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.


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


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.


Our top-notch dedicated system is used to design specialised libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of 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
Receptor.AI
 
UPACC
Q2KHM9

UPID:
MOONR_HUMAN

ALTERNATIVE NAMES:
OFD1- and FOPNL-interacting protein

ALTERNATIVE UPACC:
Q2KHM9; A8KA11; B7Z479; O94853; Q05D97; Q2KHN0; Q9UG45

BACKGROUND:
The Protein moonraker, with alternative names including OFD1- and FOPNL-interacting protein, is integral to centriole duplication, ensuring accurate cell cycle progression. It supports CEP63 and WDR62 in centrosomal localization and aids in CDK2's centrosomal recruitment. Its potential role in cilium assembly underscores its importance in maintaining cellular integrity and function.

THERAPEUTIC SIGNIFICANCE:
Given Protein moonraker's association with conditions like Orofaciodigital syndrome 15, Joubert syndrome 38, and Short-rib thoracic dysplasia 21, it emerges as a critical target for drug discovery efforts. Understanding the role of Protein moonraker could open doors to potential therapeutic strategies, providing a new avenue for treating these complex genetic diseases.

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