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.


We employ our advanced, specialised process to create targeted 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.


Our library distinguishes itself through several key aspects:


  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.

  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.

  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.

  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
P49715

UPID:
CEBPA_HUMAN

ALTERNATIVE NAMES:
-

ALTERNATIVE UPACC:
P49715; A7LNP2; P78319; Q05CA4

BACKGROUND:
The CCAAT/enhancer-binding protein alpha plays a key role in various physiological processes, including hematopoiesis, adipogenesis, and hepatic function. It activates or represses gene expression by binding to specific DNA sequences, thus influencing cell fate decisions. CEBPA's interaction with other transcription factors and modulators fine-tunes its regulatory functions, essential for proper tissue development and metabolic regulation.

THERAPEUTIC SIGNIFICANCE:
CEBPA's involvement in acute myelogenous leukemia highlights its potential as a therapeutic target. By elucidating CEBPA's mechanisms in disease progression, novel treatment avenues may be developed, focusing on restoring normal cell differentiation pathways. This approach holds promise for improving outcomes in leukemia and other CEBPA-related conditions.

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