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.


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

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost activity and selectivity.


Our library is unique due to several crucial aspects:


  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.

  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.

  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.

  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.


PARTNER
Receptor.AI
 
UPACC
Q86YJ5

UPID:
MARH9_HUMAN

ALTERNATIVE NAMES:
Membrane-associated RING finger protein 9; Membrane-associated RING-CH protein IX; RING finger protein 179; RING-type E3 ubiquitin transferase MARCHF9

ALTERNATIVE UPACC:
Q86YJ5; B2R9U9; Q86VN5; Q96GG2

BACKGROUND:
The protein E3 ubiquitin-protein ligase MARCHF9, with alternative names such as RING finger protein 179, is pivotal in the ubiquitination pathway. It specifically targets MHC-I, CD4, and ICAM1 for ubiquitination, leading to their lysosomal degradation. This activity is essential for maintaining protein quality control and modulating immune responses.

THERAPEUTIC SIGNIFICANCE:
Exploring the function of E3 ubiquitin-protein ligase MARCHF9 holds promise for uncovering new therapeutic avenues. By manipulating its ubiquitination activity, researchers could potentially devise innovative treatments for diseases where immune system regulation and protein degradation play a critical role.

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