Focused On-demand Library for ETS domain-containing transcription factor ERF

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.

The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

We utilise our cutting-edge, exclusive workflow to develop focused 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

P50548

UPID:

ERF_HUMAN

Alternative names:

Ets2 repressor factor; PE-2

Alternative UPACC:

P50548; B2RAP1; B7Z4R0; Q59G38; Q9UPI7

Background:

ETS domain-containing transcription factor ERF, also known as Ets2 repressor factor or PE-2, plays a crucial role in cellular processes. It acts as a potent transcriptional repressor, binding to the H1 element of the Ets2 promoter, and is pivotal in regulating genes involved in cellular proliferation. ERF is essential for various developmental processes, including extraembryonic ectoderm differentiation, ectoplacental cone cavity closure, and chorioallantoic attachment.

Therapeutic significance:

ERF's involvement in diseases such as Craniosynostosis 4 and Chitayat syndrome, characterized by abnormal skull growth and a complex of facial and digital anomalies respectively, highlights its potential as a therapeutic target. Understanding the role of ETS domain-containing transcription factor ERF could open doors to potential therapeutic strategies for these conditions.