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.


We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.


We employ our advanced, specialised process to create targeted libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive 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
Q3LXA3

UPID:
TKFC_HUMAN

ALTERNATIVE NAMES:
Bifunctional ATP-dependent dihydroxyacetone kinase/FAD-AMP lyase (cyclizing)

ALTERNATIVE UPACC:
Q3LXA3; Q2L9C1; Q53EQ9; Q9BVA7; Q9H895

BACKGROUND:
The bifunctional ATP-dependent dihydroxyacetone kinase/FAD-AMP lyase (cyclizing), alternatively known as Triokinase/FMN cyclase, is pivotal in cellular energy metabolism and immune response modulation. Its enzymatic activity includes the phosphorylation of key glycolytic intermediates and the efficient processing of ribonucleoside diphosphate-X compounds. Additionally, it suppresses the IFIH1-mediated antiviral defense mechanism, indicating its crucial role in maintaining cellular homeostasis.

THERAPEUTIC SIGNIFICANCE:
Linked to Triokinase and FMN cyclase deficiency syndrome, this protein's dysfunction manifests in severe clinical outcomes, including cataracts, developmental delays, and life-threatening cardiomyopathy. The exploration of Triokinase/FMN cyclase's functions and the pathological mechanisms of its associated syndrome could lead to groundbreaking therapeutic interventions, offering hope for affected individuals.

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