AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Transitional endoplasmic reticulum ATPase

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate Reaxense.

The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

We utilise our cutting-edge, exclusive workflow to develop focused 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 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

P55072

UPID:

TERA_HUMAN

Alternative names:

15S Mg(2+)-ATPase p97 subunit; Valosin-containing protein

Alternative UPACC:

P55072; B2R5T8; Q0V924; Q2TAI5; Q969G7; Q9UCD5; V9HW80

Background:

Transitional endoplasmic reticulum ATPase, also known as Valosin-containing protein, plays a crucial role in cellular processes including mitosis, membrane trafficking, and protein degradation. It is essential for Golgi reassembly, endoplasmic reticulum stress response, and DNA damage repair. Its involvement in the ubiquitin-proteasome system underscores its importance in maintaining cellular homeostasis.

Therapeutic significance:

Linked to diseases such as Inclusion body myopathy with early-onset Paget disease and Frontotemporal dementia, understanding the Transitional endoplasmic reticulum ATPase's role could unveil novel therapeutic strategies. Its connection to Charcot-Marie-Tooth disease highlights its potential in neurodegenerative and muscular disorder treatment.

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