Updated on 2024/03/12

写真b

 
DOI Hideo
 
*Items subject to periodic update by Rikkyo University (The rest are reprinted from information registered on researchmap.)
Affiliation*
College of Science Department of Chemistry
Title*
Assistant Professor
Research Interests
  • molecular simulation

  • computational chemistry

  • Campus Career*
    • 4 2022 - Present 
      College of Science   Department of Chemistry   Assistant Professor
     

    Papers

    • Enhancement of energy decomposition analysis in fragment molecular orbital calculations

      Sota Matsuoka, Kota Sakakura, Yoshinobu Akinaga, Kazuki Akisawa, Koji Okuwaki, Hideo Doi, Yuji Mochizuki

      Journal of Computational Chemistry   29 12 2023

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      Language:English   Publishing type:Research paper (scientific journal)  

      <jats:title>Abstract</jats:title><jats:p>Energy decomposition analysis is one of the most attractive features of fragment molecular orbital (FMO) calculations from the point of view of practical applications. Here we report some enhancements for PIEDA in the ABINIT‐MP program. One is a separation of the dispersion‐type stabilization from the electron correlation energy, traditionally referred to as the “dispersion interaction” (DI). Another is an alternative evaluation of the electrostatic (ES) interaction using the restrained electrostatic potential (RESP) charges. The GA:CT stacked base pair and the Trp‐Cage miniprotein were used as illustrative examples.</jats:p>

      DOI: 10.1002/jcc.27297

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    • Development of reverse mapping system bridging dissipative particle dynamics and fragment molecular orbital calculation

      Koji Okuwaki, Hideo Doi, Taku Ozawa, Yuji Mochizuki

      Japanese Journal of Applied Physics   23 10 2023

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      Publishing type:Research paper (scientific journal)   Publisher:IOP Publishing  

      Abstract

      We have developed a reverse mapping system to convert mesoscale structures generated by dissipative particle dynamics (DPD) simulations into nanoscale structures. This system is called DSRMS (DPD-based Structure Reverse Mapping System) and is controlled by Python3 scripts using OCTA's COGNAC program for DPD and molecular dynamics (MD). The restored structures can be subjected to fragment molecular orbital (FMO) calculations using the ABINIT-MP program for detailed nanoscale interaction analysis. Polyelectrolyte and lipid membranes have been used as illustrative example.

      DOI: 10.35848/1347-4065/ad0601

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      Other Link: https://iopscience.iop.org/article/10.35848/1347-4065/ad0601/pdf

    • Dissipative particle dynamics simulation for peptoid nanosheet with non-empirical parameter set

      Yusuke Tachino, Koji Okuwaki, Hideo Doi, Kazuki Akisawa, Yuji Mochizuki

      Japanese Journal of Applied Physics   23 8 2023

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      Publishing type:Research paper (scientific journal)   Publisher:IOP Publishing  

      Abstract

      Peptoids are biomimetic materials in which the substituent groups are located on the nitrogen atom of the peptide bond, facilitating the formation of nanosheet structures as reported by Mannige et al. (Nature, 526 (2015) 415). Dissipative particle dynamics (DPD) simulations were performed to investigate the aggregation stability of peptoids with different unit lengths. The crucial effective interaction parameters were determined by fragment molecular orbital (FMO) calculations, which allowed to evaluate different molecular interactions (electrostatic and dispersion) in a balanced way. The experimental observation of the unit length dependence was finally reproduced by this FMO-DPD method.

      DOI: 10.35848/1347-4065/acf356

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      Other Link: https://iopscience.iop.org/article/10.35848/1347-4065/acf356/pdf

    • Machine learning to improve efficiency of non-empirical interaction parameter for dissipative particle dynamics (DPD) simulation

      Hideo Doi, Sota Matsuoka, Koji Okuwaki, Ryo Hatada, Soujiro Minami, Ryosuke Suhara, Yuji Mochizuki

      Japanese Journal of Applied Physics   7 7 2023

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      Publishing type:Research paper (scientific journal)   Publisher:IOP Publishing  

      Abstract

      We have attempted to use machine learning to streamline the calculation of non-empirical &amp;#xD;parameters for use in dissipative particle dynamics (DPD) simulations. We replaced the &amp;#xD;calculation of molecular interaction energies by the non-empirical molecular orbital method, &amp;#xD;which requires a lot of computational resources, with predictions by machine learning. We &amp;#xD;developed two methods for prediction replacement, which are a 1-step method and a 2-step &amp;#xD;method. The prediction accuracy of the results obtained with these methods was investigated. &amp;#xD;A reduction of about half of the computational cost was expected.

