By putting a carbon atom in place of a core oxygen, chemists constructed an opioid that blocks pain with less respiratory ...

A major scientific advance in protein modeling developed by Microsoft Research AI for Science, has been published in Science.

The de novo design of drug molecules is recognized as a time-consuming and costly process, and computational approaches have been applied in each stage of the drug discovery pipeline. Variational ...

1 Department of Pharmaceutical Sciences, College of Pharmacy, Howard University, Washington, D.C., United States 2 Artificial Intelligence and Drug Discovery (AIDD) Core Laboratory for District of ...

This is particularly important to drug discovery. "When ligands bind to proteins, they kick out water from binding sites, so we need to pay attention to them in ligand design," said Fischer.

To overcome the pitfalls of sample size and dimensionality, this study employed variational autoencoder (VAE), which is a dynamic framework for unsupervised learning in recent years.

Drug discovery has traditionally been slow, expensive and prone to failure, but AI and machine learning are set to change all that.

The Articles captured in this Special Issue are exactly the breadth of science these editors had hoped for, with Articles that span the drug discovery continuum from technology development (in the ...

We describe a semiautomated and microplate-based parallel compound library approach leading to the rapid discovery of celastrol derivatives that are potent and selective PRDX1 inhibitors.

Among many other applications, it plays a crucial role in screening pipelines for drug and material discovery, where candidate molecules or materials are proposed, verified through simulators like DFT ...