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 includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.


We employ our advanced, specialised process to create targeted 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.


Key features that set our library apart include:


  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.

  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.

  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.

  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.


PARTNER
Receptor.AI
 
UPACC
Q86U42

UPID:
PABP2_HUMAN

ALTERNATIVE NAMES:
Nuclear poly(A)-binding protein 1; Poly(A)-binding protein II; Polyadenylate-binding nuclear protein 1

ALTERNATIVE UPACC:
Q86U42; D3DS49; O43484

BACKGROUND:
The Polyadenylate-binding protein 2, with alternative names such as Poly(A)-binding protein II, is pivotal in mRNA precursor's 3'-end formation by poly(A) tail addition, influencing mRNA stability and efficiency. It binds to poly(A) and poly(G) with high affinity, potentially protecting the poly(A) tail from degradation. Additionally, it is a part of the PAXT complex, targeting RNA for exosomal degradation.

THERAPEUTIC SIGNIFICANCE:
Linked to Oculopharyngeal muscular dystrophy, Polyadenylate-binding protein 2's dysfunction highlights its importance in muscle gene expression and stability. Exploring its mechanisms offers a promising avenue for developing targeted therapies for this and potentially other related muscular dystrophies.

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