Focused On-demand Library for Atlastin-1

Details

Focused On-demand Libraries - Receptor.AI 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.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by Reaxense.


The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal 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

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost 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
Q8WXF7

UPID:
ATLA1_HUMAN

ALTERNATIVE NAMES:
Brain-specific GTP-binding protein; GTP-binding protein 3; Guanine nucleotide-binding protein 3; Spastic paraplegia 3 protein A

ALTERNATIVE UPACC:
Q8WXF7; A6NND5; A8K2C0; G5E9T1; O95890; Q69YH7; Q96FK0

BACKGROUND:
The protein Atlastin-1 plays a crucial role in mediating homotypic fusion of endoplasmic reticulum membranes and is essential for the biogenesis of the endoplasmic reticulum tubular network. Known by several names including Guanine nucleotide-binding protein 3, its function extends to regulating Golgi biogenesis and axonal development, indicating its broad impact on cellular function and health.

THERAPEUTIC SIGNIFICANCE:
Linked to diseases such as Spastic paraplegia 3, autosomal dominant, and hereditary sensory neuropathy, Atlastin-1's dysfunction highlights its potential as a target for therapeutic intervention. Exploring Atlastin-1's mechanisms offers a promising avenue for developing novel therapies for these debilitating conditions, emphasizing the importance of research in this area.

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