Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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 use our state-of-the-art dedicated workflow for designing focused libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse 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
Q9GZS1

UPID:
RPA49_HUMAN

ALTERNATIVE NAMES:
DNA-directed RNA polymerase I subunit E; RNA polymerase I-associated factor 1; RNA polymerase I-associated factor 53

ALTERNATIVE UPACC:
Q9GZS1; Q5VZT3; Q8NBA9; Q96L20

BACKGROUND:
The protein DNA-directed RNA polymerase I subunit RPA49, alternatively named RNA polymerase I-associated factor 1 and RNA polymerase I-associated factor 53, is essential for the transcription of DNA into RNA, utilizing the four ribonucleoside triphosphates. It is a key part of RNA polymerase I, responsible for the synthesis of ribosomal RNA precursors. Its involvement in the initiation complex formation at the promoter through interaction with Pol I and UBTF/UBF highlights its critical function.

THERAPEUTIC SIGNIFICANCE:
Exploring the function of DNA-directed RNA polymerase I subunit RPA49 holds promise for unveiling novel therapeutic avenues.

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