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.
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 features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.
We employ our advanced, specialised process to create targeted libraries for enzymes.
Fig. 1. The sreening workflow of Receptor.AI
The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance activity and selectivity.
Our library distinguishes itself through several key aspects:
partner
Reaxense
upacc
Q13206
UPID:
DDX10_HUMAN
Alternative names:
DEAD box protein 10
Alternative UPACC:
Q13206; B2RCQ3; Q5BJD8
Background:
Probable ATP-dependent RNA helicase DDX10, also known as DEAD box protein 10, plays a crucial role in RNA metabolism. This protein is involved in various RNA processes, including transcription, splicing, and ribosome biogenesis, showcasing its versatility in cellular functions.
Therapeutic significance:
Understanding the role of Probable ATP-dependent RNA helicase DDX10 could open doors to potential therapeutic strategies. Its multifaceted role in biological systems makes it an intriguing subject for scientific inquiry and drug discovery.