Focused On-demand Library for B-cell receptor CD22

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

We use our state-of-the-art dedicated workflow for designing focused libraries.

Fig. 1. The sreening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse biological functions.

Our library stands out due to several important features:

The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

partner

Reaxense

upacc

P20273

UPID:

CD22_HUMAN

Alternative names:

B-lymphocyte cell adhesion molecule; Sialic acid-binding Ig-like lectin 2; T-cell surface antigen Leu-14

Alternative UPACC:

P20273; F5GYU4; F5H7U3; O95699; O95701; O95702; O95703; Q01665; Q32M46; Q92872; Q92873; Q9UQA6; Q9UQA7; Q9UQA8; Q9UQA9; Q9UQB0; Q9Y2A6

Background:

The B-cell receptor CD22, also known as Sialic acid-binding Ig-like lectin 2 or T-cell surface antigen Leu-14, plays a crucial role in mediating B-cell interactions. It binds sialylated glycoproteins, with a preference for alpha-2,6-linked sialic acid, and is involved in the localization of B-cells in lymphoid tissues. CD22's function in immune response includes ligand-induced tyrosine phosphorylation, regulation of B-cell antigen receptor signaling, and potentially acting as an inhibitory receptor by recruiting cytoplasmic phosphatases.

Therapeutic significance:

Understanding the role of B-cell receptor CD22 could open doors to potential therapeutic strategies, particularly in modulating immune responses and developing treatments for B-cell related disorders.