Focused On-demand Library for Receptor tyrosine-protein kinase erbB-3

Focused On-demand Libraries - Receptor.AI 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.


Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by Reaxense.


The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal 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 screening 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.


Our library is unique due to several crucial aspects:


  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.

  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.

  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.

  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

PARTNER
Receptor.AI
 
UPACC
P21860

UPID:
ERBB3_HUMAN

ALTERNATIVE NAMES:
Proto-oncogene-like protein c-ErbB-3; Tyrosine kinase-type cell surface receptor HER3

ALTERNATIVE UPACC:
P21860; A8K6L6; B4DIK7; B4DV32; E9PDT8; Q9BUD7

BACKGROUND:
The Receptor tyrosine-protein kinase erbB-3, identified by its alternative names Proto-oncogene-like protein c-ErbB-3 and Tyrosine kinase-type cell surface receptor HER3, is essential for neuregulin-mediated signaling. Its activation by ligands like NRG1 and CSPG5 initiates critical pathways for cell survival and differentiation.

THERAPEUTIC SIGNIFICANCE:
Given its association with conditions such as Lethal congenital contracture syndrome 2, familial Erythroleukemia, and familial Visceral neuropathy, Receptor tyrosine-protein kinase erbB-3 represents a promising target for drug discovery. Its multifaceted role in biological systems makes it an intriguing subject for scientific inquiry and therapeutic development.

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