Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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.


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 utilise our cutting-edge, exclusive workflow to develop focused 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
Q9HBG6

UPID:
IF122_HUMAN

ALTERNATIVE NAMES:
WD repeat-containing protein 10; WD repeat-containing protein 140

ALTERNATIVE UPACC:
Q9HBG6; B3KW53; B4DEY9; B4DPW7; E7EQF4; E9PDG2; E9PDX2; G3XAB1; H7C3C0; Q53G36; Q8TC06; Q9BTB9; Q9BTY4; Q9HAT9; Q9HBG5; Q9NV68; Q9UF80

BACKGROUND:
The Intraflagellar transport protein 122 homolog, known alternatively as WD repeat-containing protein 10 or 140, is integral to the formation and function of cilia. It facilitates the retrograde transport within cilia and is crucial for the proper trafficking of G protein-coupled receptors. Its involvement in cilia formation during neuronal patterning and its role as a negative regulator of Shh signaling underscore its importance in developmental processes.

THERAPEUTIC SIGNIFICANCE:
Linked to Cranioectodermal dysplasia 1, characterized by a spectrum of craniofacial, skeletal, and ectodermal abnormalities, the Intraflagellar transport protein 122 homolog's study offers a promising avenue for therapeutic intervention. Understanding its function could lead to novel treatments for affected individuals.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.