Mitochondrial-toxicity-related molecules lead to damaging effects on mitochondria and cause severe side effects. To keep track of such molecules a new database is created.
This database is known as the MitoTox database . It is a comprehensive electronic repository that contains detailed information about mitochondria-related toxins and their targets. All data and information for this database are collected from various sources including electronic databases including DrugBank, PubChem, UniProt, and SIDER, and scientific journals. This data is manually verified and then added to the database.
Currently, MitoTax consists of 1400 small compounds that are linked to over 870 mitochondrial-related proteins. The database maintains 300 references so far that support all the entries. Additionally, MitoTox stores experimental results of in vitro and in vivo assays for the detection of drug-induced mitochondrial toxicity.
MitoTox is implemented in Python3 and Django. The database is open access and is available at http://www.mitotox.org/.
For more details, read here.
- Lin, YT., Lin, KH., Huang, CJ. et al. MitoTox: a comprehensive mitochondrial toxicity database. BMC Bioinformatics 22, 369 (2021).
cheML.io: ML-generated molecules database
Due to the advancement of machine learning (ML) methods, we can find increasing applications of them in the field of bioinformatics as well. ML is being utilized in making personalized medicines, similarity searches in DNA and protein sequences, phylogenetics by mapping selected species on phylogenetic trees, gene and protein function annotation, generating chemical compounds, and so on. In this article, we will discuss an online database of ML-generated molecules known as cheML.io .
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