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

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.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

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.

Our top-notch dedicated system is used to design specialised libraries.

Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across 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

Reaxense

upacc

Q9BT43

UPID:

RPC7L_HUMAN

Alternative names:

DNA-directed RNA polymerase III subunit G-like; RNA polymerase III 32 kDa beta subunit

Alternative UPACC:

Q9BT43; B1MVG5

Background:

The DNA-directed RNA polymerase III subunit RPC7-like, also known as DNA-directed RNA polymerase III subunit G-like and RNA polymerase III 32 kDa beta subunit, plays a pivotal role in the transcription of DNA into RNA, focusing on small RNAs such as 5S rRNA and tRNAs. This protein's involvement in the synthesis of these essential components underscores its fundamental importance in cellular processes.

Therapeutic significance:

Understanding the role of DNA-directed RNA polymerase III subunit RPC7-like could open doors to potential therapeutic strategies, especially considering its link to the disease 'Short stature, oligodontia, dysmorphic facies, and motor delay'. This connection highlights the protein's potential impact on developmental and morphological disorders.