Focused On-demand Library for Sequestosome-1

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.

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.

We employ our advanced, specialised process to create targeted 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.

Several key aspects differentiate our library:

Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

partner

Reaxense

upacc

Q13501

UPID:

SQSTM_HUMAN

Alternative names:

EBI3-associated protein of 60 kDa; Phosphotyrosine-independent ligand for the Lck SH2 domain of 62 kDa; Ubiquitin-binding protein p62

Alternative UPACC:

Q13501; A6NFN7; B2R661; B3KUW5; Q13446; Q9BUV7; Q9BVS6; Q9UEU1

Background:

Sequestosome-1, also known as p62, plays a pivotal role in autophagy, serving as a bridge between polyubiquitinated cargo and autophagosomes. It is involved in various cellular processes including protein degradation, signal transduction, and organelle turnover. Its interaction with key proteins such as TRAF6 and CYLD underscores its significance in immune response and cell differentiation.

Therapeutic significance:

Given its involvement in diseases like Paget disease of bone 3, frontotemporal dementia, amyotrophic lateral sclerosis, and myopathy with rimmed vacuoles, targeting Sequestosome-1 could lead to novel treatments for these conditions. Understanding the role of Sequestosome-1 could open doors to potential therapeutic strategies.