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.


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.


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.


We use our state-of-the-art dedicated workflow for designing focused libraries.


 

Fig. 1. The screening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast 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
Q14152

UPID:
EIF3A_HUMAN

ALTERNATIVE NAMES:
Eukaryotic translation initiation factor 3 subunit 10; eIF-3-theta; eIF3 p167; eIF3 p180; eIF3 p185

ALTERNATIVE UPACC:
Q14152; B1AMV5; B4DYS1; F5H335; O00653; Q15778

BACKGROUND:
The eIF-3A, known alternatively as eIF-3-theta, eIF3 p167, and eIF3 p185, is a key RNA-binding component of the eIF-3 complex, required for protein synthesis initiation. It associates with the 40S ribosome, stimulating mRNA recruitment and scanning for AUG recognition. Its involvement in cell cycle regulation and response to microbial infection highlights its importance in cellular proliferation and viral pathogenesis.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Eukaryotic translation initiation factor 3 subunit A offers a promising avenue for developing novel therapeutic interventions.

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