AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Prolyl endopeptidase FAP

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

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 our partner Reaxense.

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

 Fig. 1. The sreening 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.

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

Reaxense

upacc

Q12884

UPID:

SEPR_HUMAN

Alternative names:

170 kDa melanoma membrane-bound gelatinase; Dipeptidyl peptidase FAP; Fibroblast activation protein alpha; Gelatine degradation protease FAP; Integral membrane serine protease; Post-proline cleaving enzyme; Serine integral membrane protease; Surface-expressed protease

Alternative UPACC:

Q12884; O00199; Q53TP5; Q86Z29; Q99998; Q9UID4

Background:

Prolyl endopeptidase FAP, a cell surface glycoprotein serine protease, plays a pivotal role in extracellular matrix degradation. It is involved in various cellular processes such as tissue remodeling, fibrosis, wound healing, inflammation, and tumor growth. This enzyme exhibits a preference for specific consensus sequences and degrades multiple substrates including gelatin and heat-denatured collagen, but not native collagen types I and IV. It also possesses dipeptidyl peptidase activity, targeting neuropeptide hormones.

Therapeutic significance:

Understanding the role of Prolyl endopeptidase FAP could open doors to potential therapeutic strategies. Its involvement in tissue remodeling, wound healing, and tumor progression highlights its significance in developing treatments for fibrosis, chronic wounds, and cancer. Targeting this protease could lead to innovative therapies that modulate its activity for beneficial outcomes.

Looking for more information on this library or underlying technology? Fill out the form below and we'll be in touch with all the details you need.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.