Abstract
Computer-aided drug design (CADD) techniques continue to struggle to provide a useful advance in the area of drug development due to the difficulties in an efficient exploration of the vast drug-like chemical space to uncover new chemical compounds with desired biological properties. Other challenges that users must overcome in order to fully use the potential of CADD tools and techniques include a lack of completely autonomous methods, the necessity for retraining even after deployment, and their lack of interpretability. To solve this issue, we created the ‘Custom ML Tools’ integrated within the framework of ‘AIDrugAPP’. ‘Custom ML Tools’ includes four modules: ‘Mol Identifier’, ‘DesCal’, ‘AutoDL’, and ‘Auto-Multi-ML’ which give users free access to molecular identification using SMILES and compound names, similarity search, descriptor calculation, the building of ML/DL QSAR models, and their usage in predicting new data. The study demonstrates the potential of the novel tool for computational investigations in drug discovery research. The WebApp with its modules has therefore been made available for public use at: https://sars-covid-app.herokuapp.com/