AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Nucleolar GTP-binding protein 2

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 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.

 Fig. 1. The sreening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse biological functions.

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

Q13823

UPID:

NOG2_HUMAN

Alternative names:

Autoantigen NGP-1

Alternative UPACC:

Q13823; Q9BWN7

Background:

Nucleolar GTP-binding protein 2, also known as Autoantigen NGP-1, plays a crucial role in cell proliferation and ribosome biogenesis. It is a GTPase that associates with pre-60S ribosomal subunits in the nucleolus, essential for their nuclear export and maturation. This protein may also influence p53/TP53 protein levels, thereby affecting CDKN1A/p21 levels and modulating RPL23A protein levels.

Therapeutic significance:

Understanding the role of Nucleolar GTP-binding protein 2 could open doors to potential therapeutic strategies. Its involvement in cell proliferation and ribosome biogenesis presents a unique opportunity for targeting diseases where these processes are dysregulated.

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