- Prediction of Protein Hydration using Deep Learning
- タイトル（掲載誌）
- 日本結晶学会誌 = Journal of the Crystallographic Society of Japan
- 巻号年月日等（掲載誌）
- 67(3):2025.8
- 掲載巻
- 67
- 掲載号
- 3
- 掲載ページ
- 170-175
- 掲載年月日（W3CDTF）
- 2025-08
- ISSN（掲載誌）
- 0369-4585
- ISSN-L（掲載誌）
- 0369-4585
- 出版事項（掲載誌）
- 東京 : 日本結晶学会
- 出版地（国名コード）
- JP
- 本文の言語コード
- jpn
- NDLC
- 対象利用者
- 一般
- 所蔵機関
- 国立国会図書館
- 請求記号
- Z15-138
- 連携機関・データベース
- 国立国会図書館 : 国立国会図書館雑誌記事索引
- 書誌ID（NDLBibID）
- 034356236
- 整理区分コード
- 632
- 要約等
- <p>Hydration is necessary for protein folding, stability, and functions. The hydration structure of proteins is formed inside proteins and at the interfaces between bulk solvent and protein, and has been visualized mostly using cryogenic X-ray crystallography. From massive structural data of proteins with hydration structures, we developed a three-dimensional convolutional network to generate distributions of the existence probability of hydration water molecules on protein surfaces and in protein cavities. We also devised a positional search method of hydration water molecules based on the probability maps. The predicted hydration sites are located on an average within 0.3 Å from the experimentally identified sites in crystal structures.</p>
- DOI
- 10.5940/jcrsj.67.170
- オンライン閲覧公開範囲
- インターネット公開
- 連携機関・データベース
- 科学技術振興機構 : J-STAGE
- 要約等
- <p>Hydration is necessary for protein folding, stability, and functions. The hydration structure of proteins is formed inside proteins and at the interfaces between bulk solvent and protein, and has been visualized mostly using cryogenic X-ray crystallography. From massive structural data of proteins with hydration structures, we developed a three-dimensional convolutional network to generate distributions of the existence probability of hydration water molecules on protein surfaces and in protein cavities. We also devised a positional search method of hydration water molecules based on the probability maps. The predicted hydration sites are located on an average within 0.3 Å from the experimentally identified sites in crystal structures.</p>
- DOI
- 10.5940/jcrsj.67.170
- 関連情報（URI）
- 参照
- Patterns and networks of hydrogen-bonds in the hydration structure of human lysozymeTertiary and Quaternary Structures of Photoreactive Fe-Type Nitrile Hydratase from <i>Rhodococcus</i> sp. N-771: Roles of Hydration Water Molecules in Stabilizing the Structures and the Structural Origin of the Substrate Specificity of the Enzyme<sup>,</sup>Novel non-heme iron center of nitrile hydratase with a claw setting of oxygen atomsHydration Structures of Proteinsgr Predictor: A Deep Learning Model for Predicting the Hydration Structures around ProteinsDistribution of Solvent Molecules Around Apolar Side-chains in Protein CrystalsGalaxyWater-CNN: Prediction of Water Positions on the Protein Structure by a 3D-Convolutional Neural NetworkSingle-particle Cryo-EM of Biological MacromoleculesApplication of empirical hydration distribution functions around polar atoms for assessing hydration structures of proteinsAssessment of Force Field Accuracy Using Cryogenic Electron Microscopy Data of Hyper-thermostable Glutamate DehydrogenaseWater structure of a hydrophobic protein at atomic resolution: Pentagon rings of water molecules in crystals of crambinPrediction of hydrophilic and hydrophobic hydration structure of protein by neural network optimized using experimental dataCryo <scp>EM</scp> and crystal structure analyses reveal the indirect role played by Trp89 in glutamate dehydrogenase enzymatic reactionsDesigning diving beetle inspired underwater robot(D.BeeBot)Influences of lone-pair electrons on directionality of hydrogen bonds formed by hydrophilic amino acid side chains in molecular dynamics simulationChanges in hydration structure are necessary for collective motions of a multi-domain proteinStructural mechanism of plant aquaporin gatingHydrate inclusion compoundsThe structure of aquaporinsInstantaneous generation of protein hydration properties from static structuresCoenzyme‐binding pathway on glutamate dehydrogenase suggested from multiple‐binding sites visualized by cryo‐electron microscopy<scp>UCSF ChimeraX</scp>: Structure visualization for researchers, educators, and developersAccurate Prediction of Hydration Sites of Proteins Using Energy Model With Atom EmbeddingCryoEM-sampling of metastable conformations appearing in cofactor-ligand association and catalysis of glutamate dehydrogenaseCrystallization of scytalone dehydratase F162A mutant in the unligated state and a preliminary X-ray diffraction study at 37 K3D Convolutional Neural Networks for Human Action RecognitionWhat is the best multi-stage architecture for object recognition?Energy landscape of domain motion in glutamate dehydrogenase deduced from cryo‐electron microscopyConvolutional Neural Networks for Speech RecognitionPrediction of Hydration Structures around Hydrophilic Surfaces of Proteins by Using the Empirical Hydration Distribution Functions from a Database AnalysisLarge-Scale Domain Movements and Hydration Structure Changes in the Active-Site Cleft of Unligated Glutamate Dehydrogenase from <i>Thermococcus profundus </i>Studied by Cryogenic X-ray Crystal Structure Analysis and Small-Angle X-ray Scattering<sup>,</sup>Large-scale networks of hydration water molecules around bovine β-trypsin revealed by cryogenic X-ray crystal structure analysisHydration structure of human lysozyme investigated by molecular dynamics simulation and cryogenic X‐ray crystal structure analyses: On the correlation between crystal water sites, solvent density, and solvent dipoleBuilding a More Predictive Protein Force Field: A Systematic and Reproducible Route to AMBER-FB15Probability Distributions of Hydration Water Molecules around Polar Protein Atoms Obtained by a Database AnalysisProtein Hydration and FunctionStructural Characteristics in Protein Hydration Investigated by Cryogenic X-ray Crystal Structure AnalysesImproved side‐chain torsion potentials for the Amber ff99SB protein force fieldWater–protein interactions from high–resolution protein crystallographyCryogenic X-ray Crystal Structure Analysis for the Complex of Scytalone Dehydratase of a Rice Blast Fungus and Its Tight-Binding Inhibitor, Carpropamid: The Structural Basis of Tight-Binding Inhibition<sup>,</sup>ImageNet classification with deep convolutional neural networks
- 連携機関・データベース
- 国立情報学研究所 : CiNii Research
- 提供元機関・データベース
- Japan Link Center雑誌記事索引データベースCrossref
- 書誌ID（NDLBibID）
- 034356236