AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Vacuolar protein sorting-associated protein 28 homolog

Available from Reaxense
Predicted by Alphafold

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.

Our high-tech, dedicated method is applied to construct 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.

Our library distinguishes itself through several key aspects:

  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.

partner

Reaxense

upacc

Q9UK41

UPID:

VPS28_HUMAN

Alternative names:

ESCRT-I complex subunit VPS28

Alternative UPACC:

Q9UK41; Q86VK0

Background:

Vacuolar protein sorting-associated protein 28 homolog (VPS28) is a pivotal component of the ESCRT-I complex, essential for the vesicular trafficking process. This protein plays a crucial role in the sorting of ubiquitinated cargo proteins for lysosomal degradation, thereby maintaining cellular homeostasis. VPS28's involvement in the ESCRT-I complex underscores its significance in cellular biology, particularly in the regulation of endosomal sorting and membrane receptor recycling.

Therapeutic significance:

Understanding the role of Vacuolar protein sorting-associated protein 28 homolog could open doors to potential therapeutic strategies. Its critical function in vesicular trafficking and protein sorting presents a unique opportunity for targeting diseases where these processes are dysregulated.

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