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.


Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by Reaxense.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.


Our high-tech, dedicated method is applied to construct targeted 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.


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
P83876

UPID:
TXN4A_HUMAN

ALTERNATIVE NAMES:
DIM1 protein homolog; Spliceosomal U5 snRNP-specific 15 kDa protein; Thioredoxin-like U5 snRNP protein U5-15kD

ALTERNATIVE UPACC:
P83876; B2RC18; O14834

BACKGROUND:
The Thioredoxin-like protein 4A plays a pivotal role in the spliceosome, the complex responsible for pre-mRNA splicing, through its involvement in the U5 snRNP and U4/U6-U5 tri-snRNP complexes. It is known by several names, including DIM1 protein homolog and Spliceosomal U5 snRNP-specific 15 kDa protein.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Thioredoxin-like protein 4A could open doors to potential therapeutic strategies for Burn-McKeown syndrome, a disease marked by distinct craniofacial features, deafness, and heart defects, underscoring the protein's clinical relevance.

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