AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Fanconi anemia group D2 protein

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.

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 top-notch dedicated system is used to design specialised 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

Q9BXW9

UPID:

FACD2_HUMAN

Alternative names:

-

Alternative UPACC:

Q9BXW9; Q2LA86; Q69YP9; Q6PJN7; Q9BQ06; Q9H9T9

Background:

The Fanconi anemia group D2 protein, encoded by the gene with accession number Q9BXW9, plays a crucial role in maintaining chromosomal stability. It is instrumental in the repair of DNA double-strand breaks through homologous recombination and single-strand annealing, and is vital for the accurate and efficient pairing of homologs during meiosis. This protein also contributes to checkpoint activation in response to DNA damage and aids in preventing chromatin breakage and loss.

Therapeutic significance:

Given its pivotal role in DNA repair and chromosomal stability, the Fanconi anemia group D2 protein is directly linked to Fanconi anemia complementation group D2, a disorder characterized by bone marrow failure, congenital abnormalities, and cancer predisposition. Targeting the pathways involving this protein could offer novel therapeutic strategies for treating Fanconi anemia and potentially other related genomic instability syndromes.

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