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.


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.


The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.


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 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
O75439

UPID:
MPPB_HUMAN

ALTERNATIVE NAMES:
Beta-MPP; P-52

ALTERNATIVE UPACC:
O75439; O60416; Q96FV4

BACKGROUND:
Mitochondrial-processing peptidase subunit beta, known alternatively as Beta-MPP or P-52, is integral to mitochondrial health, ensuring the maturation of precursor proteins vital for mitochondrial operations. It specifically cleaves after an arginine at position P2, a step necessary for the activation of these proteins. Additionally, it is involved in the turnover of PINK1, a protein implicated in mitochondrial quality control.

THERAPEUTIC SIGNIFICANCE:
Given its crucial role in mitochondrial function and its association with Multiple mitochondrial dysfunctions syndrome 6, the Mitochondrial-processing peptidase subunit beta represents a significant target for therapeutic intervention. Exploring its mechanisms further could unlock novel treatment avenues for related neurodegenerative diseases, highlighting the therapeutic potential of this protein.

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