AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Trafficking protein particle complex subunit 12

Available from Reaxense
Predicted by Alphafold

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 use our state-of-the-art dedicated workflow for designing focused 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.

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

Q8WVT3

UPID:

TPC12_HUMAN

Alternative names:

Tetratricopeptide repeat protein 15; Trafficking of membranes and mitosis

Alternative UPACC:

Q8WVT3; B3KV01; D6W4Y2; Q8WVW1; Q9Y395

Background:

Trafficking protein particle complex subunit 12, also known as Tetratricopeptide repeat protein 15, plays a crucial role in cellular processes including endoplasmic reticulum to Golgi apparatus trafficking and chromosome congression. It is essential for kinetochore assembly and stability, facilitating the recruitment of CENPE to kinetochores.

Therapeutic significance:

Linked to the progressive encephalopathy with brain atrophy and spasticity, understanding the role of Trafficking protein particle complex subunit 12 could open doors to potential therapeutic strategies.

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