AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Protein CBFA2T2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved activity, selectivity, and safety.

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

The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

We use our state-of-the-art dedicated workflow for designing focused libraries.

 Fig. 1. The sreening 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

Reaxense

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:

Protein CBFA2T2, also known as ETO homologous on chromosome 20, plays a crucial role in transcriptional repression, embryonic stem cell pluripotency, and primordial germ cell formation. It functions by associating with DNA-binding transcription factors, facilitating the recruitment of corepressors and histone-modifying enzymes. CBFA2T2's involvement in stabilizing key proteins like PRDM14 and OCT4 on chromatin underscores its significance in cellular differentiation and development.

Therapeutic significance:

Understanding the role of Protein CBFA2T2 could open doors to potential therapeutic strategies. Its ability to repress MMP7 expression and potentially act as a tumor suppressor gene candidate highlights its importance in cancer research and therapy development.

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