      DOI: 10.35848/1347-4065/ace575

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      Other Link: https://iopscience.iop.org/article/10.35848/1347-4065/ace575/pdf

    • タンパク質に関する FMO-DPD シミュレーション用パラメータ算定と試行

      Yusuke TACHINO, Hideo DOI, Koji OKUWAKI, Yoshinori HIRANO, Yuji MOCHIZUKI

      Journal of Computer Chemistry, Japan22 ( 2 ) 15 - 17   2023

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      Publishing type:Research paper (scientific journal)   Publisher:Society of Computer Chemistry Japan  

      DOI: 10.2477/jccj.2023-0019

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    • Regression analysis for predicting the elasticity of liquid crystal elastomers

      Hideo Doi, Kazuaki Z. Takahashi, Haruka Yasuoka, Jun-ichi Fukuda, Takeshi Aoyagi

      Scientific Reports12 ( 1 )   17 11 2022

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      Publishing type:Research paper (scientific journal)   Publisher:Springer Science and Business Media LLC  

      Abstract

      It is highly desirable but difficult to understand how microscopic molecular details influence the macroscopic material properties, especially for soft materials with complex molecular architectures. In this study we focus on liquid crystal elastomers (LCEs) and aim at identifying the design variables of their molecular architectures that govern their macroscopic deformations. We apply the regression analysis using machine learning (ML) to a database containing the results of coarse grained molecular dynamics simulations of LCEs with various molecular architectures. The predictive performance of a surrogate model generated by the regression analysis is also tested. The database contains design variables for LCE molecular architectures, system and simulation conditions, and stress–strain curves for each LCE molecular system. Regression analysis is applied using the stress–strain curves as objective variables and the other factors as explanatory variables. The results reveal several descriptors governing the stress–strain curves. To test the predictive performance of the surrogate model, stress–strain curves are predicted for LCE molecular architectures that were not used in the ML scheme. The predicted curves capture the characteristics of the results obtained from molecular dynamics simulations. Therefore, the ML scheme has great potential to accelerate LCE material exploration by detecting the key design variables in the molecular architecture and predicting the LCE deformations.

      DOI: 10.1038/s41598-022-23897-0

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      Other Link: https://www.nature.com/articles/s41598-022-23897-0

    • Screening toward the Development of Fingerprints of Atomic Environments Using Bond-Orientational Order Parameters

      Hideo Doi, Kazuaki Z. Takahashi, Takeshi Aoyagi

      ACS Omega7 ( 5 ) 4606 - 4613   8 2 2022

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      Language:English   Publishing type:Research paper (scientific journal)   Publisher:American Chemical Society ({ACS})  

      DOI: 10.1021/acsomega.1c06587

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    • Mining of Effective Local Order Parameters to Classify Ice Polymorphs

      Hideo Doi, Kazuaki Z. Takahashi, Takeshi Aoyagi

      The Journal of Physical Chemistry A125 ( 43 ) 9518 - 9526   22 10 2021

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      Language:English   Publishing type:Research paper (scientific journal)   Publisher:American Chemical Society ({ACS})  

      DOI: 10.1021/acs.jpca.1c06685

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    • Searching for local order parameters to classify water structures at triple points

      Hideo Doi, Kazuaki Z. Takahashi, Takeshi Aoyagi

      Journal of Computational Chemistry42 ( 24 ) 1720 - 1727   15 9 2021

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      Language:English   Publishing type:Research paper (scientific journal)   Publisher:Wiley  

      DOI: 10.1002/jcc.26707

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      Other Link: https://onlinelibrary.wiley.com/doi/full-xml/10.1002/jcc.26707

    • Searching local order parameters to classify water structures of ice Ih, Ic, and liquid

