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.


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.


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 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.


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
P10144

UPID:
GRAB_HUMAN

ALTERNATIVE NAMES:
C11; CTLA-1; Cathepsin G-like 1; Cytotoxic T-lymphocyte proteinase 2; Fragmentin-2; Granzyme-2; Human lymphocyte protein; SECT; T-cell serine protease 1-3E

ALTERNATIVE UPACC:
P10144; Q8N1D2; Q9UCC1

BACKGROUND:
Granzyme B, alternatively known as Cathepsin G-like 1 and T-cell serine protease 1-3E, is abundant in the immune system's cytotoxic cells. It activates caspase-independent cell death by cleaving gasdermin-E and is instrumental in the apoptosis cascade by processing caspases -3, -9, and -10. Its ability to cleave and activate CASP7 in bacterial infections underscores its role in immune defense and cellular integrity maintenance.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of Granzyme B offers a promising avenue for the development of novel therapeutic interventions.

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