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 for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage 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
Q3SY69

UPID:
AL1L2_HUMAN

ALTERNATIVE NAMES:
Aldehyde dehydrogenase family 1 member L2

ALTERNATIVE UPACC:
Q3SY69; Q3SY68; Q68D62; Q6AI55; Q8N922

BACKGROUND:
The enzyme Mitochondrial 10-formyltetrahydrofolate dehydrogenase, known alternatively as Aldehyde dehydrogenase family 1 member L2, is integral to mitochondrial folate metabolism. It efficiently converts 10-formyltetrahydrofolate to tetrahydrofolate and CO2, facilitating critical cellular functions.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Mitochondrial 10-formyltetrahydrofolate dehydrogenase offers a promising avenue for the development of novel therapeutic approaches. Its central role in metabolic pathways underscores its potential relevance in health and disease.

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