Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.


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


 

Fig. 1. The screening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage 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
Q9Y570

UPID:
PPME1_HUMAN

ALTERNATIVE NAMES:
-

ALTERNATIVE UPACC:
Q9Y570; B3KMU6; B5MEE7; J3QT22; Q8WYG8; Q9NVT5; Q9UI18

BACKGROUND:
The enzyme Protein phosphatase methylesterase 1, identified by the UniProt accession Q9Y570, is instrumental in the post-translational modification of proteins through demethylation. This enzyme's activity towards PPP2CB and PPP2CA suggests a regulatory mechanism over the PP2A complex, a critical player in various cellular pathways including apoptosis, cell growth, and DNA damage response.

THERAPEUTIC SIGNIFICANCE:
The exploration of Protein phosphatase methylesterase 1's function offers a promising avenue for drug discovery. Given its regulatory impact on the PP2A complex, which is implicated in numerous cellular processes, targeting PPME1 could lead to innovative treatments for conditions associated with PP2A dysfunction.

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