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.


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 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 employ our advanced, specialised process to create targeted libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance activity and selectivity.


Several key aspects differentiate our library:


  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.

  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.

  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.

  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.


PARTNER
Receptor.AI
 
UPACC
Q8TCT8

UPID:
SPP2A_HUMAN

ALTERNATIVE NAMES:
Intramembrane protease 3; Presenilin-like protein 2

ALTERNATIVE UPACC:
Q8TCT8; B2RDS0; Q8TAW1; Q96SZ8

BACKGROUND:
The protein Signal peptide peptidase-like 2A, with alternative names Intramembrane protease 3 and Presenilin-like protein 2, is integral to the immune system's function. It cleaves type II membrane signal peptides, facilitating the processing of key immune signaling molecules like TNF-alpha and Fas antigen ligand FASLG. Its role extends to the degradation of the invariant chain CD74, vital for antigen presentation.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Signal peptide peptidase-like 2A could open doors to potential therapeutic strategies. Its direct link to Immunodeficiency 86, characterized by heightened vulnerability to mycobacterial infections post-BCG vaccination, highlights its significance in developing targeted therapies for immune deficiencies.

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