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.


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.


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


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of biological functions.


Key features that set our library apart include:


  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.

  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.

  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.

  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.


PARTNER
Receptor.AI
 
UPACC
P62879

UPID:
GBB2_HUMAN

ALTERNATIVE NAMES:
G protein subunit beta-2; Transducin beta chain 2

ALTERNATIVE UPACC:
P62879; B3KPU1; P11016; P54312

BACKGROUND:
Guanine nucleotide-binding protein G(I)/G(S)/G(T) subunit beta-2, known alternatively as G protein subunit beta-2 or Transducin beta chain 2, is integral to transmembrane signaling. It facilitates GTPase activity, GDP for GTP replacement, and interaction with effectors, acting through its beta and gamma chains.

THERAPEUTIC SIGNIFICANCE:
Its association with diseases such as Neurodevelopmental disorder with hypotonia and dysmorphic facies and Sick sinus syndrome 4 underscores the therapeutic potential of targeting Guanine nucleotide-binding protein G(I)/G(S)/G(T) subunit beta-2 in drug discovery.

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