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.


We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by Reaxense.


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.


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
Q9Y6D9

UPID:
MD1L1_HUMAN

ALTERNATIVE NAMES:
Mitotic arrest deficient 1-like protein 1; Mitotic checkpoint MAD1 protein homolog; Tax-binding protein 181

ALTERNATIVE UPACC:
Q9Y6D9; B3KR41; Q13312; Q75MI0; Q86UM4; Q9UNH0

BACKGROUND:
The Mitotic checkpoint MAD1 protein homolog is integral to the mitotic checkpoint, sequestering MAD2L1 and impairing the spindle assembly checkpoint. This action is pivotal in maintaining genomic stability by preventing premature anaphase onset and ensuring accurate chromosome segregation.

THERAPEUTIC SIGNIFICANCE:
Given its role in chromosomal instability in hepatocellular carcinomas and its association with severe developmental disorders, targeting Mitotic checkpoint MAD1 protein homolog offers a promising avenue for developing treatments for cancer and genetic diseases. Understanding the role of Mitotic checkpoint MAD1 protein homolog could open doors to potential therapeutic strategies.

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