Focused On-demand Library for Melanoma-associated antigen 3

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 includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

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.

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

P43357

UPID:

MAGA3_HUMAN

Alternative names:

Antigen MZ2-D; Cancer/testis antigen 1.3; MAGE-3 antigen

Alternative UPACC:

P43357; Q6FHI6

Background:

Melanoma-associated antigen 3 (MAGE-3), also known as Antigen MZ2-D and Cancer/testis antigen 1.3, plays a pivotal role in the regulation of ubiquitin ligase activity of RING-type zinc finger-containing E3 ubiquitin-protein ligases. It acts as a repressor of autophagy, enhances TRIM28-mediated ubiquitination of p53/TP53, and is involved in embryonal development, tumor transformation, and progression. Additionally, MAGE-3 promotes cell viability in melanoma cell lines and is recognized by autologous cytolytic T-lymphocytes in melanoma.

Therapeutic significance:

Understanding the role of Melanoma-associated antigen 3 could open doors to potential therapeutic strategies, especially in the context of melanoma treatment and the modulation of autophagy and immune response.