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.
We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate Reaxense.
Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.
We use our state-of-the-art dedicated workflow for designing focused 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.
Several key aspects differentiate our library:
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.