Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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 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 high-tech, dedicated method is applied to construct targeted libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse biological functions.


Our library distinguishes itself through several key aspects:


  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.

  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.

  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.

  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
Q9Y366

UPID:
IFT52_HUMAN

ALTERNATIVE NAMES:
Protein NGD5 homolog

ALTERNATIVE UPACC:
Q9Y366; B3KMA1; E1P5W9; Q5H8Z0; Q9H1G3; Q9H1G4; Q9H1H2

BACKGROUND:
The protein Intraflagellar transport protein 52 homolog, alternatively known as Protein NGD5 homolog, is integral to the bi-directional movement of particles within cilia, known as intraflagellar transport. This process is vital for cilia's assembly, maintenance, and proper functioning, with IFT52 specifically required for moving IFT88 forward within the ciliary structure.

THERAPEUTIC SIGNIFICANCE:
Mutations in IFT52 have been identified as causative for Short-rib thoracic dysplasia 16, a disease presenting with severe skeletal and possible organ anomalies. The exploration of IFT52's function offers promising avenues for developing targeted therapies for such genetic disorders.

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.