Focused On-demand Library for Epidermal growth factor receptor

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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 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

P00533

UPID:

EGFR_HUMAN

Alternative names:

Proto-oncogene c-ErbB-1; Receptor tyrosine-protein kinase erbB-1

Alternative UPACC:

P00533; O00688; O00732; P06268; Q14225; Q68GS5; Q92795; Q9BZS2; Q9GZX1; Q9H2C9; Q9H3C9; Q9UMD7; Q9UMD8; Q9UMG5

Background:

The Epidermal Growth Factor Receptor (EGFR), also known as Proto-oncogene c-ErbB-1 and Receptor tyrosine-protein kinase erbB-1, plays a pivotal role in cellular signaling pathways. By binding ligands of the EGF family, it activates cascades such as RAS-RAF-MEK-ERK, PI3 kinase-AKT, and others, influencing cell migration, proliferation, and differentiation.

Therapeutic significance:

EGFR's involvement in lung cancer and Inflammatory skin and bowel disease, neonatal, 2, underscores its potential as a therapeutic target. Its role in disease pathogenesis and cell entry facilitation for hepatitis C virus highlights the importance of EGFR modulation in treating these conditions.