AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Transcription factor IIIB 90 kDa subunit

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.

The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

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

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

Q92994

UPID:

TF3B_HUMAN

Alternative names:

B-related factor 1; TAF3B2; TATA box-binding protein-associated factor, RNA polymerase III, subunit 2

Alternative UPACC:

Q92994; B3KU36; B4DIG5; B7Z2N3; F5H5Z7; F8WA46; Q13223; Q3SYD9; Q5PR24; Q6IQ02; Q96KX3; Q9HCW6; Q9HCW7; Q9HCW8

Background:

Transcription factor IIIB 90 kDa subunit, also known as B-related factor 1, plays a pivotal role in RNA polymerase activation, engaging with different TFIIIB complexes across diverse promoters. It is essential for the transcription of tRNA, adenovirus VA1, 7SL, and 5S RNA, highlighting its versatility in RNA synthesis.

Therapeutic significance:

Linked to Cerebellofaciodental syndrome, a disorder marked by cerebellar hypoplasia and intellectual disability, this protein's genetic variants offer a target for therapeutic intervention. Understanding its role could pave the way for novel treatments.

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