AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Vacuolar protein sorting-associated protein 11 homolog

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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 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 leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of 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

Q9H270

UPID:

VPS11_HUMAN

Alternative names:

RING finger protein 108

Alternative UPACC:

Q9H270; Q8WY89; Q96EP8; Q9H6D9; Q9HCS6

Background:

Vacuolar protein sorting-associated protein 11 homolog, also known as RING finger protein 108, is crucial in vesicle-mediated protein trafficking to lysosomal compartments, including endocytic membrane transport and autophagic pathways. It acts as a core component of the HOPS and CORVET endosomal tethering complexes, facilitating the Rab5-to-Rab7 endosome conversion, essential for membrane fusion events.

Therapeutic significance:

This protein's malfunction is linked to Leukodystrophy, hypomyelinating, 12, and Dystonia 32, diseases characterized by neurologic disorders and dystonia, respectively. Understanding the role of Vacuolar protein sorting-associated protein 11 homolog could open doors to potential therapeutic strategies for these conditions.

Looking for more information on this library or underlying technology? Fill out the form below and we'll be in touch with all the details you need.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
No Spam. Cancel Anytime.