Focused On-demand Libraries - Receptor.AI 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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


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 screening 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
Receptor.AI
 
UPACC
Q7Z4I7

UPID:
LIMS2_HUMAN

ALTERNATIVE NAMES:
LIM-like protein 2; Particularly interesting new Cys-His protein 2

ALTERNATIVE UPACC:
Q7Z4I7; A6NLH0; B4DMV1; F5H6E6; Q7Z4I2; Q7Z4I6; Q7Z4I8; Q8NFE7; Q9HA13

BACKGROUND:
The protein LIM and senescent cell antigen-like-containing domain protein 2, with alternative names LIM-like protein 2 and Particularly interesting new Cys-His protein 2, is integral to modulating cell dynamics. It acts as an adapter, bridging beta-integrins with the actin cytoskeleton and facilitating communication with cell surface receptor tyrosine kinases and growth factor receptors, thus playing a crucial role in cell spreading and migration.

THERAPEUTIC SIGNIFICANCE:
Linked to a rare form of muscular dystrophy that includes cardiomyopathy and a unique triangular tongue shape, the protein's involvement in this autosomal recessive disorder underscores its potential as a target for therapeutic intervention. Understanding the role of LIM and senescent cell antigen-like-containing domain protein 2 could open doors to potential therapeutic strategies.

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