Explore the Potential with AI-Driven Innovation
The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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 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 use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.
Fig. 1. The sreening workflow of Receptor.AI
It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage activity and selectivity.
Our library distinguishes itself through several key aspects:
partner
Reaxense
upacc
Q5H9U9
UPID:
DDX6L_HUMAN
Alternative names:
DEAD box protein 60-like
Alternative UPACC:
Q5H9U9; Q96ND6
Background:
The Probable ATP-dependent RNA helicase DDX60-like, also known as DEAD box protein 60-like, plays a crucial role in RNA metabolism processes, including RNA decay, ribosome biogenesis, and the initiation of translation. Its ATP-dependent helicase activity is pivotal for unwinding RNA structures, facilitating various aspects of RNA processing and turnover.
Therapeutic significance:
Understanding the role of Probable ATP-dependent RNA helicase DDX60-like 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.