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.


We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by Reaxense.


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.


Our high-tech, dedicated method is applied to construct targeted 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
Q969H8

UPID:
MYDGF_HUMAN

ALTERNATIVE NAMES:
-

ALTERNATIVE UPACC:
Q969H8; D6W628; O75256; O75272; Q9BTK7; Q9NP69

BACKGROUND:
Myeloid-derived growth factor is crucial for cardiac myocyte survival and the promotion of adaptive angiogenesis, essential for heart repair after myocardial infarction. It operates through stimulating endothelial cell proliferation via a MAPK1/3-, STAT3-, and CCND1-mediated pathway and preventing cardiac myocyte apoptosis through a PI3K/AKT pathway. This protein's activity underscores its significant role in cardiac protection and repair mechanisms.

THERAPEUTIC SIGNIFICANCE:
The exploration of Myeloid-derived growth factor's functions offers promising avenues for therapeutic intervention. Given its critical role in enhancing cardiac myocyte survival and facilitating angiogenesis, targeting this protein could lead to innovative treatments for heart repair and protection, particularly in the context of myocardial infarction recovery.

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