Focused On-demand Library for Vesicle-fusing ATPase

Details

Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. 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 utilise our cutting-edge, exclusive workflow to develop focused libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.


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
Receptor.AI
 
UPACC
P46459

UPID:
NSF_HUMAN

ALTERNATIVE NAMES:
N-ethylmaleimide-sensitive fusion protein; Vesicular-fusion protein NSF

ALTERNATIVE UPACC:
P46459; A8K2D9; B4DFA2; Q8N6D7; Q9UKZ2

BACKGROUND:
The protein Vesicle-fusing ATPase, known alternatively as N-ethylmaleimide-sensitive fusion protein or Vesicular-fusion protein NSF, is crucial for the fusion of transport vesicles within the Golgi apparatus and for the transport from the endoplasmic reticulum to the Golgi. It ensures the delivery of cargo proteins to all Golgi compartments, regardless of vesicle origin, and interacts with AMPAR subunit GRIA2 to affect GRIA2 membrane cycling.

THERAPEUTIC SIGNIFICANCE:
The involvement of Vesicle-fusing ATPase in Developmental and epileptic encephalopathy 96, characterized by severe early-onset epilepsies and neurodevelopmental impairments, underscores its therapeutic importance. Exploring the functions of this protein could lead to groundbreaking therapeutic strategies for this and potentially other related neurological disorders.

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