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.


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.


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.


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
Receptor.AI
 
UPACC
Q9NVI1

UPID:
FANCI_HUMAN

ALTERNATIVE NAMES:
-

ALTERNATIVE UPACC:
Q9NVI1; A4ZVE4; A5YMH4; A6NJZ0; Q96JN1; Q96ST0; Q9BT96

BACKGROUND:
Fanconi anemia group I protein is integral to the homologous recombination repair of DNA double-strand breaks and the repair of interstrand DNA cross-links, crucial for genomic stability. It promotes FANCD2 monoubiquitination and is vital for DNA repair site recruitment. Its ability to bind branched DNA, including both ssDNA and dsDNA, underscores its essential role in the cellular response to DNA damage.

THERAPEUTIC SIGNIFICANCE:
The association of Fanconi anemia complementation group I with mutations in the gene for this protein highlights its importance in disease. This condition, characterized by anemia, leukopenia, and thrombopenia, along with a predisposition to malignancies, points to the critical role of the Fanconi anemia group I protein in DNA repair pathways. Leveraging insights into its function offers promising avenues for developing novel therapeutic interventions.

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