      Hideo Doi, Kazuaki Z. Takahashi, Takeshi Aoyagi

      The Journal of Chemical Physics154 ( 16 ) 164505 - 164505   28 4 2021

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      Language:English   Publishing type:Research paper (scientific journal)   Publisher:{AIP} Publishing  

      DOI: 10.1063/5.0049258

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    • Mining of effective local order parameters for classifying crystal structures: A machine learning study

      Hideo Doi, Kazuaki Z. Takahashia, Takeshi Aoyagi

      The Journal of Chemical Physics152 ( 21 ) 214501 - 214501   7 6 2020

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      Language:English   Publishing type:Research paper (scientific journal)   Publisher:AIP Publishing  

      DOI: 10.1063/5.0005228

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    • Ab Initio Fragment Molecular Orbital-Based Molecular Dynamics (FMO-MD) Simulations of (NH3)32 Cluster: Effects of Electron Correlation

      Moeko Ninomiya, Hideo Doi, Yoshiteru Matsumoto, Yuji Mochizuki, Yuto Komeiji

      Bulletin of the Chemical Society of Japan93 ( 4 ) 553 - 560   15 4 2020

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      Language:English   Publishing type:Research paper (scientific journal)   Publisher:The Chemical Society of Japan  

      An isolated cluster of 32 ammonia (NH3) molecules was simulated at 50 and 100K by the ab initio fragment molecular orbital based molecular dynamics (FMO-MD) method to analyze the effect of electron correlation via second-order MollerPlesset perturbation (MP2). Both the energy and force of the system were calculated at the MP2 and Hartree-Fock (HF) levels with the 6-31G** basis set. The radial distribution and angular distribution functions were obtained from the trajectories. A comparison of MP2 and HF suggested that the electroncorrelation effect via MP2 leads to relative condensation through electron delocalization, similar to the case of water. Vibrational spectra were also calculated at both the MP2 and HF levels, and the former gave a more minute split of the higher modes. This again suggested that MP2 better describes the electron delocalization.

      DOI: 10.1246/bcsj.20190320

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    • Stabilization Mechanism for a Non-fibrillar Amyloid β Oligomer Based on Formation of a Hydrophobic Core Determined by Dissipative Particle Dynamics

      Hideo Doi

      ACS Chemical Neuroscience11 ( 3 ) 385 - 394   3 1 2020

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      Language:English   Publishing type:Research paper (scientific journal)   Publisher:American Chemical Society ({ACS})  

      DOI: 10.1021/acschemneuro.9b00602

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    • Folding simulation of small proteins by dissipative particle dynamics (DPD) with non-empirical interaction parameters based on fragment molecular orbital calculations

      Hideo Doi

      Applied Physics Express   1 1 2020

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      Publishing type:Research paper (scientific journal)  

      DOI: 10.7567/1882-0786/ab5e0a

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    • Machine learning-aided analysis for complex local structure of liquid crystal polymers

      Hideo Doi

      Scientific Reports9 ( 1 )   8 11 2019

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      Language:English   Publishing type:Research paper (scientific journal)   Publisher:Springer Science and Business Media LLC  

      Abstract

      Elucidation of mesoscopic structures of molecular systems is of considerable scientific and technological interest for the development and optimization of advanced materials. Molecular dynamics simulations are a promising means of revealing macroscopic physical properties of materials from a microscopic viewpoint, but analysis of the resulting complex mesoscopic structures from microscopic information is a non-trivial and challenging task. In this study, a Machine Learning-aided Local Structure Analyzer (ML-LSA) is developed to classify the complex local mesoscopic structures of molecules that have not only simple atomistic group units but also rigid anisotropic functional groups such as mesogens. The proposed ML-LSA is applied to classifying the local structures of liquid crystal polymer (LCP) systems, which are of considerable scientific and technological interest because of their potential for sensors and soft actuators. A machine learning (ML) model is constructed from small, and thus computationally less costly, monodomain LCP trajectories. The ML model can distinguish nematic- and smectic-like monodomain structures with high accuracy. The ML-LSA is applied to large, complex quenched LCP structures, and the complex local structures are successfully classified as either nematic- or smectic-like. Furthermore, the results of the ML-LSA suggest the best order parameter for distinguishing the two mesogenic structures. Our ML model enables automatic and systematic analysis of the mesogenic structures without prior knowledge, and thus can overcome the difficulty of manually determining the specific order parameter required for the classification of complex structures.

