Focused On-demand Library for NLR family member X1

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.

The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

We utilise our cutting-edge, exclusive workflow to develop focused libraries.

Fig. 1. The sreening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of biological functions.

Key features that set our library apart include:

The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

upacc

Q86UT6

UPID:

NLRX1_HUMAN

Alternative names:

Caterpiller protein 11.3; Nucleotide-binding oligomerization domain protein 5; Nucleotide-binding oligomerization domain protein 9

Alternative UPACC:

Q86UT6; A8K6Q1; B3KPK2; B3KTA2; Q7RTR3; Q96D51; Q9H724

Background:

NLR family member X1, also known as Caterpiller protein 11.3, Nucleotide-binding oligomerization domain protein 5, and Nucleotide-binding oligomerization domain protein 9, plays a crucial role in antiviral signaling. It acts as a negative regulator of MAVS-mediated antiviral responses and promotes autophagy by interacting with TUFM. Additionally, it regulates MAVS-dependent NLRP3 inflammasome activation to attenuate apoptosis and enhances NF-kappa-B and JUN N-terminal kinase dependent signaling.

Therapeutic significance:

Understanding the role of NLR family member X1 could open doors to potential therapeutic strategies, particularly in modulating antiviral responses and autophagy processes.