Focused On-demand Libraries - Receptor.AI 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.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated 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.


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of biological functions.


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
Receptor.AI
 
UPACC
Q07889

UPID:
SOS1_HUMAN

ALTERNATIVE NAMES:
-

ALTERNATIVE UPACC:
Q07889; A8K2G3; B4DXG2

BACKGROUND:
The protein Son of sevenless homolog 1 (SOS1) is essential for the regulation of intracellular signaling pathways. It facilitates Ras activation by promoting the exchange of GDP for GTP on Ras, and regulates MAPK3 phosphorylation in response to EGF. Additionally, SOS1 is involved in signal transduction from Ras to Rac, playing a significant role in cellular processes.

THERAPEUTIC SIGNIFICANCE:
Involvement of SOS1 in diseases such as Fibromatosis, gingival, 1, and Noonan syndrome 4 highlights its potential as a therapeutic target. By elucidating the mechanisms by which SOS1 contributes to these diseases, researchers can develop targeted therapies, opening doors to innovative treatments for patients with these genetic conditions.

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