AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for A disintegrin and metalloproteinase with thrombospondin motifs 2

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.

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 method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance activity and selectivity.

Our library stands out due to several important features:

  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

partner

Reaxense

upacc

O95450

UPID:

ATS2_HUMAN

Alternative names:

Procollagen I N-proteinase; Procollagen I/II amino propeptide-processing enzyme; Procollagen N-endopeptidase

Alternative UPACC:

O95450

Background:

A disintegrin and metalloproteinase with thrombospondin motifs 2 (ADAMTS2) plays a crucial role in the biosynthesis of collagen, facilitating the cleavage of propeptides from type I and II collagen, essential for fibril assembly. This enzyme selectively does not act on type III collagen but modifies lysyl oxidase LOX, impacting collagen-binding activity. Known by alternative names such as Procollagen I N-proteinase, this protein is pivotal in connective tissue integrity.

Therapeutic significance:

ADAMTS2's mutation leads to Ehlers-Danlos syndrome, dermatosparaxis type, characterized by extreme skin fragility, joint hypermobility, and tissue fragility. Understanding the role of ADAMTS2 could open doors to potential therapeutic strategies, offering hope for targeted treatments for this and related connective tissue disorders.

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