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.


We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.


We utilise our cutting-edge, exclusive workflow to develop focused libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize 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
Q16769

UPID:
QPCT_HUMAN

ALTERNATIVE NAMES:
Glutaminyl cyclase; Glutaminyl-tRNA cyclotransferase; Glutamyl cyclase

ALTERNATIVE UPACC:
Q16769; Q16770; Q3KRG6; Q53TR4

BACKGROUND:
The enzyme Glutaminyl-peptide cyclotransferase, known alternatively as Glutamyl cyclase, is integral to the formation of pyroglutamyl peptides. It selectively catalyzes the formation of N-terminal pyroglutamate in peptides, a process critical for the biological activity of many peptides. Notably, it is involved in the pyroglutamate modification of amyloid-beta peptides, which are key components in the pathology of Alzheimer's disease.

THERAPEUTIC SIGNIFICANCE:
The exploration of Glutaminyl-peptide cyclotransferase's function offers promising avenues for therapeutic intervention. Given its role in the formation of pyroglutamate-modified amyloid-beta peptides, strategies to modulate its activity could lead to innovative treatments for Alzheimer's disease and other amyloid-related conditions.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.