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.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is 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 use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.


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
P01374

UPID:
TNFB_HUMAN

ALTERNATIVE NAMES:
TNF-beta; Tumor necrosis factor ligand superfamily member 1

ALTERNATIVE UPACC:
P01374; Q8N4C3; Q9UKS8

BACKGROUND:
The protein Lymphotoxin-alpha, known alternatively as TNF-beta, plays a crucial role in immune regulation and inflammation through its interaction with TNF receptors. Its ability to form complexes with other ligands and induce cytotoxic effects against tumor cells highlights its significance in immune surveillance.

THERAPEUTIC SIGNIFICANCE:
The association of Lymphotoxin-alpha with psoriatic arthritis underscores its potential as a therapeutic target. By elucidating the mechanisms through which it contributes to disease pathology, researchers can unlock new avenues for the development of targeted therapies, offering hope for patients suffering from this debilitating condition.

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