AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for SCL-interrupting locus protein

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.

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 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

Q15468

UPID:

STIL_HUMAN

Alternative names:

TAL-1-interrupting locus protein

Alternative UPACC:

Q15468; Q5T0C5; Q68CN9

Background:

The SCL-interrupting locus protein, also known as TAL-1-interrupting locus protein, plays a pivotal role in embryonic development, cellular growth, and proliferation. It is a key regulator of the sonic hedgehog pathway and is essential for centriole duplication and proper mitotic progression. Its activity influences cell survival and the cell cycle, highlighting its importance in cellular function.

Therapeutic significance:

Linked to Microcephaly 7, primary, autosomal recessive, a condition characterized by significantly reduced brain size and mental retardation, the SCL-interrupting locus protein's genetic variants underscore its critical role in brain development. Understanding the role of this protein could open doors to potential therapeutic strategies for treating microcephaly and related neurological disorders.

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