Focused On-demand Library for Epithelial splicing regulatory protein 1

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.


Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.


We use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve activity and selectivity.


Our library distinguishes itself through several key aspects:


  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.

  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.

  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.

  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.

PARTNER
Receptor.AI
 
UPACC
Q6NXG1

UPID:
ESRP1_HUMAN

ALTERNATIVE NAMES:
RNA-binding motif protein 35A; RNA-binding protein 35A

ALTERNATIVE UPACC:
Q6NXG1; A6NHA8; A8MPX1; E9PB47; Q2M2B0; Q499G3; Q6PJ86; Q9NXL8

BACKGROUND:
The Epithelial splicing regulatory protein 1, known alternatively as RNA-binding motif protein 35A or RNA-binding protein 35A, is integral to mRNA splicing, influencing epithelial cell-specific isoform formation. It modulates the expression of FGFR2-IIIb and affects the splicing of several genes during the epithelial-to-mesenchymal transition by binding to specific mRNA sequences. Its regulatory function on genes involved in the development of the inner ear and differentiation of auditory hair cells is critical for proper cochlear function.

THERAPEUTIC SIGNIFICANCE:
The direct association of Epithelial splicing regulatory protein 1 with Deafness, autosomal recessive, 109, highlights its therapeutic significance. By elucidating the mechanisms through which this protein influences gene expression and splicing in the auditory system, researchers can identify novel targets for treating severe to profound sensorineural hearing loss and vestibular dysplasia, paving the way for innovative therapeutic approaches in audiological disorders.

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