AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Vacuolar protein sorting-associated protein 35

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.

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.

Our top-notch dedicated system is used to design specialised libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse biological functions.

Our library stands out due to several important features:

  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

partner

Reaxense

upacc

Q96QK1

UPID:

VPS35_HUMAN

Alternative names:

Maternal-embryonic 3; Vesicle protein sorting 35

Alternative UPACC:

Q96QK1; Q561W2; Q9H016; Q9H096; Q9H4P3; Q9H8J0; Q9NRS7; Q9NVG2; Q9NX80; Q9NZK2

Background:

Vacuolar protein sorting-associated protein 35 (VPS35) is a crucial component of the retromer complex, involved in transporting proteins from endosomes to the Golgi apparatus and plasma membrane. It plays a key role in preventing the misrouting of transmembrane proteins, ensuring their proper recycling and degradation pathways. VPS35 is essential for the retrograde transport of several cargo proteins, including IGF2R and SLC11A2, and interacts with various proteins to facilitate endosomal sorting and recycling.

Therapeutic significance:

Given its pivotal role in neuronal protein sorting, VPS35 is directly implicated in Parkinson disease 17, a neurodegenerative disorder characterized by the loss of dopaminergic neurons and the presence of Lewy bodies. Understanding the role of VPS35 could open doors to potential therapeutic strategies for treating Parkinson's disease by targeting the underlying protein misrouting issues.

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.