Prediction of biological activity of compounds containing a 1,3,5-triazinyl sulfonamide scaffold by artificial neural networks using simple molecular descriptors

Bioorg Chem. 2021 Feb:107:104565. doi: 10.1016/j.bioorg.2020.104565. Epub 2020 Dec 19.

Abstract

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).

Keywords: 1,3,5-triazinyl sulfonamide derivatives; ANN; Carbonic anhydrase; Structural descriptors.

MeSH terms

  • Antigens, Neoplasm / metabolism
  • Carbonic Anhydrase II / antagonists & inhibitors
  • Carbonic Anhydrase II / metabolism
  • Carbonic Anhydrase IX / antagonists & inhibitors
  • Carbonic Anhydrase IX / metabolism
  • Carbonic Anhydrase Inhibitors / chemistry
  • Carbonic Anhydrase Inhibitors / metabolism
  • Drug Design
  • Humans
  • Neural Networks, Computer*
  • Sulfonamides / chemistry*
  • Sulfonamides / metabolism
  • Triazines / chemistry*

Substances

  • Antigens, Neoplasm
  • Carbonic Anhydrase Inhibitors
  • Sulfonamides
  • Triazines
  • Carbonic Anhydrase II
  • CA9 protein, human
  • Carbonic Anhydrase IX