In this repository, you will find the notebooks and analyses done on SureChEMBL data.
Metadata relevant to the repository:
- Dataset -
- Pre-print -
- Publication -
Patent documents have played significant roles in drug discovery ranging from competitive and academic intelligence to research and innovation index. Acknowledging the importance of these legal documents, a number of manual and automated workflows have been developed to annotate biomedical-related entities such as protein and gene sequences accurately. Of these, the annotation of chemical compounds from patents has played a pivotal role for medicinal chemists to understand the underlying patenting landscape for potential drug lead candidates. Consequently, the establishment of a public patent database, SureChEMBL, has allowed academic researchers to leverage the patent annotation tools that would otherwise be inaccessible due to commercial software. This manuscript looks at the medicinal perspective of data present in SureChEMBL. We started by looking at the FAIRness level of the compounds both within SureChEMBL as well as externally in publicly available chemical databases such as PubChem. Furthermore, we elucidate the drug-like properties of the annotated compounds to understand the chemical space annotated by SureChEMBL. Lastly, we capture the transitioning of the compounds from pre-clinical to clinic based on data existing in established data repositories such as DrugBank.
Through this research article, we have outlined and highlighted three major outcomes:
i) the need for a stronger correlation between SureChEMBL and prominent compounds public databases such as PubChem and ChEMBL,
ii) the awareness that reusing data from SureChEMBL requires a pre-filtering to accurately select lead-like compounds with potential bioactivity when modeling their corresponding activity landscape and
iii) by incorporating these compounds into the existing chemical space, we would expand our access to a broader and more diverse range of chemical entities.
The open-access article is now available at Nature Scientific Data:
Gadiya, Y., Shetty, S., Hofmann-Apitius, M. et al. Exploring SureChEMBL from a drug discovery perspective. Sci Data 11, 507 (2024). https://doi.org/10.1038/s41597-024-03371-4