Focused On-demand Library for Alpha-synuclein

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.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner 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.

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

 Fig. 1. The sreening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve 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.







Alternative names:

Non-A beta component of AD amyloid; Non-A4 component of amyloid precursor

Alternative UPACC:

P37840; A8K2A4; Q13701; Q4JHI3; Q6IAU6


Alpha-synuclein, known also as Non-A beta component of AD amyloid or Non-A4 component of amyloid precursor, plays pivotal roles in synaptic activity. It regulates synaptic vesicle trafficking, neurotransmitter release, and acts as a molecular chaperone for SNAREs, crucial for synaptic fusion. Additionally, it modulates dopamine neurotransmission, associating with the dopamine transporter.

Therapeutic significance:

Alpha-synuclein's malfunction is linked to neurodegenerative disorders such as Parkinson disease 1 and 4, and Dementia with Lewy bodies. These associations highlight its critical role in the pathology of these diseases, suggesting that targeting alpha-synuclein could offer novel therapeutic avenues for treating such debilitating conditions.

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