Publication details
Prediction of biological activity of compounds containing a 1,3,5-triazinyl sulfonamide scaffold by artificial neural networks using simple molecular descriptors
| Authors | |
|---|---|
| Year of publication | 2021 |
| Type | Article in Periodical |
| Magazine / Source | Bioorganic Chemistry |
| MU Faculty or unit | |
| Citation | |
| Web | https://doi.org/10.1016/j.bioorg.2020.104565 |
| Doi | http://dx.doi.org/10.1016/j.bioorg.2020.104565 |
| Keywords | ANN; Structural descriptors1.3.5-triazinyl sulfonamide derivatives; Carbonic anhydrase |
| Description | Simple molecular descriptors of extensive series of 1,3,5-triazinyl sulfonamide derivatives, based on the structure of sulfonamides and their physicochemical properties, were designed and calculated. These descriptors were successfully applied as inputs for artificial neural network (ANN) modelling of the relationship between the structure and biological activity. The optimized ANN architecture was applied to the prediction of the inhibition activity of 1,3,5-triazinyl sulfonamides against human carbonic anhydrase (hCA) II, tumour-associated hCA IX, and their selectivity (hCA II/hCA IX). |