Focused On-demand Library for AFG3-like protein 2

Details

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.


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 utilise our cutting-edge, exclusive workflow to develop 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
Q9Y4W6

UPID:
AFG32_HUMAN

ALTERNATIVE NAMES:
Paraplegin-like protein

ALTERNATIVE UPACC:
Q9Y4W6; Q6P1L0

BACKGROUND:
The AFG3-like protein 2, known alternatively as Paraplegin-like protein, is crucial for mitochondrial integrity and neuronal health. It ensures the proper degradation and maturation of mitochondrial proteins, such as SMDT1/EMRE and paraplegin, thereby supporting efficient mitochondrial function. Its role extends to the regulation of mitochondrial morphology and energy production, highlighting its importance in cellular metabolism and neurodevelopment.

THERAPEUTIC SIGNIFICANCE:
Given its involvement in critical neurodegenerative diseases like Spinocerebellar ataxia 28, Spastic ataxia 5, and Optic atrophy 12, AFG3-like protein 2 represents a promising target for drug discovery. The protein's essential functions in mitochondrial maintenance and neuron development make it a key candidate for developing treatments aimed at these genetic disorders. Exploring AFG3-like protein 2's therapeutic potential could lead to breakthroughs in managing and possibly reversing the effects of these diseases.

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