Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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 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 utilise our cutting-edge, exclusive workflow to develop focused libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of 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
Q6UX04

UPID:
CWC27_HUMAN

ALTERNATIVE NAMES:
Antigen NY-CO-10; Probable inactive peptidyl-prolyl cis-trans isomerase CWC27 homolog; Serologically defined colon cancer antigen 10

ALTERNATIVE UPACC:
Q6UX04; O60529; O60530; Q96EM3

BACKGROUND:
The Spliceosome-associated protein CWC27 homolog, with alternative names such as Antigen NY-CO-10, plays a pivotal role in the spliceosome for pre-mRNA splicing. Its involvement in the splicing of U12-type introns highlights its essential function in RNA maturation and gene expression regulation.

THERAPEUTIC SIGNIFICANCE:
Given its association with Retinitis pigmentosa, a condition characterized by retinal degeneration and neurologic manifestations, exploring the functions of Spliceosome-associated protein CWC27 homolog presents a promising avenue for therapeutic intervention.

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.