Focused On-demand Library for Transcriptional regulator ERG

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.

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 methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of 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.

partner

Reaxense

upacc

P11308

UPID:

ERG_HUMAN

Alternative names:

Transforming protein ERG

Alternative UPACC:

P11308; B4DTW5; B4E0T4; Q16113; Q6XXX4; Q6XXX5; Q8IXK9

Background:

The Transcriptional regulator ERG, also known as Transforming protein ERG, encoded by the gene with accession number P11308, plays a pivotal role in gene expression regulation. It achieves this through its involvement in transcriptional regulation, notably by recruiting the SETDB1 histone methyltransferase, which alters local chromatin structure.

Therapeutic significance:

ERG's involvement in Ewing sarcoma, a highly malignant tumor affecting children and adolescents, underscores its therapeutic significance. The chromosomal aberration involving ERG, specifically the translocation t(21;22)(q22;q12) with EWSR1, highlights its role in disease pathogenesis. Targeting ERG's function or its aberrant expression could offer novel therapeutic strategies for Ewing sarcoma.