CovalentInDB 2.0: An Updated Database for Covalent Inhibitor Design
Author Information
Author(s): Du Hongyan, Zhang Xujun, Wu Zhenxing, Zhang Odin, Gu Shukai, Wang Mingyang, Zhu Feng, Li Dan, Hou Tingjun, Pan Peichen
Primary Institution: College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
Hypothesis
CovalentInDB 2.0 aims to enhance covalent drug discovery by providing a comprehensive database of covalent inhibitors and their interactions.
Conclusion
CovalentInDB 2.0 significantly expands the dataset and features available for covalent drug discovery, making it a vital resource for researchers.
Supporting Evidence
- CovalentInDB 2.0 includes 8303 inhibitors and 368 targets.
- The database features 3445 newly added cocrystal structures.
- An AI-based model profiles the ligandability of 144,864 cysteines across the human proteome.
- The largest covalent virtual screening library contains 2,030,192 commercially available compounds.
Takeaway
CovalentInDB 2.0 is like a big library that helps scientists find and design new medicines that stick to their targets really well.
Methodology
The database was updated by collecting data from scientific literature and established databases, analyzing cocrystal structures, and employing an AI model to profile cysteines in the human proteome.
Limitations
The study may be limited by the reliance on existing databases and the potential for incomplete data in the literature.
Digital Object Identifier (DOI)
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