Explore the Potential with AI-Driven Innovation
This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved activity, selectivity, and safety.
Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner Reaxense.
The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.
Our top-notch dedicated system is used to design specialised libraries.
Fig. 1. The sreening workflow of Receptor.AI
Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse biological functions.
Our library is unique due to several crucial aspects:
partner
Reaxense
upacc
Q99584
UPID:
S10AD_HUMAN
Alternative names:
S100 calcium-binding protein A13
Alternative UPACC:
Q99584; Q52PI9; Q6FGF8
Background:
Protein S100-A13, an S100 calcium-binding protein, is pivotal in the non-classical secretion pathway. It uniquely binds two calcium ions and one copper ion per subunit, facilitating the export of proteins like IL1A and FGF1 in a copper-dependent manner. Its interaction with lipid vesicles is selective, preferring those containing phosphatidylserine over phosphatidylcholine.
Therapeutic significance:
Understanding the role of Protein S100-A13 could open doors to potential therapeutic strategies, especially in conditions where the non-classical protein secretion pathway is implicated.