AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Vacuolar protein sorting-associated protein 33B

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

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

Q9H267

UPID:

VP33B_HUMAN

Alternative names:

-

Alternative UPACC:

Q9H267; B3KQF6; Q96K14; Q9NRP6; Q9NSF3

Background:

Vacuolar protein sorting-associated protein 33B (VPS33B) plays a crucial role in vesicle-mediated protein trafficking to lysosomal compartments, membrane docking/fusion reactions of late endosomes/lysosomes, and is essential for the proper trafficking of lysyl hydroxylase 3 to intracellular collagen. It also mediates phagolysosomal fusion in macrophages and is involved in endosomal maturation, implicating VIPAS39 in these processes.

Therapeutic significance:

VPS33B is linked to several genetic disorders, including Arthrogryposis, renal dysfunction and cholestasis syndrome 1, Keratoderma-ichthyosis-deafness syndrome, and progressive familial intrahepatic cholestasis 12. These associations highlight its potential as a target for therapeutic intervention in these diseases.

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