Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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 features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.


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
Q15326

UPID:
ZMY11_HUMAN

ALTERNATIVE NAMES:
Adenovirus 5 E1A-binding protein; Bone morphogenetic protein receptor-associated molecule 1; Protein BS69

ALTERNATIVE UPACC:
Q15326; B2R6G8; B7Z293; F6UH50; Q2LD45; Q2LD46; Q2LD47; Q2LD48; Q5VUI1; Q8N4B3

BACKGROUND:
Zinc finger MYND domain-containing protein 11, recognized for its binding to H3.3K36me3, plays a pivotal role in transcription regulation by modulating RNA polymerase II. Its ability to colocalize with highly expressed genes and act as a tumor-suppressor by repressing essential transcriptional programs for tumor growth emphasizes its significance in cellular processes.

THERAPEUTIC SIGNIFICANCE:
Given its direct involvement in Intellectual developmental disorder, autosomal dominant 30, and its tumor-suppressor functions, Zinc finger MYND domain-containing protein 11 presents a promising avenue for developing novel therapeutic interventions. Its role in disease mechanisms offers valuable insights for targeted drug discovery.

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