Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


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 utilise our cutting-edge, exclusive workflow to develop focused libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage activity and selectivity.


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
Q92743

UPID:
HTRA1_HUMAN

ALTERNATIVE NAMES:
High-temperature requirement A serine peptidase 1; L56; Serine protease 11

ALTERNATIVE UPACC:
Q92743; D3DRE4; Q9UNS5

BACKGROUND:
The Serine protease HTRA1, with alternative names such as L56 and Serine protease 11, is instrumental in modulating the extracellular matrix and cellular signaling pathways. It cleaves various substrates, including fibronectin and IGF-binding proteins, and inhibits TGF-beta signaling, impacting retinal angiogenesis and neuronal development.

THERAPEUTIC SIGNIFICANCE:
Given its association with significant diseases like age-related macular degeneration and various forms of cerebral arteriopathy, Serine protease HTRA1 represents a promising target for drug discovery. Exploring the therapeutic potential of modulating HTRA1's activity could lead to innovative treatments for these debilitating diseases, enhancing patient care and quality of life.

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