Table 1.
Examples of AI tools used in drug discovery
| Tools | Details | Website URL | Refs |
|---|---|---|---|
| DeepChem | MLP model that uses a python-based AI system to find a suitable candidate in drug discovery | https://github.com/deepchem/deepchem | [21] |
| DeepTox | Software that predicts the toxicity of total of 12 000 drugs | www.bioinf.jku.at/research/DeepTox | [22] |
| DeepNeuralNetQSAR | Python-based system driven by computational tools that aid detection of the molecular activity of compounds | https://github.com/Merck/DeepNeuralNet-QSAR | [23] |
| ORGANIC | A molecular generation tool that helps to create molecules with desired properties | https://github.com/aspuru-guzik-group/ORGANIC | [24] |
| PotentialNet | Uses NNs to predict binding affinity of ligands | https://pubs.acs.org/doi/full/10.1021/acscentsci.8b00507 | [25] |
| Hit Dexter | ML technique to predict molecules that might respond to biochemical assays | http://hitdexter2.zbh.uni-hamburg.de | |
| DeltaVina | A scoring function for rescoring drug–ligand binding affinity | https://github.com/chengwang88/deltavina | |
| Neural graph fingerprint | Helps to predict properties of novel molecules | https://github.com/HIPS/neural-fingerprint | |
| AlphaFold | Predicts 3D structures of proteins | https://deepmind.com/blog/alphafold | |
| Chemputer | Helps to report procedure for chemical synthesis in standardized format | https://zenodo.org/record/1481731 |