AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Matrix metalloproteinase-17

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.

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.

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

Q9ULZ9

UPID:

MMP17_HUMAN

Alternative names:

Membrane-type matrix metalloproteinase 4; Membrane-type-4 matrix metalloproteinase

Alternative UPACC:

Q9ULZ9; Q14850

Background:

Matrix metalloproteinase-17 (MMP-17), also known as Membrane-type matrix metalloproteinase 4, plays a crucial role in degrading extracellular matrix components like fibrin. It activates precursors of growth factors and inflammatory mediators, including tumor necrosis factor-alpha, and is implicated in tumor processes. MMP-17's specificity excludes collagen types I-V, gelatin, fibronectin, laminin, decorin, and alpha1-antitrypsin.

Therapeutic significance:

Understanding the role of Matrix metalloproteinase-17 could open doors to potential therapeutic strategies.

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