Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.


Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by Reaxense.


The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.


We employ our advanced, specialised process to create targeted 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
Q8IV45

UPID:
UN5CL_HUMAN

ALTERNATIVE NAMES:
Protein unc-5 homolog C-like; ZU5 and death domain-containing protein

ALTERNATIVE UPACC:
Q8IV45; Q5TGU1

BACKGROUND:
UNC5C-like protein, identified by its alternative names Protein unc-5 homolog C-like and ZU5 and death domain-containing protein, is integral in modulating cellular functions. It achieves this by hindering the binding of NF-kappa-B to its targets, thereby inhibiting NF-kappa-B-dependent transcription. This action underscores the protein's vital role in cellular regulation.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of UNC5C-like protein presents a unique opportunity for therapeutic innovation. Given its crucial role in impeding NF-kappa-B-dependent transcription, this protein could be instrumental in developing treatments targeting inflammatory and immune-mediated conditions, marking a significant step forward in drug discovery.

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