      DOI: 10.1038/s41598-019-51238-1

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      Other Link: http://www.nature.com/articles/s41598-019-51238-1

    • 物性測定とFMO-DPD法による脂質微粒子の構造解析 Peer-reviewed

      新庄 永治, 奥脇 弘次, 土居 英男, 望月 祐志, 古石 誉之, 福澤 薫, 米持 悦生

      日本DDS学会学術集会プログラム予稿集35回   135 - 135   6 2019

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      Language:Japanese   Publisher:日本DDS学会  

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    • 小角X線散乱測定とFMO-DPDシミュレーションによる脂質/Cholesterol混合二重膜における物性の解析 Peer-reviewed

      新庄 永治, 奥脇 弘次, 土居 英男, 望月 祐志, 古石 誉之, 福澤 薫, 米持 悦生

      日本薬学会年会要旨集139年会 ( 4 ) 80 - 80   3 2019

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      Language:Japanese   Publisher:(公社)日本薬学会  

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    • Theoretical Analyses on Water Cluster Structures in Polymer Electrolyte Membrane by Using Dissipative Particle Dynamics Simulations with Fragment Molecular Orbital Based Effective Parameters Peer-reviewed

      Okuwaki Koji, Mochizuki Yuji, Doi Hideo, Kawada Shutaro, Ozawa Taku, Yasuoka Kenji

      RSC Advances8 ( 60 ) 34582 - 34595   10 2018

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      Publisher:Royal Society of Chemistry  

      DOI: 10.1039/C8RA07428C

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    • A portable code for dissipative particle dynamics (DPD) simulations with additional specific interactions Peer-reviewed

      Hideo, Doi, Koji, Okuwaki, Takamitsu, Naito, Sona, Saitou, Yuji, Mochizuki

      Chem-Bio Informatics Journal18 ( 0 ) 70 - 85   6 2018

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      Publishing type:Research paper (scientific journal)  

      DOI: 10.1273/cbij.18.70

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    • Formation Mechanism of Lipid Membrane and Vesicle Using Small Angle X-ray Scattering and Dissipative Particle Dynamics (DPD) Method Peer-reviewed

      Eiji Shinsho, Koji Okuwaki, Hideo Doi, Yuji Mochizuki, Takayuki Furuishi, Kaori Fukuzawa, Etsuo Yonemochi

      JOURNAL OF COMPUTER CHEMISTRY-JAPAN17 ( 4 ) 172 - 179   2018

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      Language:Chinese   Publishing type:Research paper (scientific journal)   Publisher:SOC COMPUTER CHEMISTRY, JAPAN  

      In order to perform efficient nanoparticle design in drug delivery systems, prediction of physical properties and elucidation of the molecular mechanism are expected by using molecular simulation. In this study, we investigated the molecular mechanism of lipid bilayer formation and mixed lipid vesicle formation using the dissipative particle dynamics (DPD) method and small angle X-ray scattering measurement. Parameters of inter-molecular interaction used for the DPD simulation were estimated in quantum mechanical level by the fragment molecular orbital method (FMO-DPD method). In lipid bilayer formation, it was found that the phospholipid having an unsaturated bond (DOPC) has higher membrane fluidity than the phospholipid (DPPC) having only saturated bonds. In the vesicle formation mixed with phospholipid and positively charged lipid, it was also found that as the proportion of positively charged lipid increases, the fluidity of the membrane increases and the shape changes from a sphere to a flat sphere.

