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 carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


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.


Our high-tech, dedicated method is applied to construct 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 is unique due to several crucial aspects:


  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.

  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.

  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.

  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.


PARTNER
Receptor.AI
 
UPACC
O43439

UPID:
MTG8R_HUMAN

ALTERNATIVE NAMES:
ETO homologous on chromosome 20; MTG8-like protein; MTG8-related protein 1; Myeloid translocation-related protein 1; p85

ALTERNATIVE UPACC:
O43439; B2RAE6; F8W6D7; Q5TGE4; Q5TGE5; Q5TGE6; Q5TGE7; Q8IWF3; Q96B06; Q96L00; Q9H436; Q9UJP8; Q9UJP9; Q9UP24

BACKGROUND:
The Protein CBFA2T2, known for its alternative names such as MTG8-like protein and Myeloid translocation-related protein 1, is integral to the maintenance of the secretory cell lineage in the small intestine. It exerts its function through the repression of AML1-dependent transcription and may play a role in myeloid tumors when the 20q11 region is deleted. Its interaction with the AML1-MTG8/ETO fusion protein, produced in acute myeloid leukemia, further emphasizes its therapeutic potential.

THERAPEUTIC SIGNIFICANCE:
The exploration of Protein CBFA2T2's function offers promising avenues for therapeutic intervention. Its involvement in critical processes such as the regulation of embryonic stem cell pluripotency and differentiation of erythroid progenitors makes it a target of interest in the development of novel treatments for a range of diseases.

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