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.


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.


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 employ our advanced, specialised process to create targeted libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide 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
P10109

UPID:
ADX_HUMAN

ALTERNATIVE NAMES:
Adrenal ferredoxin; Ferredoxin-1; Hepatoredoxin

ALTERNATIVE UPACC:
P10109; B0YJ14; Q53YD6

BACKGROUND:
The protein Adrenodoxin, mitochondrial, known alternatively as adrenal ferredoxin, ferredoxin-1, or hepatoredoxin, plays a crucial role in the synthesis of steroid hormones. It acts by transferring electrons between adrenodoxin reductase and CYP11A1, a cytochrome P450 enzyme involved in cholesterol side-chain cleavage, a vital step in steroidogenesis. This process does not involve the formation of a ternary complex but rather a dynamic shuttling of electrons.

THERAPEUTIC SIGNIFICANCE:
Exploring the function of Adrenodoxin, mitochondrial, offers a pathway to novel therapeutic approaches. Given its essential role in the production of steroid hormones, targeting this protein could provide solutions for managing diseases associated with steroid hormone production.

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