AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Matrix metalloproteinase-23

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best 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

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

O75900

UPID:

MMP23_HUMAN

Alternative names:

Femalysin; MIFR-1; Matrix metalloproteinase-21; Matrix metalloproteinase-22

Alternative UPACC:

O75900; A2AGN0; A2AGN1; O75894; O75895; Q5QPQ8; Q76P96; Q7LDM6; Q7LDM7; Q9UBR9; Q9UJK8

Background:

Matrix metalloproteinase-23, known by alternative names such as Femalysin, MIFR-1, and Matrix metalloproteinases 21 and 22, plays a crucial role as a protease. It is implicated in regulating the surface expression of potassium channels by retaining them in the endoplasmic reticulum, showcasing its significance in cellular processes.

Therapeutic significance:

Understanding the role of Matrix metalloproteinase-23 could open doors to potential therapeutic strategies. Its involvement in key cellular mechanisms highlights its potential as a target for drug discovery, aiming to modulate potassium channel activities for therapeutic benefits.

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