AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Epsilon-sarcoglycan

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.

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 employ our advanced, specialised process to create targeted 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.

partner

Reaxense

upacc

O43556

UPID:

SGCE_HUMAN

Alternative names:

-

Alternative UPACC:

O43556; B2R8N2; D6W5Q8; E9PF60; G5E9K6; Q6L8P0; Q75MH8; Q8NFG8; Q8WW28

Background:

Epsilon-sarcoglycan, encoded by the gene with accession number O43556, is a crucial component of the sarcoglycan complex. This complex is part of the larger dystrophin-glycoprotein complex, linking the F-actin cytoskeleton to the extracellular matrix. This linkage is vital for the integrity of muscle tissue.

Therapeutic significance:

Dystonia 11, myoclonic, a form of dystonia characterized by involuntary muscle contractions and alleviated by alcohol, is associated with variants in the epsilon-sarcoglycan gene. Understanding the role of epsilon-sarcoglycan could lead to novel therapeutic strategies for this condition.

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