      DOI: 10.2477/jccj.2018-0012

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    • Development and Application of FMO Calculation − DPD Simulation Conbination Scheme Peer-reviewed

      Okuwaki Koji, Doi Hideo, Mochizuki Yuji, Ozawa Taku, Yasuoka Kenji, Fukuzawa Kaori

      Journal of Computer Chemistry, Japan17 ( 3 ) 144   2018

    • An automated framework to evaluate effective interaction parameters for dissipative particle dynamics simulations based on the fragment molecular orbital (FMO) method

      Okuwaki, Koji, Doi, Hideo, Mochizuki, Yuji

      JOURNAL OF COMPUTER CHEMISTRY-JAPAN17 ( 2 ) 102 - 109   2018

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      Publishing type:Research paper (scientific journal)   Publisher:SOC COMPUTER CHEMISTRY, JAPAN 2-1-13 HIGASHIUENO, TAITO-KU, TOWA HIGH TOWN UENO 607, TOKYO, 110-0015, JAPAN  

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    • Application of TensorFlow to recognition of visualized results of fragment molecular orbital (FMO) calculations

      Saitou, Sona, Iijima, Jun, Fujimoto, Mayu, Mochizuki, Yuji, Okuwaki, Koji, Doi, Hideo, Komeiji, Yuto

      Chem-Bio Informatics Journal18   58 - 69   2018

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      Publishing type:Research paper (scientific journal)   Publisher:Chem-Bio Informatics Society  

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    • 可視化されたフラグメント分子軌道 (FMO) 計算結果の TensorFlow の応用による解釈

      Hideo Doi

      CBI ジャーナル   2018

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      Publishing type:Research paper (scientific journal)  

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    • フラグメント分子軌道 (FMO) 法を用いた散逸粒子動力学シミュレーションのための有効相互作用パラメータ算出の自動化フレームワーク

      Hideo Doi

      Journal of Computer Chemistry, Japan   2018

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      Publishing type:Research paper (scientific journal)  

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    • A New Treatment for Water near the Interface between Lipid Membrane and Silica in Dissipative Particle Dynamics Simulation

      Doi, Hideo, Okuwaki, Koji, Mochizuki, Yuji, Ozawa, Taku

      JOURNAL OF COMPUTER CHEMISTRY-JAPAN16 ( 1 ) 28 - 31   2017

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      Publishing type:Research paper (scientific journal)   Publisher:SOC COMPUTER CHEMISTRY, JAPAN 2-1-13 HIGASHIUENO, TAITO-KU, TOWA HIGH TOWN UENO 607, TOKYO, 110-0015, JAPAN  

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    • Development and Performance Evaluation of a Simulation Code for Dissipative Particle Dynamics (DPD) CAMUS

      Doi, Hideo, Saitou, Sona, Okuwaki, Koji, Naito, Takamitsu, Mochizuki, Yuji

      JOURNAL OF COMPUTER CHEMISTRY-JAPAN16 ( 5 ) 126 - 128   2017

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      Publishing type:Research paper (scientific journal)   Publisher:SOC COMPUTER CHEMISTRY, JAPAN 2-1-13 HIGASHIUENO, TAITO-KU, TOWA HIGH TOWN UENO 607, TOKYO, 110-0015, JAPAN  

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    • Fragment Molecular Orbital Based Parametrization Procedure for Mesoscopic Structure Prediction of Polymeric Materials

      Okuwaki, Koji, Mochizuki, Yuji, Doi, Hideo, Ozawa, Taku

      The Journal of Physical Chemistry B122 ( 1 ) 338 - 347   2017

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      Publishing type:Research paper (scientific journal)   Publisher:American Chemical Society  

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    • 散逸粒子動力学におけるシリカ-脂質膜界面付近の水の取扱い

      Hideo Doi

      Journal of Computer Chemistry, Japan   2017

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      Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:Society of Computer Chemistry, Japan  

      <p>Dissipative particle dynamics (DPD) simulation is used for research in a wide range of science fields such as biological membranes. Conventionally, in such DPD simulations, both bulk water and interfacial water were treated by the same properties. However, such an approach could not well reproduce several properties of the target system, because some experimental and theoretical researches show the properties of water molecules near interfaces are considerably different from those of bulk water molecules. Therefore, in order to solve such a problem, we propose a new approach for interfacial water. We apply this approach to the DPD simulation of lipid membrane - silica - water system. As result, we could model the adsorption of lipid membrane on silica surface.</p>

      DOI: 10.2477/jccj.2017-0003

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    • Replica exchange molecular simulation of Lennard--Jones particles in a two-dimensional confined system

