Focused On-demand Library for Deleted in malignant brain tumors 1 protein

Available from Reaxense
Predicted by Alphafold

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.

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.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

We use our state-of-the-art dedicated workflow for designing focused libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of 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.







Alternative names:

Glycoprotein 340; Hensin; Salivary agglutinin; Surfactant pulmonary-associated D-binding protein

Alternative UPACC:

Q9UGM3; A6NDG4; A6NDJ5; A8E4R5; B1ARE7; B1ARE8; B1ARE9; B1ARF0; B7Z8Y2; F8WEF7; Q59EX0; Q5JR26; Q6MZN4; Q96DU4; Q9UGM2; Q9UJ57; Q9UKJ4; Q9Y211; Q9Y4V9


Deleted in malignant brain tumors 1 protein, also known as Glycoprotein 340, Hensin, Salivary agglutinin, and Surfactant pulmonary-associated D-binding protein, plays a pivotal role in mucosal defense, cellular immune defense, and epithelial differentiation. It is involved in various biological processes including liver regeneration, taste sensation regulation, and acts as a binding protein for broad bacterial specificity.

Therapeutic significance:

Given its involvement in gliomas and its potential role as a tumor suppressor in brain, lung, esophageal, gastric, and colorectal cancers, understanding the role of Deleted in malignant brain tumors 1 protein could open doors to potential therapeutic strategies.

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