AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Vacuolar-sorting protein SNF8

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 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.

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 high-tech, dedicated method is applied to construct targeted 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 is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

partner

Reaxense

upacc

Q96H20

UPID:

SNF8_HUMAN

Alternative names:

ELL-associated protein of 30 kDa; ESCRT-II complex subunit VPS22

Alternative UPACC:

Q96H20; Q8IXY3; Q9UN50

Background:

Vacuolar-sorting protein SNF8, also known as ELL-associated protein of 30 kDa or ESCRT-II complex subunit VPS22, plays a crucial role in the endosomal sorting complex required for transport II (ESCRT-II). This complex is essential for multivesicular body (MVB) formation and the sorting of endosomal cargo proteins into MVBs, which are pivotal for the degradation of transmembrane proteins in the lysosome. SNF8 is involved in the recruitment of the ESCRT-III complex and may influence transcription regulation through its interaction with ELL. It is vital for the degradation of endocytosed EGF and EGFR, and the exosomal release of SDCBP, CD63, and syndecan.

Therapeutic significance:

Understanding the role of Vacuolar-sorting protein SNF8 could open doors to potential therapeutic strategies.

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