Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced 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.


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.


 

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
Q8NI22

UPID:
MCFD2_HUMAN

ALTERNATIVE NAMES:
Neural stem cell-derived neuronal survival protein

ALTERNATIVE UPACC:
Q8NI22; A8K7W2; D6W5A9; E9PD95; Q53SS3; Q68D61; Q8N3M5

BACKGROUND:
The protein Multiple coagulation factor deficiency protein 2, with alternative names including Neural stem cell-derived neuronal survival protein, is integral to the secretion of coagulation factors. It forms a part of the MCFD2-LMAN1 complex, facilitating the ER-to-Golgi transport of proteins essential for coagulation.

THERAPEUTIC SIGNIFICANCE:
Linked to the blood coagulation disorder Factor V and factor VIII combined deficiency 2, MCFD2's involvement in this disease highlights its potential as a target for therapeutic intervention. Exploring MCFD2's function offers a promising pathway to developing treatments for related coagulation disorders.

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