In drug discovery, virtual screening is a fast and cost-effective way of narrowing down vast chemical libraries to identify the most promising hits, reducing synthesis and testing requirements while ...

Computational methods and recently modern machine learning methods have played a key role in structure-based drug design. Though several benchmarking datasets are available for machine learning ...

Designing protein-binding proteins is critical for drug discovery. However, artificial-intelligence-based design of such proteins is challenging due to the complexity of protein–ligand interactions, ...

Various approaches to such protein redesign have drawbacks. Traditional methods include time-consuming trial and error efforts, and many models in the emerging field ...

Understanding protein–ligand interactions is fundamental to molecular biology and biochemistry. These interactions are at the heart of many cellular processes, from enzyme catalysis to signal ...

Recently, SandboxAQ launched what it claims is the largest publicly available dataset of protein-ligand pairs with annotated experimental binding potency data. According to the company, the ...

Explore predictive modeling for compound prioritization, including in silico screening, toxicology models, and lead selection ...

The ability to alter proteins to refine control over binding affinity and specificity can create tailored therapeutics with reduced side effects, highly sensitive diagnostic tools, efficient ...