AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Matrix Gla protein

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.

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.

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 sreening 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.

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

P08493

UPID:

MGP_HUMAN

Alternative names:

Cell growth-inhibiting gene 36 protein

Alternative UPACC:

P08493; A0M8W5; B2R519; J3KMX7; Q2TU41; Q567P9; Q6ICN5

Background:

Matrix Gla protein, also known as Cell growth-inhibiting gene 36 protein, plays a crucial role in the human body by associating with the organic matrix of bone and cartilage. It is primarily thought to act as an inhibitor of bone formation, highlighting its significance in skeletal development and maintenance.

Therapeutic significance:

Matrix Gla protein's involvement in Keutel syndrome, a disorder characterized by abnormal cartilage calcification and peripheral pulmonary stenosis, underscores its therapeutic potential. Understanding the role of Matrix Gla protein could open doors to potential therapeutic strategies for treating or managing this condition.

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