Focused On-demand Library for Zinc finger MIZ domain-containing protein 1

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner Reaxense.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

We employ our advanced, specialised process to create targeted 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 stands out due to several important features:

  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.







Alternative names:

PIAS-like protein Zimp10; Retinoic acid-induced protein 17

Alternative UPACC:

Q9ULJ6; Q5JSH9; Q7Z7E6


Zinc finger MIZ domain-containing protein 1, also known as PIAS-like protein Zimp10 or Retinoic acid-induced protein 17, plays a crucial role in cellular processes. It acts as a transcriptional coactivator, enhancing the activity of AR and promoting AR sumoylation, which is essential for ligand-dependent transcriptional activity. Additionally, it serves as a coactivator in the TGF-beta signaling pathway, augmenting the SMAD3/SMAD4 transcriptional complex's activity. Its involvement extends to the activation of specific NOTCH1 target genes, including MYC, and it plays a pivotal role in thymocyte, T cell development, and the positioning of pyramidal neurons in the cerebral cortex.

Therapeutic significance:

The protein is implicated in a neurodevelopmental disorder characterized by a spectrum of symptoms including intellectual disability and skeletal anomalies. Understanding the role of Zinc finger MIZ domain-containing protein 1 could open doors to potential therapeutic strategies for this disorder.

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