Focused On-demand Library for Neurogenic differentiation factor 1

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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 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 use our state-of-the-art dedicated workflow for designing focused libraries.

Fig. 1. The sreening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse biological functions.

Several key aspects differentiate our library:

Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

partner

Reaxense

upacc

Q13562

UPID:

NDF1_HUMAN

Alternative names:

Class A basic helix-loop-helix protein 3

Alternative UPACC:

Q13562; B2R9I8; F1T0E1; O00343; Q13340; Q5U095; Q96TH0; Q99455; Q9UEC8

Background:

Neurogenic differentiation factor 1, also known as Class A basic helix-loop-helix protein 3, plays a pivotal role in neurogenesis. It acts as a transcriptional activator, binding to E box-containing promoter consensus core sequences to mediate transcriptional activation. This protein is integral in the regulation of cell differentiation pathways, contributing to the formation of various neural and endocrine cells.

Therapeutic significance:

Neurogenic differentiation factor 1 is linked to Maturity-onset diabetes of the young 6 and Type 2 diabetes mellitus, diseases characterized by insulin secretion defects and insulin resistance. Understanding its role could lead to novel therapeutic strategies targeting these metabolic disorders.