Focused On-demand Libraries - Receptor.AI 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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.


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


 

Fig. 1. The screening 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 is unique due to several crucial aspects:


  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.

  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.

  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.

  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.


PARTNER
Receptor.AI
 
UPACC
P50548

UPID:
ERF_HUMAN

ALTERNATIVE NAMES:
Ets2 repressor factor; PE-2

ALTERNATIVE UPACC:
P50548; B2RAP1; B7Z4R0; Q59G38; Q9UPI7

BACKGROUND:
The ETS domain-containing transcription factor ERF, with alternative names Ets2 repressor factor and PE-2, is a key regulator of cellular proliferation. It binds to the Ets2 promoter's H1 element, influencing genes critical for cellular growth. ERF's significance extends to developmental roles, necessary for differentiation of the extraembryonic ectoderm, closure of the ectoplacental cone cavity, and ensuring proper chorioallantoic attachment.

THERAPEUTIC SIGNIFICANCE:
Given ERF's critical role in conditions like Craniosynostosis 4, where skull growth is prematurely halted, and Chitayat syndrome, marked by unique facial and limb anomalies, targeting ERF could offer new avenues for treatment. The exploration of ETS domain-containing transcription factor ERF's function is a promising frontier for developing innovative therapeutic interventions.

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