AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Atlastin-1

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.

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.

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 employ our advanced, specialised process to create targeted libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance activity and selectivity.

Our library distinguishes itself through several key aspects:

  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.

partner

Reaxense

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:

Atlastin-1, known for its roles in GTPase tethering membranes and endoplasmic reticulum tubular network biogenesis, is pivotal in cellular processes. Identified by alternative names such as Brain-specific GTP-binding protein and Spastic paraplegia 3 protein A, it underscores its significance in neurological pathways. Its involvement in Golgi biogenesis and axonal development further highlights its multifaceted functions in cellular architecture and signaling.

Therapeutic significance:

Atlastin-1's mutation is linked to Spastic paraplegia 3, autosomal dominant, and Neuropathy, hereditary sensory, 1D, underscoring its clinical relevance. Understanding Atlastin-1's role could pave the way for innovative treatments targeting these neurodegenerative disorders, offering hope for affected individuals through potential therapeutic strategies.

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