AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Vascular endothelial zinc finger 1

Available from Reaxense
Predicted by Alphafold

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.

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.

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.

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

Q14119

UPID:

VEZF1_HUMAN

Alternative names:

Putative transcription factor DB1; Zinc finger protein 161

Alternative UPACC:

Q14119

Background:

Vascular endothelial zinc finger 1, also known as Putative transcription factor DB1 and Zinc finger protein 161, plays a crucial role in gene expression regulation. It specifically binds to the CT/GC-rich region of the interleukin-3 promoter, mediating tax transactivation of IL-3. This protein's involvement in transcriptional regulation underscores its importance in cellular functions and disease mechanisms.

Therapeutic significance:

Linked to Cardiomyopathy, dilated, 1OO, a condition characterized by ventricular dilation and impaired systolic function leading to congestive heart failure and arrhythmia, Vascular endothelial zinc finger 1's study offers insights into genetic underpinnings of heart diseases. Understanding its role could pave the way for novel therapeutic strategies targeting genetic variants affecting this protein.

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.