Focused On-demand Libraries - Receptor.AI 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.


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


The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.


We use our state-of-the-art dedicated workflow for designing focused libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive 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.


PARTNER
Receptor.AI
 
UPACC
Q8IY92

UPID:
SLX4_HUMAN

ALTERNATIVE NAMES:
BTB/POZ domain-containing protein 12

ALTERNATIVE UPACC:
Q8IY92; Q69YT8; Q8TF15; Q96JP1

BACKGROUND:
The protein Structure-specific endonuclease subunit SLX4, alternatively named BTB/POZ domain-containing protein 12, is integral to genome integrity. It activates different endonucleases for resolving deleterious DNA structures caused by replication errors, recombination, and DNA damage. SLX4's ability to interact with and promote the cleavage of various DNA structures, including Holliday junctions and replication forks, is essential for DNA repair processes.

THERAPEUTIC SIGNIFICANCE:
Given its critical role in Fanconi anemia complementation group P, characterized by bone marrow failure and increased cancer risk, SLX4 represents a significant target for therapeutic intervention. Exploring SLX4's function offers promising avenues for developing treatments for Fanconi anemia and enhancing our understanding of DNA repair mechanisms.

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