Focused On-demand Library for Steroid hormone receptor ERR2

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.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate Reaxense.

The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

Our high-tech, dedicated method is applied to construct targeted libraries.

Fig. 1. The sreening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive 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

O95718

UPID:

ERR2_HUMAN

Alternative names:

ERR beta-2; Estrogen receptor-like 2; Estrogen-related receptor beta; Nuclear receptor subfamily 3 group B member 2

Alternative UPACC:

O95718; A2VDJ2; B6ZGU4; Q5F0P7; Q5F0P8; Q9HCB4

Background:

Steroid hormone receptor ERR2, also known as Estrogen receptor-like 2, plays a pivotal role in gene regulation. It binds a specific DNA sequence to regulate the expression of target genes involved in cell survival, pluripotency, and metabolic processes. Its activity influences the FGF and Wnt signaling pathways, crucial for stem cell renewal and differentiation.

Therapeutic significance:

Linked to autosomal recessive deafness 35, ERR2's genetic variants underscore its clinical relevance. Understanding the role of Steroid hormone receptor ERR2 could open doors to potential therapeutic strategies.