AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for V-type immunoglobulin domain-containing suppressor of T-cell activation

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, 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.

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

 Fig. 1. The sreening 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.

Our library stands out due to several important features:

  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

partner

Reaxense

upacc

Q9H7M9

UPID:

VISTA_HUMAN

Alternative names:

Platelet receptor Gi24; Stress-induced secreted protein-1; V-set domain-containing immunoregulatory receptor; V-set immunoregulatory receptor

Alternative UPACC:

Q9H7M9; A1L0X9; A4ZYV1; A8MVH5; Q6UXF3; Q8WUG3; Q8WYZ8

Background:

The V-type immunoglobulin domain-containing suppressor of T-cell activation, also known as Platelet receptor Gi24, Stress-induced secreted protein-1, and V-set immunoregulatory receptor, plays a crucial role in immunoregulation. It inhibits the T-cell response, potentially affecting the body's ability to fight infections and diseases. Additionally, it may influence embryonic stem cell differentiation by inhibiting BMP4 signaling and stimulate MMP14-mediated MMP2 activation, impacting tissue remodeling and repair.

Therapeutic significance:

Understanding the role of V-type immunoglobulin domain-containing suppressor of T-cell activation could open doors to potential therapeutic strategies. Its involvement in T-cell regulation and stem cell differentiation presents opportunities for developing treatments for immune disorders and enhancing regenerative medicine.

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