      Doi, Hideo, Yasuoka, Kenji

      AIP Advances7 ( 5 ) 055018 - 055018   2017

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      Publishing type:Research paper (scientific journal)   Publisher:AIP Publishing  

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    • Dissipative particle dynamics (DPD) simulations with fragment molecular orbital (FMO) based effective parameters for 1-Palmitoyl-2-oleoyl phosphatidyl choline (POPC) membrane

      Doi, Hideo, Okuwaki, Koji, Mochizuki, Yuji, Ozawa, Taku, Yasuoka, Kenji

      Chemical Physics Letters684   427 - 432   2017

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      Publishing type:Research paper (scientific journal)   Publisher:North-Holland  

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    • Approaches for Controlling the Temperature and Pressure Range in Generalized NPT Ensembles

      Doi, Hideo, Yasuoka, Kenji

      Journal of Chemical Theory and Computation11 ( 9 ) 4370 - 4376   2015

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      Publishing type:Research paper (scientific journal)   Publisher:ACS Publications  

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    • Influence of trimethylamine n-oxide (TMAO) on the three-dimensional distribution and alignment of solvent molecules in aqueous solution

      Doi, Hideo, Watanabe, Yudai, Aida, Misako

      Chemistry Letters43 ( 6 ) 865 - 867   2014

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      Language:English   Publishing type:Research paper (scientific journal)   Publisher:The Chemical Society of Japan  

      By means of Monte Carlo simulations together with an ab initio molecular orbital method, we present the influence of trimethylamine <i>N</i>-oxide (TMAO), which is a highly polarized spherical-polyhedron, on the distribution and the alignment of surrounding water molecules. The specific alignment of the average dipole moments of solvent water around TMAO is observed in the MC simulation. The number of water molecules in the first hydration shell from MC simulation was in good agreement with the experimental value. A cluster model of TMAO with 12 water molecules was presented as a representative hydration structure of TMAO.

      DOI: 10.1246/cl.140043

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    • A new variant of multicanonical Monte Carlo algorithm with specifying the temperature range and its application to the hydration free energy change of fluorinated methane derivatives

      Doi, Hideo, Aida, Misako

      Chemical Physics Letters595   55 - 60   2014

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      Publishing type:Research paper (scientific journal)   Publisher:North-Holland  

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    • Hydration of Adamantane Skeleton: Water Assembling around Amantadine and Halo-substituted Adamantanes

      Doi, Hideo, Aida, Misako

      Chemistry Letters42 ( 3 ) 292 - 294   2013

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      Publishing type:Research paper (scientific journal)   Publisher:The Chemical Society of Japan  

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    Misc.

    • FMOプログラムABINIT-MPの整備状況2022 Invited Peer-reviewed

      MOCHIZUKI Yuji, NAKANO Tatsuya, SAKAKURA Kota, WATANABE Hiromasa, SATO Shinya, OKUWAKI Koji, AKISAWA Kazuki, DOI Hideo, OHSHIMA Satoshi, KATAGIRI Takahiro

      J. Comp. Chem. Jpn.21 ( 4 ) 106 - 110   29 4 2023

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      Language:Japanese   Publishing type:Rapid communication, short report, research note, etc. (scientific journal)   Publisher:Society of Computer Chemistry, Japan  

      We have been developing the ABINIT-MP program for fragment molecular orbital (FMO) calculations over 20 years. Several improvements for accelerated processing were made after the release of Open Version 2 Revision 4 at September 2021. Functionalities were enhanced as well. In this short report, we summarize such developments toward the next release of Revision 8

      DOI: 10.2477/jccj.2022-0037

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    • Simulation of Lipid Membrane, Cholesterol, and Proteins using FMO-DPD Method

      奥脇弘次, 新庄永治, 西田瑠花, 加藤幸一郎, 土屋裕大朗, 土居英男, 望月祐志, 望月祐志, 福澤薫, 福澤薫, 米持悦生

      応用物理学会春季学術講演会講演予稿集(CD-ROM)67th   2020

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    • FMO計算に基づく脂質二重膜,タンパク質の非経験的粗視化シミュレーションの展開

