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 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 use our state-of-the-art dedicated workflow for designing focused libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of 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
O75477

UPID:
ERLN1_HUMAN

ALTERNATIVE NAMES:
Endoplasmic reticulum lipid raft-associated protein 1; Protein KE04; Stomatin-prohibitin-flotillin-HflC/K domain-containing protein 1

ALTERNATIVE UPACC:
O75477; B0QZ42; D3DR65; Q53HV0

BACKGROUND:
Erlin-1 is essential for hepatitis C virus (HCV) infection, facilitating both the initiation of RNA replication and the production of infectious virus. This protein's interaction with cholesterol and its role in the ERLIN1/ERLIN2 complex highlight its multifaceted functions in cellular processes.

THERAPEUTIC SIGNIFICANCE:
Given Erlin-1's critical role in HCV infection and its involvement in Spastic paraplegia 62, targeting this protein could offer novel therapeutic avenues. Understanding the role of Erlin-1 could open doors to potential therapeutic strategies, offering hope for treatments against HCV and neurodegenerative disorders.

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