Water molecules are emerging as pivotal players in drug design and the molecular dynamics of protein–ligand complexes. Their unique properties not only mediate solvation effects and contribute ...

Such methodologies underpin both structure-based design and the development of predictive models that accelerate the discovery of effective therapeutics while reducing cost and experimental overhead.

Traditional drug development methods involve identifying a target protein (e.g., a cancer cell receptor) that causes disease, and then searching through countless molecular candidates (potential ...

The newly developed AI can learn and understand the key features required for strong binding to a target protein, and design optimal drug candidate molecules—even without any prior input.

ETH Zurich team captures electron motion in mirror-image molecules, proving chirality is a dynamic electronic property.

It also supports Ligand-Based Drug Design (LBDD) and Structure-Based Drug Design (SBDD) methods, including docking simulations, offering users the flexibility to test a wide range of approaches.

Neo-1 is the first model to unify de novo molecular generation and atomic-level structure prediction in a single model, by generating latent representations of whole molecules instead of ...

Researchers have uncovered how electronic behavior in molecules is influenced by chirality, a key property for drug development. The study, published in Nature, reveals crucial insights into how ...

RNA-binding proteins use a dual binding mechanism involving zinc finger (ZnF) domains and intrinsically disordered regions (IDR), reports a new study from the Institute of Science, Tokyo, Japan.

Peptides have recently emerged at the forefront of therapeutic innovation, with cyclic peptides gaining particular attention for their ...

Opportunities for guanine compounds lie in their use for antiviral, anticancer, and enzyme inhibitor therapies. Innovations in synthetic biology and high-throughput screening enhance development, ...