Explore the Potential with AI-Driven Innovation
The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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 promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.
We utilise our cutting-edge, exclusive workflow to develop focused libraries for enzymes.
Fig. 1. The sreening workflow of Receptor.AI
The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.
Our library distinguishes itself through several key aspects:
partner
Reaxense
upacc
Q7RTY8
UPID:
TMPS7_HUMAN
Alternative names:
Matriptase-3
Alternative UPACC:
Q7RTY8; C9J8P7; E9PAS3; Q17RH4
Background:
Transmembrane protease serine 7, also known as Matriptase-3, is a serine protease that exhibits a preference for hydrolyzing peptides with Arginine at the P1 position. This specificity suggests a critical role in proteolytic processes.
Therapeutic significance:
Understanding the role of Transmembrane protease serine 7 could open doors to potential therapeutic strategies. Its unique enzymatic activity highlights its importance in biological systems and underscores the potential for targeted drug discovery.