Focused On-demand Library for Non-structural maintenance of chromosomes element 3 homolog

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner Reaxense.

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 top-notch dedicated system is used to design specialised libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of biological functions.

Our library stands out due to several important features:

  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.







Alternative names:

Hepatocellular carcinoma-associated protein 4; MAGE-G1 antigen; Melanoma-associated antigen G1; Necdin-like protein 2

Alternative UPACC:

Q96MG7; Q8IW16; Q8TEI6; Q9H214


Non-structural maintenance of chromosomes element 3 homolog (NSMCE3), also known as Hepatocellular carcinoma-associated protein 4, MAGE-G1 antigen, Melanoma-associated antigen G1, and Necdin-like protein 2, plays a crucial role in DNA repair. It is a component of the SMC5-SMC6 complex, essential for the repair of DNA double-strand breaks via homologous recombination and telomere maintenance in ALT cell lines. NSMCE3 also influences the sumoylation of shelterin complex components, facilitating telomere maintenance.

Therapeutic significance:

NSMCE3's involvement in Lung disease, immunodeficiency, and chromosome breakage syndrome, a condition characterized by severe lung disease and immunodeficiency, underscores its therapeutic potential. Understanding the role of NSMCE3 could open doors to potential therapeutic strategies for this and related genetic disorders.

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