Focused On-demand Library for Matrix Gla protein

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.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

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

Fig. 1. The sreening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve 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

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.