New COVID-19 protease inhibitors

designed by AI with recurrent neural networks, molecular docking, and QSAR

Information about generated molecule # 36253

O=C(N[C@H](C[S@](=O)c1ccc2ccccc2c1)C(=O)N[C@@H]1c2ccccc2C[C@H]1O)O[C@@H]1CCOC1



Predicted properties

Property Value Comments
Docking score -9.1 VINA score, less is better
pIC50 (SARS, M) 5.44 bigger is better
pIC50 (HIV, M) 9.86 bigger is better
logS (M) -3.97 Solubility based on the Transformer Model, bigger is better.
Cycle >4 The cycle when the molecule was generate, the bigger cycle the more RNN is inventive.
Cardiotoxicity, hERG 0.0018 Probability of being hERG binder (0-1), less is better.
Mutagenicity, AMES 0.2249 Probability of being mutagenic (0-1), less is better.
Caco-2 permeability -5.8397 log(sm/s)
HIA, intestinal absorbtion 99.98 %
LD50, oral (rats) 2.7 -log(M)
SARS-CoV inhibition 36.0 %
Molecular weight 508.6 g/mole
This molecule was not found in references databases.

Generator summary

Random prospective compound




Cc1ccc(C)c(SC2C(=O)OC(CF)(CCc3ccc(O)cc3)CCC2C(C)(C)C)c1

COVID-19 protease

The structure has been recently solved, PDB code 6lu7. 6ul7 structure
Developed in group of Cheminformatics in the Institute of Structural Biology at Helmholtz-Zentrum Muenchen, Tetko group
With support of BIGCHEM GmBH (bigchem.de) and RULIS Ltd. (rulis.ru).