Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.


Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by Reaxense.


Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.


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


 

Fig. 1. The screening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve activity and selectivity.


Our library distinguishes itself through several key aspects:


  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.

  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.

  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.

  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
Q9NXL9

UPID:
MCM9_HUMAN

ALTERNATIVE NAMES:
Mini-chromosome maintenance deficient domain-containing protein 1; Minichromosome maintenance 9

ALTERNATIVE UPACC:
Q9NXL9; B4DR30; B9DI77; Q2KHJ0; Q8N5S5; Q9HCV5

BACKGROUND:
The MCM8-MCM9 complex, with DNA helicase MCM9 as a key component, is indispensable for the repair of DNA damages, including double-stranded breaks and interstrand cross-links, via homologous recombination. It also plays a significant role in DNA mismatch repair post-replication, highlighting its multifaceted role in maintaining genomic stability.

THERAPEUTIC SIGNIFICANCE:
DNA helicase MCM9's involvement in Ovarian dysgenesis 4 underscores its therapeutic significance. By elucidating the mechanisms by which MCM9 influences DNA repair and gametogenesis, novel therapeutic avenues for treating related reproductive disorders may be discovered.

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