Focused On-demand Library for Trafficking kinesin-binding protein 1

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 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 employ our advanced, specialised process to create targeted 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.

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

Q9UPV9

UPID:

TRAK1_HUMAN

Alternative names:

106 kDa O-GlcNAc transferase-interacting protein; Protein Milton

Alternative UPACC:

Q9UPV9; E9PDS2; J3KNT7; Q63HR0; Q659B5; Q96B69

Background:

Trafficking kinesin-binding protein 1, also known as Protein Milton and 106 kDa O-GlcNAc transferase-interacting protein, plays a pivotal role in cellular processes. It regulates endosome-to-lysosome trafficking, including the endocytic trafficking of EGF-EGFR complexes and GABA-A receptors. Additionally, it is involved in mitochondrial motility and recruits OGT to the mitochondrial surface in neuronal processes.

Therapeutic significance:

The protein's association with Developmental and epileptic encephalopathy 68, a severe early-onset epilepsy, underscores its therapeutic significance. Understanding the role of Trafficking kinesin-binding protein 1 could lead to novel therapeutic strategies for managing this debilitating condition.