Focused On-demand Library for DNA-directed RNA polymerase III subunit RPC7

Focused On-demand Libraries - Reaxense 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.

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.

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 sreening 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.

Key features that set our library apart include:

The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

upacc

O15318

UPID:

RPC7_HUMAN

Alternative names:

DNA-directed RNA polymerase III subunit G; RNA polymerase III 32 kDa apha subunit; RNA polymerase III 32 kDa subunit

Alternative UPACC:

O15318; A8MTH0

Background:

DNA-directed RNA polymerase III subunit RPC7, also known as the 32 kDa subunit, plays a pivotal role in the transcription of DNA into RNA, focusing on small RNAs like 5S rRNA and tRNAs. It is a key component of the RNA polymerase III complex, interacting with the TFIIIB-DNA complex to facilitate transcription initiation. Beyond its primary function, RPC7 is crucial in the innate immune response, detecting foreign DNA and triggering antiviral pathways.

Therapeutic significance:

Understanding the role of DNA-directed RNA polymerase III subunit RPC7 could open doors to potential therapeutic strategies. Its involvement in innate immunity and transcription regulation highlights its potential as a target for modulating immune responses and treating diseases linked to transcription dysregulation.