Focused On-demand Library for Mediator of RNA polymerase II transcription subunit 23

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 carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

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 employ our advanced, specialised process to create targeted libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive 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.







Alternative names:

Activator-recruited cofactor 130 kDa component; Cofactor required for Sp1 transcriptional activation subunit 3; Mediator complex subunit 23; Protein sur-2 homolog; Transcriptional coactivator CRSP130; Vitamin D3 receptor-interacting protein complex 130 kDa component

Alternative UPACC:

Q9ULK4; B9TX55; O95403; Q5JWT3; Q5JWT4; Q6P9H6; Q9H0J2; Q9NTT9; Q9NTU0; Q9Y5P7; Q9Y667


Mediator of RNA polymerase II transcription subunit 23 (Med23) plays a pivotal role in gene expression, acting as a key component of the Mediator complex. This complex is essential for the transcriptional activation by serving as a conduit between gene-specific regulatory proteins and the basal RNA polymerase II transcription machinery. Med23 is involved in various processes, including transcriptional activation by adenovirus E1A protein and ELK1-dependent transcription in response to activated Ras signaling.

Therapeutic significance:

Med23's involvement in Intellectual developmental disorder, autosomal recessive 18, with or without epilepsy, underscores its potential as a target for therapeutic intervention. Understanding the role of Med23 could open doors to potential therapeutic strategies.

Looking for more information on this library or underlying technology? Fill out the form below and we'll be in touch with all the details you need.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.