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.


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 top-notch dedicated system is used to design specialised libraries.


 

Fig. 1. The screening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast 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
Q06455

UPID:
MTG8_HUMAN

ALTERNATIVE NAMES:
Cyclin-D-related protein; Eight twenty one protein; Protein ETO; Protein MTG8; Zinc finger MYND domain-containing protein 2

ALTERNATIVE UPACC:
Q06455; B7Z4P4; E7EPN4; O14784; Q06456; Q14873; Q16239; Q16346; Q16347; Q6IBL1; Q6NXH1; Q7Z4J5; Q92479; Q9BRZ0

BACKGROUND:
The Protein CBFA2T1, with alternative names such as Cyclin-D-related protein and Eight twenty one protein, is a transcriptional corepressor. It is involved in the repression of gene expression through its interaction with DNA-binding transcription factors, enhancing the recruitment of corepressors and histone-modifying enzymes. Its ability to repress MMP7 expression and act against transactivation mediated by TCF12 highlights its regulatory significance. Furthermore, its role in adipogenesis and the contribution of its fusion form in leukemogenesis underscore its biological importance.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Protein CBFA2T1 offers a promising avenue for the development of novel therapeutic approaches, especially in the context of its regulatory activities and its potential role in the pathogenesis of leukemia.

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