AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Protein moonraker

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.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

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 employ our advanced, specialised process to create targeted libraries.

 Fig. 1. The sreening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of biological functions.

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

Reaxense

upacc

Q2KHM9

UPID:

MOONR_HUMAN

Alternative names:

OFD1- and FOPNL-interacting protein

Alternative UPACC:

Q2KHM9; A8KA11; B7Z479; O94853; Q05D97; Q2KHN0; Q9UG45

Background:

Protein moonraker, also known as OFD1- and FOPNL-interacting protein, plays a crucial role in centriole duplication and is essential for proper cell division. It positively regulates CEP63 centrosomal localization and is necessary for WDR62 centrosomal localization, promoting CDK2's centrosomal presence. This protein may also be involved in cilium assembly, indicating its multifaceted role in cellular structure and function.

Therapeutic significance:

Protein moonraker's involvement in diseases such as Orofaciodigital syndrome 15, Joubert syndrome 38, and Short-rib thoracic dysplasia 21 without polydactyly highlights its potential as a target for therapeutic intervention. Understanding the role of Protein moonraker could open doors to potential therapeutic strategies, offering hope for patients suffering from these genetic disorders.

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