Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.


We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by Reaxense.


Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.


Our high-tech, dedicated method is applied to construct 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
Q9P2R6

UPID:
RERE_HUMAN

ALTERNATIVE NAMES:
Atrophin-1-like protein; Atrophin-1-related protein

ALTERNATIVE UPACC:
Q9P2R6; O43393; O75046; O75359; Q5VXL9; Q6P6B9; Q9Y2W4

BACKGROUND:
Arginine-glutamic acid dipeptide repeats protein, known alternatively as Atrophin-1-like or Atrophin-1-related protein, is crucial for developmental transcriptional repression and cell survival. It influences cell fate through BAX recruitment and caspase-3 activation, leading to apoptosis.

THERAPEUTIC SIGNIFICANCE:
Given its association with a neurodevelopmental disorder characterized by developmental delay, intellectual disability, and various congenital defects, the Arginine-glutamic acid dipeptide repeats protein presents a significant target for therapeutic research. Exploring its function and regulation could yield novel treatments for this and potentially other related disorders.

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