Screening and Optimization of Drug-like Compounds

The IBScreen database containing 211432 compounds was selected. The drug-likeness behavior of the database compounds was predicted by using QikProp version 4.3 (Schrödinger). The compounds were employed for the calculation of pharmacokinetic parameters by QikProp v4.3. Physiochemical descriptors and pharmaceutically relevant properties of compounds were evaluated to analyze druggable properties [27 (link), 38 (link)]. Lipinski's rule of five was used to filter the compounds with drug-like properties [39 (link)]. To identify the best match molecules, the AAARRR.1061 hypothesis was applied for screening the IBScreen database with drug-like properties. Finally, we selected the compounds with the pIC₅₀ value of more than 4 which were considered as the most active compounds, and then, further screening of these compounds is done by ADMET (absorption, distribution, metabolism, elimination, and toxicity) properties using QikProp version 4.3. The compounds complied with Lipinski's rule, with good predicted activity and good ADMET properties, were selected for molecular docking studies [24 (link), 32 ].