Focused On-demand Library for Coatomer subunit beta'

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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 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.

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

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

Reaxense

upacc

P35606

UPID:

COPB2_HUMAN

Alternative names:

Beta'-coat protein; p102

Alternative UPACC:

P35606; B4DZI8

Background:

The Coatomer subunit beta', also known as Beta'-coat protein or p102, plays a pivotal role in cellular transport mechanisms. It is a key component of the coatomer complex, essential for Golgi budding and vesicular trafficking. This protein binds to dilysine motifs and associates with Golgi non-clathrin-coated vesicles, facilitating the transport of biosynthetic proteins from the ER through the Golgi apparatus. Its interaction with ADP-ribosylation factors underscores its importance in membrane recruitment and Golgi structural integrity.

Therapeutic significance:

Linked to diseases such as Microcephaly 19 and juvenile-onset Osteoporosis with developmental delay, understanding the role of Coatomer subunit beta' could open doors to potential therapeutic strategies. Its involvement in crucial cellular processes makes it a target for research aimed at uncovering novel treatments for these conditions.