Focused On-demand Libraries - Receptor.AI Collaboration


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


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.


Our top-notch dedicated system is used to design specialised libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.


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
Receptor.AI
 
UPACC
Q9NW64

UPID:
RBM22_HUMAN

ALTERNATIVE NAMES:
RNA-binding motif protein 22; Zinc finger CCCH domain-containing protein 16

ALTERNATIVE UPACC:
Q9NW64; A6NDM5; B4DLI9; O95607

BACKGROUND:
The Pre-mRNA-splicing factor RBM22, known for its alternative names RNA-binding motif protein 22 and Zinc finger CCCH domain-containing protein 16, is integral to the spliceosome's activation and catalytic phases. It binds to the U6 snRNA and pre-mRNA intron, playing a pivotal role in the splicing process. Additionally, RBM22 is involved in the nuclear-cytosolic translocation of proteins like SLU7 and PDCD6 under stress conditions.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Pre-mRNA-splicing factor RBM22 holds promise for unveiling novel therapeutic avenues.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.