AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for DNA-directed RNA polymerase III subunit RPC10

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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 our associate Reaxense.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

 Fig. 1. The sreening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of biological functions.

Several key aspects differentiate our library:

  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

partner

Reaxense

upacc

Q9Y2Y1

UPID:

RPC10_HUMAN

Alternative names:

DNA-directed RNA polymerase III subunit K; RNA polymerase III 12.5 kDa subunit; RNA polymerase III subunit C11

Alternative UPACC:

Q9Y2Y1; Q1W6H4; Q96S35

Background:

DNA-directed RNA polymerase III subunit RPC10, also known as the 12.5 kDa subunit, plays a crucial role in transcribing DNA into RNA, focusing on small RNAs like 5S rRNA and tRNAs. It is pivotal in the innate immune response, sensing intracellular bacteria and DNA viruses, and initiating defense mechanisms.

Therapeutic significance:

Linked to Leukodystrophy, hypomyelinating, 21, a neurodegenerative disorder, understanding the role of DNA-directed RNA polymerase III subunit RPC10 could open doors to potential therapeutic strategies.

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