AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Lon protease homolog, mitochondrial

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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 our partner Reaxense.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

 Fig. 1. The sreening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.

Several key aspects differentiate our library:

  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

partner

Reaxense

upacc

P36776

UPID:

LONM_HUMAN

Alternative names:

LONHs; Lon protease-like protein; Mitochondrial ATP-dependent protease Lon; Serine protease 15

Alternative UPACC:

P36776; B3KPH8; D6W635; E5KMH8; F5GZ27; P36777; Q8N8K8; Q9UQ95

Background:

Lon protease homolog, mitochondrial, known as LONP1, plays a crucial role in mitochondrial function by mediating the degradation of misfolded proteins and maintaining mitochondrial genome integrity. It exhibits ATP-dependent serine protease activity, targeting damaged polypeptides and regulatory proteins for degradation. LONP1 also binds to mitochondrial DNA and RNA, influencing gene expression and mitochondrial DNA replication.

Therapeutic significance:

LONP1's involvement in CODAS syndrome, a rare condition marked by developmental delays and skeletal anomalies, underscores its therapeutic potential. Understanding the role of Lon protease homolog, mitochondrial could open doors to potential therapeutic strategies for treating mitochondrial disorders and diseases linked to protein misfolding.

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