Focused On-demand Library for Centromere protein R

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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. Our collaborator, Reaxense, aids in their synthesis and provision.

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 employ our advanced, specialised process to create targeted libraries.

 Fig. 1. The sreening 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 stands out due to several important features:

  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.







Alternative names:

Beta-3-endonexin; Integrin beta-3-binding protein; Nuclear receptor-interacting factor 3

Alternative UPACC:

Q13352; B2R7D8; Q13353; Q5RJ42; Q5RJ44; Q5RJ45; Q7KYX2; Q96CD5; Q9UKB6


Centromere protein R, also known as Beta-3-endonexin, Integrin beta-3-binding protein, and Nuclear receptor-interacting factor 3, plays a pivotal role in transcription regulation, acting as both a coactivator and corepressor. It is specifically involved in the coactivation of nuclear receptors for retinoid X and thyroid hormone, while also serving as a coactivator for estrogen receptor alpha. Additionally, it functions as a transcriptional corepressor through its interaction with NFKB1 and acts as an inhibitor of cyclin A-associated kinase. Its role extends to apoptosis induction in breast cancer cells and participation in the assembly of kinetochore proteins, mitotic progression, and chromosome segregation.

Therapeutic significance:

Understanding the role of Centromere protein R could open doors to potential therapeutic strategies.

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