Focused On-demand Libraries - Receptor.AI 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.
From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.
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 utilise our cutting-edge, exclusive workflow to develop focused libraries for enzymes.
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 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.
Receptor.AI
Q9NY93
UPID:
DDX56_HUMAN
ALTERNATIVE NAMES:
ATP-dependent 61 kDa nucleolar RNA helicase; DEAD box protein 21; DEAD box protein 56
ALTERNATIVE UPACC:
Q9NY93; A4D2K9; C9JV95; Q6IAE2; Q9H9I8