Accurate Prediction of Hydration Sites of Proteins Using Energy Model With Atom Embedding.
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ABSTRACT:
SUBMITTER: Huang P
PROVIDER: S-EPMC8488165 | biostudies-literature | 2021
REPOSITORIES: biostudies-literature
Publications
Accurate Prediction of Hydration Sites of Proteins Using Energy Model With Atom Embedding.
Huang Pin P Xing Haoming H Zou Xun X Han Qi Q Liu Ke K Sun Xiangyan X Wu Junqiu J Fan Jie J
Frontiers in molecular biosciences 20210920
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 on proteins and predict the nearest water molecule that is not present. The score function is further integrated into our water placement algorithm to generate explicit hydration sites. In experiment ...[more]
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