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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.


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


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
Q9Y250

UPID:
LZTS1_HUMAN

ALTERNATIVE NAMES:
F37/esophageal cancer-related gene-coding leucine-zipper motif; Fez1

ALTERNATIVE UPACC:
Q9Y250; D3DSQ6; Q9Y5V7; Q9Y5V8; Q9Y5V9; Q9Y5W0; Q9Y5W1; Q9Y5W2

BACKGROUND:
The protein Leucine zipper putative tumor suppressor 1, with alternative names F37/esophageal cancer-related gene-coding leucine-zipper motif and Fez1, is implicated in cell growth regulation. By potentially stabilizing the CDC2-cyclin B1 complex, it aids in cell cycle control and the prevention of uncontrolled proliferation, highlighting its importance as a tumor suppressor.

THERAPEUTIC SIGNIFICANCE:
The link between Leucine zipper putative tumor suppressor 1 and esophageal cancer highlights its therapeutic significance. As the protein may act as a tumor suppressor, elucidating its mechanisms could lead to breakthroughs in cancer therapy, particularly for esophageal cancer, where early detection and treatment options are limited.

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