Focused On-demand Library for ATP-dependent RNA helicase DDX50

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

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

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 stands out due to several important features:

The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

partner

Reaxense

upacc

Q9BQ39

UPID:

DDX50_HUMAN

Alternative names:

DEAD box protein 50; Gu-beta; Nucleolar protein Gu2

Alternative UPACC:

Q9BQ39; Q5VX37; Q8WV76; Q9BWI8

Background:

ATP-dependent RNA helicase DDX50, also known as DEAD box protein 50, Gu-beta, and Nucleolar protein Gu2, plays a crucial role in RNA metabolism. This protein is involved in various RNA processes including ribosome biogenesis, mRNA splicing, and possibly RNA decay, showcasing its multifaceted role in cellular RNA management.

Therapeutic significance:

Understanding the role of ATP-dependent RNA helicase DDX50 could open doors to potential therapeutic strategies. Its involvement in fundamental RNA processes makes it a promising target for drug discovery, aiming to modulate RNA metabolism in disease conditions.