In particular, they are restricted by the limited size and chemical diversity of existing sets of training data 8. However, existing computational models for a molecule’s BBB permeability are inadequate. Therefore, predicting BBB permeability for small molecules is a vital but challenging task in drug discovery and development 4, 5, 6, 7. However, it is estimated that 98% of small molecule drugs are not BBB permeable 4. The blood-brain barrier (BBB) denotes a regulatory and protective mechanism of microvasculature in the central nervous system (CNS) that is central to regulating the homeostatis of the CNS 1, 2 and protecting the CNS from toxins, pathogens, and inflammations 3. By analyzing these properties, we can demonstrate some physiochemical similarities and differences between BBB+ and BBB− compounds. We also provide some physicochemical properties of the molecules. The dataset is freely available at and (version 3). A subset of the molecules in B3DB has numerical log BB values (1058 compounds), while the whole dataset has categorical (BBB+ or BBB−) BBB permeability labels (7807). To mitigate this issue, we present a large benchmark dataset, B3DB, complied from 50 published resources and categorized based on experimental uncertainty. Machine learning (ML) is a promising strategy for predicting the BBB permeability, but existing studies have been limited by small datasets with limited chemical diversity. As such, the BBB has a close relationship with CNS disease development and treatment, so predicting whether a substance crosses the BBB is a key task in lead discovery for CNS drugs. The highly-selective blood-brain barrier (BBB) prevents neurotoxic substances in blood from crossing into the extracellular fluid of the central nervous system (CNS).
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |