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.
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.
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 high-tech, dedicated method is applied to construct targeted libraries for enzymes.
Fig. 1. The sreening workflow of Receptor.AI
This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve activity and selectivity.
Our library distinguishes itself through several key aspects:
partner
Reaxense
upacc
Q9Y6V7
UPID:
DDX49_HUMAN
Alternative names:
DEAD box protein 49
Alternative UPACC:
Q9Y6V7; E7ENA0; Q53FJ1; Q9BVQ8
Background:
The Probable ATP-dependent RNA helicase DDX49, also known as DEAD box protein 49, plays a crucial role in RNA metabolism, including RNA splicing, ribosome biogenesis, and possibly mRNA decay. Its ATP-dependent helicase activity is essential for unwinding RNA duplexes, facilitating various aspects of RNA processing and metabolism.
Therapeutic significance:
Understanding the role of Probable ATP-dependent RNA helicase DDX49 could open doors to potential therapeutic strategies. Its involvement in fundamental RNA processes makes it a promising target for interventions in diseases where RNA metabolism is disrupted.