Focused On-demand Library for RNA-binding protein 10

Details

Focused On-demand Libraries - Receptor.AI 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 Reaxense.


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 leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide 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
P98175

UPID:
RBM10_HUMAN

ALTERNATIVE NAMES:
G patch domain-containing protein 9; RNA-binding motif protein 10; RNA-binding protein S1-1

ALTERNATIVE UPACC:
P98175; A0A0A0MR66; C4AM81; Q14136; Q5JRR2; Q9BTE4; Q9BTX0; Q9NTB1

BACKGROUND:
The RNA-binding protein 10, with alternative names such as G patch domain-containing protein 9 and RNA-binding motif protein 10, is implicated in the intricate process of mRNA splicing. Its binding preference for poly(G) and poly(U) RNA homopolymers, alongside its interaction with specific miRNA hairpins, highlights its significant role in post-transcriptional gene regulation.

THERAPEUTIC SIGNIFICANCE:
Its association with TARP syndrome, a disorder marked by distinct physical malformations and cardiac defects, positions RNA-binding protein 10 as a critical gene of interest in the realm of genetic diseases. The exploration of RNA-binding protein 10's function offers promising avenues for the development of novel therapeutic approaches.

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