Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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.


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.


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
P16278

UPID:
BGAL_HUMAN

ALTERNATIVE NAMES:
Acid beta-galactosidase; Elastin receptor 1

ALTERNATIVE UPACC:
P16278; B2R7H8; B7Z6B0; P16279

BACKGROUND:
Beta-galactosidase, identified by its alternative names Acid beta-galactosidase and Elastin receptor 1, is crucial for breaking down complex carbohydrates in lysosomes. It also functions in the formation of extracellular elastic fibers and connective tissue development. This protein's dual role underscores its importance in cellular homeostasis and tissue integrity.

THERAPEUTIC SIGNIFICANCE:
Given its critical role in diseases like GM1-gangliosidosis and Mucopolysaccharidosis 4B, Beta-galactosidase represents a key target for therapeutic intervention. These conditions, characterized by enzyme deficiency leading to substrate accumulation, highlight the potential of enzyme replacement or enhancement therapies. Understanding the role of Beta-galactosidase could open doors to potential therapeutic strategies.

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