Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.


We utilise our cutting-edge, exclusive workflow to develop focused libraries for protein-protein interfaces.


 

Fig. 1. The screening workflow of Receptor.AI

This process entails comprehensive molecular simulations of the target protein, individually and in complex with essential partner proteins, along with ensemble virtual screening that focuses on conformational mobility in both its free and complex states. Potential binding pockets are considered at the protein-protein interaction interface and in remote allosteric locations to address every conceivable mechanism of action.


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
P50539

UPID:
MXI1_HUMAN

ALTERNATIVE NAMES:
Class C basic helix-loop-helix protein 11

ALTERNATIVE UPACC:
P50539; B1ANN7; D3DR25; D3DRA9; Q15887; Q6FHW2; Q96E53

BACKGROUND:
The Max-interacting protein 1, identified by its alternative name Class C basic helix-loop-helix protein 11, is integral to the transcriptional repression mechanism within cells. By binding with MAX, it forms a specific DNA-binding protein complex, crucial for counteracting MYC transcriptional activities. This regulatory function underscores its importance in gene expression control and cellular equilibrium.

THERAPEUTIC SIGNIFICANCE:
The association of Max-interacting protein 1 with prostate cancer underscores its therapeutic potential. By elucidating the protein's role in this malignancy, researchers can unlock novel therapeutic strategies. Targeting the pathways influenced by this protein could pave the way for innovative treatments, offering hope for improved management of prostate cancer.

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