Introducing the Automated Ligand Searcher.
Luise JacobsenJonathan HungerlandVladimir BačićLuca GerhardsFabian SchuhmannIlia A Solov'yovPublished in: Journal of chemical information and modeling (2023)
The Automated Ligand Searcher (ALISE) is designed as an automated computational drug discovery tool. To approximate the binding free energy of ligands to a receptor, ALISE includes a three-stage workflow, with each stage involving an increasingly sophisticated computational method: molecular docking, molecular dynamics, and free energy perturbation, respectively. To narrow the number of potential ligands, poorly performing ligands are gradually segregated out. The performance and usability of ALISE are benchmarked for a case study containing known active ligands and decoys for the HIV protease. The example illustrates that ALISE filters the decoys successfully and demonstrates that the automation, comprehensiveness, and user-friendliness of the software make it a valuable tool for improved and faster drug development workflows.
Keyphrases
- molecular dynamics
- molecular docking
- drug discovery
- machine learning
- deep learning
- density functional theory
- high throughput
- hiv positive
- hiv infected
- antiretroviral therapy
- human immunodeficiency virus
- electronic health record
- hepatitis c virus
- healthcare
- hiv aids
- men who have sex with men
- human health
- risk assessment
- dna binding
- south africa