gr Predictor: A Deep Learning Model for Predicting the Hydration Structures around Proteins-Reference-Cited by-同舟云学术

gr Predictor: A Deep Learning Model for Predicting the Hydration Structures around Proteins

Published:2022-09-07 Issue:18 Volume:62 Page:4460-4473
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Kawama Kosuke¹,Fukushima Yusaku¹,Ikeguchi Mitsunori²³^ORCID,Ohta Masateru²^ORCID,Yoshidome Takashi¹^ORCID

Affiliation:

1. Department of Applied Physics, Graduate School of Engineering, Tohoku University, Sendai 980-8579, Japan

2. AI-Driven Drug Discovery Collaborative Unit, HPC- and AI-Driven Drug Development Platform Division, Center for Computational Science, RIKEN, 1-7-29, Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan

3. Graduate School of Medical Life Science, Yokohama City University, 1-7-29, Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan

Funder

Japan Society for the Promotion of Science

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.2c00987

Reference30 articles.

1. Just add water! The effect of water on the specificity of protein-ligand binding sites and its potential application to drug design

2. A new theoretical approach to biological self-assembly

3. Elucidating the multiple roles of hydration for accurate protein-ligand binding prediction via deep learning

4. Water Molecules in a Protein Cavity Detected by a Statistical−Mechanical Theory

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1. Water position sampling on protein structures based on a 3D distribution function using a weighted Monte Carlo method;Bulletin of the Chemical Society of Japan;2024-06

2. An innovative method for calculating partial molar volume from a standard molecular trajectory;Journal of Molecular Liquids;2024-02

3. HydraMap v.2: Prediction of Hydration Sites and Desolvation Energy with Refined Statistical Potentials;Journal of Chemical Information and Modeling;2023-07-11

4. Applications of Deep Learning for Drug Discovery Systems with BigData;BioMedInformatics;2022-11-12