A key challenge in structure-based drug design is generating three-dimensional molecules while preserving essential protein-ligand interactions. We propose DiffPharma, a structure-based pharmacophore ...

The identification of therapeutically interesting compounds from the estimated 10 60 potential drug-like chemicals remains a critical challenge in drug discovery 1. High-throughput screening is widely ...

A study from Cornell researchers could enable a quantum leap forward in identifying and deciphering cancer-driving genetic mutations, the first step in developing effective therapeutics. Cells become ...

A University of Missouri researcher has created a computer program that can unravel the mysteries of how proteins work together—giving scientists valuable insights to better prevent, diagnose and ...

Scientists have designed a publicly-available software and web database to break down barriers to identifying key protein-protein interactions to treat with medication. The computational tool is ...

An enzyme type noted in several cancers is the family of adenosine deaminases acting on RNA (ADARs). These enzymes convert adenosines in double-stranded RNA (dsRNA) into inosines, which cells read as ...

Scientists have used deep learning to design new proteins that bind to complexes involving other small molecules like hormones or drugs, opening up a world of possibilities in the computational design ...

Researchers capture first-of-its-kind video of dynein–Lis1 protein interaction, supporting future drug development for neurological disorders. Our cells rely on microscopic highways and specialized ...

Protein-Protein Interactions (PPIs) are critical for biological systems to function properly. Strong interactions maintain structural integrity and function, whereas weaker interactions enable ...

In a recent study published in the journal Nature Methods, a group of researchers developed a novel method called Ribonucleic Acid (RNA) High-Order Folding Prediction Plus (RhoFold+). This deep ...