Focused On-demand Library for Runt-related transcription factor 2

Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best 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.


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.


PARTNER
Receptor.AI
 
UPACC
Q13950

UPID:
RUNX2_HUMAN

ALTERNATIVE NAMES:
Acute myeloid leukemia 3 protein; Core-binding factor subunit alpha-1; Oncogene AML-3; Osteoblast-specific transcription factor 2; Polyomavirus enhancer-binding protein 2 alpha A subunit; SL3-3 enhancer factor 1 alpha A subunit; SL3/AKV core-binding factor alpha A subunit

ALTERNATIVE UPACC:
Q13950; O14614; O14615; O95181

BACKGROUND:
The protein Runt-related transcription factor 2, known by its alternative names such as Acute myeloid leukemia 3 protein and Osteoblast-specific transcription factor 2, is central to bone formation and development. It supports transcription activation in osteoblasts and inhibits KAT6B-dependent transcriptional activation, showcasing its multifaceted role in skeletal morphogenesis.

THERAPEUTIC SIGNIFICANCE:
Given RUNX2's critical function in bone dysplasias like Cleidocranial dysplasia 1 and its association with Metaphyseal dysplasia, research into RUNX2 offers promising avenues for developing innovative therapeutic interventions. The protein's gene variants provide a genetic basis for these conditions, making RUNX2 a key target for drug discovery efforts aimed at mitigating skeletal abnormalities.

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