Focused On-demand Library for Signal-regulatory protein gamma

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 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.

Our top-notch dedicated system is used to design specialised 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 is unique due to several crucial aspects:

Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

partner

Reaxense

upacc

Q9P1W8

UPID:

SIRPG_HUMAN

Alternative names:

CD172 antigen-like family member B; Signal-regulatory protein beta-2

Alternative UPACC:

Q9P1W8; B1AKP6; Q5D051; Q5JV25; Q5MKL4; Q8WWA5; Q9NQK8

Background:

Signal-regulatory protein gamma, also known as CD172 antigen-like family member B or Signal-regulatory protein beta-2, plays a crucial role in immunological processes. It functions as a probable immunoglobulin-like cell surface receptor, facilitating cell-cell adhesion upon binding with CD47. This interaction is pivotal in enhancing antigen-specific T-cell proliferation and co-stimulating T-cell activation.

Therapeutic significance:

Understanding the role of Signal-regulatory protein gamma could open doors to potential therapeutic strategies. Its involvement in T-cell activation and proliferation highlights its significance in immune response modulation, presenting a promising target for immunotherapy developments.