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.


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.


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


 

Fig. 1. The screening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse 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
Q5TCH4

UPID:
CP4AM_HUMAN

ALTERNATIVE NAMES:
CYPIVA22; Fatty acid omega-hydroxylase; Lauric acid omega-hydroxylase; Long-chain fatty acid omega-monooxygenase

ALTERNATIVE UPACC:
Q5TCH4; Q5TCH3; Q6JXK7; Q6JXK8; Q9NRM4

BACKGROUND:
The enzyme Cytochrome P450 4A22, also referred to as Lauric acid omega-hydroxylase or Long-chain fatty acid omega-monooxygenase, is pivotal in the omega- and (omega-1)-hydroxylation of fatty acids like laurate and palmitate. It is distinguished by its lack of activity towards arachidonic acid and prostaglandin A1, and its absence of functional activity in renal 20-HETE biosynthesis.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of Cytochrome P450 4A22 offers a promising avenue for the development of novel therapeutic approaches in the management of metabolic disorders.

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