AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Glutaminyl-peptide cyclotransferase

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved activity, selectivity, and safety.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate Reaxense.

The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

Our high-tech, dedicated method is applied to construct targeted libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost 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

Reaxense

upacc

Q16769

UPID:

QPCT_HUMAN

Alternative names:

Glutaminyl cyclase; Glutaminyl-tRNA cyclotransferase; Glutamyl cyclase

Alternative UPACC:

Q16769; Q16770; Q3KRG6; Q53TR4

Background:

Glutaminyl-peptide cyclotransferase, also known as Glutaminyl cyclase, plays a pivotal role in the biosynthesis of pyroglutamyl peptides. It exhibits specificity by favoring substrates that do not have acidic or tryptophan residues adjacent to the N-terminal glutaminyl residue. This enzyme is crucial for the formation of N-terminal pyroglutamate, a modification observed in various peptides, including those involved in amyloid plaque formation.

Therapeutic significance:

Understanding the role of Glutaminyl-peptide cyclotransferase could open doors to potential therapeutic strategies. Its involvement in the modification of peptides related to amyloid plaques highlights its significance in neurodegenerative diseases. Targeting this enzyme could offer a novel approach to modulate disease-associated peptide formation.

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