Focused On-demand Library for V-set domain-containing T-cell activation inhibitor 1

Details

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.


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


 

Fig. 1. The screening workflow of Receptor.AI

The method includes extensive molecular simulations of the target protein alone and in complex with its most relevant partner proteins, followed by ensemble virtual screening that considers conformational mobility in both free and complex states. Potential binding pockets are examined on the protein-protein interaction interface and in distant allosteric sites to cover all possible mechanisms of action.


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
Q7Z7D3

UPID:
VTCN1_HUMAN

ALTERNATIVE NAMES:
B7 homolog 4; B7h.5; Immune costimulatory protein B7-H4; Protein B7S1; T-cell costimulatory molecule B7x

ALTERNATIVE UPACC:
Q7Z7D3; Q0GN76; Q45VN0; Q5WPZ3; Q6P097; Q9H6B2

BACKGROUND:
The protein V-set domain-containing T-cell activation inhibitor 1, also referred to as B7-H4, B7h.5, and T-cell costimulatory molecule B7x, is integral to immune regulation. It suppresses T-cell-mediated immune responses and plays a significant role, alongside regulatory T-cells, in inhibiting tumor-associated antigen-specific T-cell immunity. This action is crucial for maintaining immune homeostasis and preventing overactive immune responses.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of V-set domain-containing T-cell activation inhibitor 1 offers promising avenues for developing novel therapeutic interventions. Its critical role in modulating immune responses and facilitating tumor immune evasion makes it a compelling target for enhancing cancer immunotherapy.

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