CovalentInDB 2.0: an updated comprehensive database for structure-based and ligand-based covalent inhibitor design and screening

The rational design of targeted covalent inhibitors (TCIs) has emerged as a powerful strategy in drug discovery, known for its ability to achieve strong binding affinity and prolonged target engagement. However, the development of covalent drugs is often challenged by the need to optimize both covalent warhead and non-covalent interactions, alongside the limitations of existing compound libraries. To address these challenges, we present CovalentInDB 2.0, an updated online database designed to support covalent drug discovery. This updated version includes 8303 inhibitors and 368 targets, supplemented by 3445 newly added cocrystal structures, providing detailed analyses of non-covalent interactions. Furthermore, we have employed an AI-based model to profile the ligandability of 144 864 cysteines across the human proteome. CovalentInDB 2.0 also features the largest covalent virtual screening library with 2 030 192 commercially available compounds and a natural product library with 105 901 molecules, crucial for covalent drug screening and discovery. To enhance the utility of these compounds, we performed structural similarity analysis and drug-likeness predictions. Additionally, a new user data upload feature enables efficient data contribution and continuous updates. CovalentInDB 2.0 is freely accessible at http://cadd.zju.edu.cn/cidb/.

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Publication Details

Journal
Nucleic Acids Research
Published
2024-10-23
DOI
https://doi.org/10.1093/nar/gkae946
Citations
24
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
8.67

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article

CovalentInDB 2.0: an updated comprehensive database for structure-based and ligand-based covalent inhibitor design and screening

Mingyang Wang, Tingjun Hou, Hongyan Du, Shukai Gu et al.
24 citations
Nucleic Acids Research
Computational Drug Discovery Methods
8.67
article

CovalentInDB 2.0: an updated comprehensive database for structure-based and ligand-based covalent inhibitor design and screening

Mingyang Wang, Tingjun Hou, Hongyan Du, Shukai Gu, Peichen Pan, Zhenhua Wu, Feng Zhu, Dan Li, Xujun Zhang, Odin Zhang
article en
24 citations

Abstract

The rational design of targeted covalent inhibitors (TCIs) has emerged as a powerful strategy in drug discovery, known for its ability to achieve strong binding affinity and prolonged target engagement. However, the development of covalent drugs is often challenged by the need to optimize both covalent warhead and non-covalent interactions, alongside the limitations of existing compound libraries. To address these challenges, we present CovalentInDB 2.0, an updated online database designed to support covalent drug discovery. This updated version includes 8303 inhibitors and 368 targets, supplemented by 3445 newly added cocrystal structures, providing detailed analyses of non-covalent interactions. Furthermore, we have employed an AI-based model to profile the ligandability of 144 864 cysteines across the human proteome. CovalentInDB 2.0 also features the largest covalent virtual screening library with 2 030 192 commercially available compounds and a natural product library with 105 901 molecules, crucial for covalent drug screening and discovery. To enhance the utility of these compounds, we performed structural similarity analysis and drug-likeness predictions. Additionally, a new user data upload feature enables efficient data contribution and continuous updates. CovalentInDB 2.0 is freely accessible at http://cadd.zju.edu.cn/cidb/.

Nucleic Acids ResearchVol. 53(D1)
Zhejiang University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China, Natural Science Foundation of Zhejiang Province
Openalex Percentile: Top 2%
Computational Drug Discovery Methods
8.67
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