Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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 features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.


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
Q9BZV3

UPID:
IMPG2_HUMAN

ALTERNATIVE NAMES:
Interphotoreceptor matrix proteoglycan of 200 kDa; Sialoprotein associated with cones and rods proteoglycan

ALTERNATIVE UPACC:
Q9BZV3; A8MWT5; Q9UKD4; Q9UKK5

BACKGROUND:
The protein Interphotoreceptor matrix proteoglycan 2, with alternative names including Interphotoreceptor matrix proteoglycan of 200 kDa, is pivotal in retinal health. It binds crucial components like chondroitin sulfate and hyaluronan, facilitating the proper function and structure of photoreceptor cells. Its ability to bind heparin also suggests a complex role in the eye's biochemistry.

THERAPEUTIC SIGNIFICANCE:
The association of Interphotoreceptor matrix proteoglycan 2 with diseases such as Retinitis pigmentosa 56 and Vitelliform macular dystrophy, 5, highlights its therapeutic potential. Targeting this protein could lead to innovative treatments for these debilitating visual impairments, offering hope 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.