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Ivermectin as a potential drug for treatment of COVID-19.

Numerous datasets from historic clinical trials are being reviewed in the hope that existing drugs, that have already been cleared […]

Reducing False Positive Drug Target Predictions

Target prediction with machine learning algorithms can help accelerate the identification of protein targets of hit molecules, limiting the number […]

Discovery of Candidate Antibody-Drug Conjugate Targets

A recent study used the Human Protein Atlas as a unique big data resource to identify and prioritise candidate antibody-drug […]

Identifying Drug Repurposing Candidates for COVID-19 Using Drug-Wide Association Studies

A recent study carried out a systematic evaluation of the drugs available in electronic health record data, including prescription drugs […]

Ensemble Learning-Based Method for Inferring Drug-Target Interactions

A recent study presented a novel computational method for inferring drug-target interactions, which exploits the primary protein sequence and molecular […]

An Overview of AI/ML for CNS Drug Discovery

Due to the complex nature of central nervous system diseases and the presence of the blood-brain barrier (among other factors), […]

DrugCentral2021 – A Database for Drug Discovery and Repositioning

A recent study has described the new DrugCentral2021 database, which is a public resource that serves the scientific community by […]

Marine Natural Products Database for Drug Discovery

Marine organisms are expected to be an important source of inspiration for drug discovery. At present, very few databases exist […]

Characterising Multi-Target Compounds Using ML

A recent study, published in Scientific Reports, designed a test system using machine learning to systematically examine the structural features […]

Drug3D-Net: Predicting new Drug Properties

Computationally predicting molecular shapes and structures plays an important role in drug discovery, as it enables the identification of drug […]