Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced 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 features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.


Our top-notch dedicated system is used to design specialised libraries.


 

Fig. 1. The screening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast 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
Q10713

UPID:
MPPA_HUMAN

ALTERNATIVE NAMES:
Alpha-MPP; Inactive zinc metalloprotease alpha; P-55

ALTERNATIVE UPACC:
Q10713; B4DKL3; E7ET61; Q16639; Q5SXM9; Q8N513

BACKGROUND:
The Mitochondrial-processing peptidase subunit alpha, known alternatively as Alpha-MPP, is integral to mitochondrial protein processing. It serves as the substrate recognition component of the MPP complex, essential for the maturation of mitochondrial proteins by removing their targeting sequences. This function is critical for mitochondrial health and energy production.

THERAPEUTIC SIGNIFICANCE:
Linked to Spinocerebellar ataxia, autosomal recessive, 2, a condition marked by early childhood onset of motor and cognitive impairments, the protein's dysfunction underscores its potential as a therapeutic target. Exploring the molecular mechanisms of Mitochondrial-processing peptidase subunit alpha could lead to novel interventions for mitochondrial diseases.

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