CavitySpace: A Database of Potential Ligand Binding Sites in the Human Proteome

By Shiwei Wang, Haoyu Lin, Zhixian Huang, Yufeng He, Xiaobing Deng, Youjun Xu, Jianfeng Pei, Luhua Lai. 2022

29 citations recorded by the source corpus.

The ligand binding sites of a protein provide useful information to uncover its functions and to direct the structure-based drug design. However, as binding site detection relies on the three-dimensional (3D) structural data of proteins, functional analysis based on protein ligand binding sites is formidable for proteins without structural information. Recent developments in protein structure prediction and the 3D structures built by AlphaFold provide an unprecedented opportunity for analyzing ligand binding sites in human proteins. We have used the reliable ligand binding site detection program CAVITY to analyse all the proteins in the human proteome and constructed the CavitySpace database, which is the first pocket library for predicted protein structures. CavitySpace can be used to predict protein function based on pocket information, to identify new druggable protein targets for drug design, and to search for new binding sites for known drugs for drug repurposing. CavitySpace is freely available at http://www.pkumdl.cn:8000/cavityspace/.

Subfields: Computational Theory and Mathematics, Molecular Biology

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In Computational Theory and Mathematics

1. Yi Zhao
2. Zhenyu Yang
3. Runsheng Chen
4. Xiaoxi Zeng

In Molecular Biology

1. Yi Zhao
2. Zhenyu Yang
3. Runsheng Chen
4. Xiaoxi Zeng

Citations in the corpus

• AlphaFold2 and its applications in the fields of biology and medicine (2023, methodology): “Wang et al. 125 utilized the AF2 structures to construct the fi rst pocket library for all the proteins in the human proteome, called the CavitySpace database.”