      奥脇弘次, 新庄英治, 土居英男, 望月祐志, 望月祐志, 福澤薫, 福澤薫, 米持悦生

      応用物理学会春季学術講演会講演予稿集(CD-ROM)66th   2019

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    • FMO-DPDの連携による脂質二重膜とコレステロール,ペプチドモデルのシミュレーション

      奥脇弘次, 新庄永治, 西田瑠花, 土屋祐大郎, 土居英男, 望月祐志, 望月祐志, 福澤薫, 福澤薫, 米持悦生

      応用物理学会秋季学術講演会講演予稿集(CD-ROM)80th   2019

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    • Coarse-grained simulation analysis based on non-empirical parameters for polymer electrolyte membrane material design

      加藤幸一郎, 奥脇弘次, 土居英男, 米田雅一, 望月祐志, 望月祐志

      電池討論会PDF要旨集(CD-ROM)60th   2019

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    • 散逸粒子動力学法シミュレーションを用いた脂質膜構成メカニズムの予測

      新庄永治, 奥脇弘次, 土居英男, 望月祐志, 望月祐志, 古石誉之, 福澤薫, 米持悦生

      日本DDS学会学術集会プログラム予稿集34回   157 - 157   5 2018

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      Language:Japanese  

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    • DPDシミュレーションによる脂質膜構成メカニズムの解明

      新庄永治, 奥脇弘次, 土居英男, 望月祐志, 望月祐志, 郡司美穂子, 古石誉之, 福澤薫, 米持悦生

      日本薬学会年会要旨集(CD-ROM)138年会 ( 4 ) 79 - 79   3 2018

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      Language:Japanese  

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    • 脂質ベシクル,タンパク質の非経験的粗視化シミュレーション

      奥脇弘次, 新庄英治, 土居英男, 望月祐志, 望月祐志, 福澤薫, 福澤薫, 米持悦生

      応用物理学会秋季学術講演会講演予稿集(CD-ROM)79th   2018

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    • FMO-DPD連携シミュレーション手法の開発とベシクル形成への応用

      奥脇弘次, 土居英男, 望月祐志, 望月祐志, 新庄永治, 福澤薫, 福澤薫, 米持悦生, 小沢拓, 泰岡顕治

      応用物理学会秋季学術講演会講演予稿集(CD-ROM)78th   2017

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    • Digraphs in Chemistry: All Possible Structures and Temperature-Dependent Distribution of Water Clusters

      Aida, Misako, Akase, Dai, Doi, Hideo, Yoshida, Tomoki

      Practical Aspects of Computational Chemistry II   49 - 68   2012

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      Publisher:Springer  

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    Presentations

    • Non-Empirical calculation of parameters for DPD simulation with the aid of machine learning

      Hideo Doi, Sota Matsuoka, Koji Okuwaki, Ryo Hatada, Sojiro Minami, Ryosuke Suhara, Yuji Mochizuki

      21 9 2023 

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      Event date: 19 9 2023 - 23 9 2023

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    • Improving Efficiency of Non-Empirical Calculation of Parameters for DPD Simulation by Machine Learning

      Hideo Doi, Sota Matsuoka, Koji Okuwaki, Ryo Hatada, Sojiro Minami, Ryosuke Suhara, Yuji Mochizuki

      2 6 2023 

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      Event date: 31 5 2023 - 1 6 2023

      Presentation type:Oral presentation (general)  

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    • Parameter development for DPD simulation of microdomain in lipid bilayers with effective parameter based on fragment molecular orbital calculation

      Hideo Doi, Yushi Osada, Yusuke Tachino, Koji Okuwaki, Melvin Goh, Ryugo Tero, Yuji Mochizuki

      17 3 2023 

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      Event date: 15 3 2023 - 18 3 2023

      Presentation type:Oral presentation (general)  

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    • DPD simulation of microdomain in lipid bilayers with effective parameter based on fragment molecular orbital calculation

      Yushi Osada, Yusuke Tachino, Koji Okuwaki, Hideo Doi, Melvin Wei Shern Goh, Ryugo Tero, Yuji Mochizuki

      The 83rd JSAP Autumn Meeting 2022  22 9 2022 

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      Event date: 20 9 2022 - 23 9 2022

      Language:Japanese   Presentation type:Oral presentation (general)  

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