Focused On-demand Library for Interleukin-1 receptor-associated kinase 4

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.

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.

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 for enzymes.

Fig. 1. The sreening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve activity and selectivity.

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

Q9NWZ3

UPID:

IRAK4_HUMAN

Alternative names:

Renal carcinoma antigen NY-REN-64

Alternative UPACC:

Q9NWZ3; Q69FE1; Q8TDF7; Q9Y589

Background:

Interleukin-1 receptor-associated kinase 4 (IRAK4) is a serine/threonine-protein kinase pivotal in the innate immune response to pathogens. It is involved in signaling pathways initiated by Toll-like receptors and IL-1R, leading to NF-kappa-B activation. Alternative names include Renal carcinoma antigen NY-REN-64.

Therapeutic significance:

IRAK4's role in Immunodeficiency 67, a primary immunodeficiency with recurrent bacterial infections, highlights its potential as a therapeutic target. Understanding IRAK4's function could pave the way for novel treatments.