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.


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.


Our high-tech, dedicated method is applied to construct targeted libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize 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
Q9UPY3

UPID:
DICER_HUMAN

ALTERNATIVE NAMES:
Helicase with RNase motif

ALTERNATIVE UPACC:
Q9UPY3; A7E2D3; B3KRG4; E0AD28; O95943; Q9UQ02

BACKGROUND:
The Endoribonuclease Dicer, alternatively named Helicase with RNase motif, is integral to the RNA-induced silencing complex (RISC), facilitating the cleavage of dsRNA into siRNAs and miRNAs. These molecules are instrumental in post-transcriptional gene silencing, playing a key role in maintaining genomic stability and regulating viral defense mechanisms.

THERAPEUTIC SIGNIFICANCE:
Dicer's involvement in critical pathways of RNA interference links it to diseases such as Pleuropulmonary blastoma and Goiter multinodular 1. Harnessing insights into Dicer's mechanisms offers a promising avenue for developing novel therapeutic interventions for these and related genetic disorders.

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