AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Beta-soluble NSF attachment protein

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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.

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 employ our advanced, specialised process to create 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 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

Q9H115

UPID:

SNAB_HUMAN

Alternative names:

N-ethylmaleimide-sensitive factor attachment protein beta

Alternative UPACC:

Q9H115; B4DK44; Q4G0M0; Q4G187; Q5JXF9; Q8N3C4

Background:

The Beta-soluble NSF attachment protein, also known as N-ethylmaleimide-sensitive factor attachment protein beta, plays a crucial role in vesicular transport between the endoplasmic reticulum and the Golgi apparatus. This protein is essential for the proper functioning of cellular transport mechanisms, ensuring the correct delivery of proteins and lipids within the cell.

Therapeutic significance:

The Beta-soluble NSF attachment protein is linked to Developmental and epileptic encephalopathy 107 (DEE107), a severe neurological condition characterized by early-onset epilepsies, neurodevelopmental impairment, and a poor prognosis. Understanding the role of this protein could lead to novel therapeutic strategies for treating DEE107, offering hope for patients and families affected by this devastating disease.

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