Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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.


The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.


Our top-notch dedicated system is used to design specialised libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse biological functions.


Our library distinguishes itself through several key aspects:


  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.

  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.

  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.

  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
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:
V-type immunoglobulin domain-containing suppressor of T-cell activation, known variably as Platelet receptor Gi24, Stress-induced secreted protein-1, and V-set immunoregulatory receptor, is pivotal in modulating immune responses. It serves to inhibit T-cell activity, a key process in immune system functioning. The protein's potential role in embryonic stem cell differentiation and its capacity to activate MMP2 via MMP14 mediation suggest significant implications for tissue regeneration and disease treatment.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of V-type immunoglobulin domain-containing suppressor of T-cell activation holds promise for uncovering new therapeutic avenues. Its critical role in immune modulation and possible contributions to stem cell differentiation and tissue repair underscore its potential as a target in developing innovative treatments for a range of diseases.

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