Focused On-demand Library for Melanoma-associated antigen B1

Available from Reaxense
Predicted by Alphafold

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.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

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

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.







Alternative names:

Cancer/testis antigen 3.1; DSS-AHC critical interval MAGE superfamily 10; MAGE-B1 antigen; MAGE-XP antigen

Alternative UPACC:

P43366; B2RC79; O00601; O75862; Q6FHJ0; Q96CW8


Melanoma-associated antigen B1, known by its alternative names such as Cancer/testis antigen 3.1, DSS-AHC critical interval MAGE superfamily 10, MAGE-B1 antigen, and MAGE-XP antigen, plays a pivotal role in the realm of cancer biology. Its unique expression pattern, predominantly in cancerous tissues and sparingly in normal tissues, marks it as a significant biomarker for cancer diagnosis and prognosis.

Therapeutic significance:

Understanding the role of Melanoma-associated antigen B1 could open doors to potential therapeutic strategies. Its specific expression in cancer cells offers a promising target for cancer immunotherapy, enabling the development of targeted treatments that spare normal, healthy cells, thereby reducing side effects and improving patient outcomes.

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