Focused On-demand Library for Runt-related transcription factor 1

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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.

Our high-tech, dedicated method is applied to construct targeted libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.

Several key aspects differentiate our library:

  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.







Alternative names:

Acute myeloid leukemia 1 protein; Core-binding factor subunit alpha-2; Oncogene AML-1; Polyomavirus enhancer-binding protein 2 alpha B subunit; SL3-3 enhancer factor 1 alpha B subunit; SL3/AKV core-binding factor alpha B subunit

Alternative UPACC:

Q01196; A8MV94; B2RMS4; D3DSG1; O60472; O60473; O76047; O76089; Q13081; Q13755; Q13756; Q13757; Q13758; Q13759; Q15341; Q15343; Q16122; Q16284; Q16285; Q16286; Q16346; Q16347; Q92479


Runt-related transcription factor 1 (RUNX1) plays a pivotal role in hematopoiesis, acting as a core component of the core-binding factor (CBF) complex. It modulates transcription by recognizing specific DNA sequences, essential for normal blood cell development. RUNX1's interaction with various proteins, including CBFB and ELF4, underscores its multifaceted role in gene regulation and lineage commitment of T cells.

Therapeutic significance:

RUNX1's mutation is linked to Familial platelet disorder with associated myeloid malignancy, highlighting its critical role in blood diseases. Understanding RUNX1's function could pave the way for innovative treatments targeting hematological disorders and leukemia.

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