AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for L-selectin

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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. Our collaborator, Reaxense, aids in their synthesis and provision.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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.

Our library distinguishes itself through several key aspects:

  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.

partner

Reaxense

upacc

P14151

UPID:

LYAM1_HUMAN

Alternative names:

CD62 antigen-like family member L; Leukocyte adhesion molecule 1; Leukocyte surface antigen Leu-8; Leukocyte-endothelial cell adhesion molecule 1; Lymph node homing receptor; TQ1; gp90-MEL

Alternative UPACC:

P14151; A0A024R8Z0; B2R6Q8; P15023; Q9UJ43

Background:

L-selectin, also known as CD62 antigen-like family member L, plays a crucial role in mediating cell adhesion by binding to glycoproteins on neighboring cells. It facilitates the adherence of lymphocytes to endothelial cells in peripheral lymph nodes and supports the initial tethering and rolling of leukocytes in endothelia. This protein's involvement in cell adhesion and immune response highlights its significance in biological systems.

Therapeutic significance:

Understanding the role of L-selectin could open doors to potential therapeutic strategies. Its pivotal function in leukocyte adhesion and migration makes it a promising target for modulating immune responses and treating inflammatory conditions.

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