Focused On-demand Library for Protein fem-1 homolog C

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.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, 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.

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

Key features that set our library apart include:

The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

upacc

Q96JP0

UPID:

FEM1C_HUMAN

Alternative names:

FEM1-gamma

Alternative UPACC:

Q96JP0; B2RE47; Q8N3V8; Q9H704; Q9NPL6; Q9NPL9

Background:

Protein fem-1 homolog C, also known as FEM1-gamma, plays a crucial role in the cellular machinery as a substrate-recognition component of the Cul2-RING (CRL2) E3 ubiquitin-protein ligase complex within the DesCEND pathway. It specifically targets proteins for ubiquitination and degradation by recognizing a unique C-degron at the extreme C terminus. This process is vital for maintaining protein homeostasis and regulating protein levels in the cell.

Therapeutic significance:

Understanding the role of Protein fem-1 homolog C could open doors to potential therapeutic strategies. Its involvement in the precise regulation of protein degradation highlights its potential as a target for modulating disease-related protein levels.