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 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.


We use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve 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
P68402

UPID:
PA1B2_HUMAN

ALTERNATIVE NAMES:
PAF acetylhydrolase 30 kDa subunit; PAF-AH subunit beta

ALTERNATIVE UPACC:
P68402; A8DPS5; A8DPS6; A8DPS7; E9PEJ5; E9PLP3; O00687; Q29459; Q6IBR6

BACKGROUND:
Platelet-activating factor acetylhydrolase IB subunit alpha2, known alternatively as PAF acetylhydrolase 30 kDa subunit or PAF-AH subunit beta, is integral to the cytosolic type I platelet-activating factor (PAF) acetylhydrolase enzyme's function. It specializes in the hydrolysis of PAF and its analogs, playing a crucial role in the regulation of inflammatory mediators. The enzyme's efficiency and specificity are determined by its subunit composition, highlighting its importance in cellular processes.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Platelet-activating factor acetylhydrolase IB subunit alpha2 could open doors to potential therapeutic strategies. Its critical function in the regulation of inflammatory mediators underscores its potential as a therapeutic target, offering new avenues for drug discovery in the treatment of inflammation-related conditions.

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