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 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.


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.


We employ our advanced, specialised process to create targeted 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.


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
P30533

UPID:
AMRP_HUMAN

ALTERNATIVE NAMES:
Low density lipoprotein receptor-related protein-associated protein 1

ALTERNATIVE UPACC:
P30533; D3DVR9; Q2M310; Q53HQ3; Q53HS6

BACKGROUND:
The Alpha-2-macroglobulin receptor-associated protein, alternatively named Low density lipoprotein receptor-related protein-associated protein 1, serves as a molecular chaperone. It is essential for the regulation of ligand binding activity of LDL receptor-related proteins throughout the secretory pathway, highlighting its significance in cellular mechanisms.

THERAPEUTIC SIGNIFICANCE:
This protein's mutation is associated with Myopia 23, autosomal recessive, characterized by a refractive error where distant objects come into focus in front of the retina. The exploration of Alpha-2-macroglobulin receptor-associated protein's function and its genetic variants offers a promising avenue for developing treatments for myopia and potentially other visual impairments.

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