Focused On-demand Libraries - Receptor.AI 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.


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.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.


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


 

Fig. 1. The screening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across 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
Q96DU3

UPID:
SLAF6_HUMAN

ALTERNATIVE NAMES:
Activating NK receptor; NK-T-B-antigen

ALTERNATIVE UPACC:
Q96DU3; A6NMW2; B2R8X8; Q14CF0; Q5TAS4; Q5TAS6; Q5TAT3; Q96DV0

BACKGROUND:
The protein SLAM family member 6, with alternative names Activating NK receptor and NK-T-B-antigen, is integral to immune cell regulation. It influences the activation, differentiation, and interconnection of immune cells, playing a role in both innate and adaptive immunity. The activity of this protein is modulated by adapter proteins such as SH2D1A/SAP and SH2D1B/EAT-2, and it is essential for NK cell cytolytic activity, T-cell differentiation, and the negative regulation of the humoral immune response.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of SLAM family member 6 holds promise for identifying novel therapeutic approaches. Its critical role in immune cell regulation underscores its potential as a therapeutic target, particularly in diseases where immune response modulation is beneficial.

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