Explore the Potential with AI-Driven Innovation
Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.
The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated 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.
Our top-notch dedicated system is used to design specialised 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.
Key features that set our library apart include:
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.