Accurate Prediction of Hydration Sites of Proteins Using Energy Model With Atom Embedding
We propose a method based on neural networks to accurately predict hydration sites in proteins. In our approach, high-quality data of protein structures are used to parametrize our neural network model, which is a differentiable score function that can evaluate an arbitrary position in 3D structures...
Main Authors: | Pin Huang, Haoming Xing, Xun Zou, Qi Han, Ke Liu, Xiangyan Sun, Junqiu Wu, Jie Fan |
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Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2021-09-01
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Series: | Frontiers in Molecular Biosciences |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fmolb.2021.756075/full |
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