Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.


Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed 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.


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


 

Fig. 1. The screening 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.


Our library stands out due to several important features:


  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.

  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.

  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.

  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
Q96TA2

UPID:
YMEL1_HUMAN

ALTERNATIVE NAMES:
ATP-dependent metalloprotease FtsH1; Meg-4; Presenilin-associated metalloprotease; YME1-like protein 1

ALTERNATIVE UPACC:
Q96TA2; B4DNM1; D3DRV8; D3DRV9; Q5T8D9; Q9H1Q0; Q9UMR9

BACKGROUND:
The ATP-dependent zinc metalloprotease YME1L1, known for its roles as Meg-4 and Presenilin-associated metalloprotease, is integral to mitochondrial integrity. It degrades various proteins in the mitochondrial intermembrane space, facilitating normal mitochondrial structure and function. This protease is key in preventing the accumulation of damaged proteins, ensuring efficient mitochondrial respiration, and promoting cell survival by inhibiting apoptotic pathways.

THERAPEUTIC SIGNIFICANCE:
Given YME1L1's critical function in mitochondrial maintenance and its association with Optic atrophy 11, exploring its mechanisms offers a promising avenue for developing targeted therapies for mitochondrial-related disorders. Understanding the role of YME1L1 could open doors to potential therapeutic strategies.

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