AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Structure-specific endonuclease subunit SLX4

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner Reaxense.

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 top-notch dedicated system is used to design specialised 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.

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

Q8IY92

UPID:

SLX4_HUMAN

Alternative names:

BTB/POZ domain-containing protein 12

Alternative UPACC:

Q8IY92; Q69YT8; Q8TF15; Q96JP1

Background:

Structure-specific endonuclease subunit SLX4, also known as BTB/POZ domain-containing protein 12, plays a pivotal role in maintaining genome stability. It enhances the activity of various endonucleases, resolving harmful DNA structures from replication, recombination intermediates, and DNA damage. SLX4 is crucial in resolving DNA secondary structures, cleaving branched DNA substrates, and interacting with multiple endonucleases to promote the cleavage of complex DNA structures.

Therapeutic significance:

SLX4's involvement in Fanconi anemia complementation group P, a disorder impacting bone marrow and predisposing individuals to malignancies, underscores its therapeutic potential. Understanding SLX4's role could open doors to novel therapeutic strategies for treating Fanconi anemia and related genomic instability disorders.

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