Focused On-demand Library for L-selectin

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate 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.

Our high-tech, dedicated method is applied to construct targeted libraries.

Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse 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.