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.


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 for receptors.


 

Fig. 1. The screening workflow of Receptor.AI

This process includes extensive molecular simulations of the receptor in its native membrane environment, along with ensemble virtual screening that accounts for its conformational mobility. In the case of dimeric or oligomeric receptors, the entire functional complex is modelled, identifying potential binding pockets on and between the subunits to encompass all possible mechanisms 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
Q9UHD0

UPID:
IL19_HUMAN

ALTERNATIVE NAMES:
Melanoma differentiation-associated protein-like protein; NG.1

ALTERNATIVE UPACC:
Q9UHD0; B6VEV9; Q5VUT3; Q96QR4; Q9NUA0

BACKGROUND:
The protein Interleukin-19, with alternative names Melanoma differentiation-associated protein-like protein and NG.1, is a key cytokine in the regulation of inflammatory responses and angiogenesis. It orchestrates the shift of adaptive immunity towards an anti-inflammatory state by regulating key cytokines, notably reducing IFN-gamma and enhancing IL4 and IL13 levels. Originating from osteocytes, it has a significant role in stimulating granulopoiesis and neutrophil production. Its biological activity is mediated through the interaction with the IL20RA and IL20RB receptor complex, leading to the activation of the JAK-STAT signaling pathway, with a notable impact on STAT3.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of Interleukin-19 offers a promising avenue for the development of novel therapeutic interventions, particularly in managing inflammatory and angiogenic disorders.

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