Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by Reaxense.


The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.


Our high-tech, dedicated method is applied to construct targeted libraries.


 

Fig. 1. The screening 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 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
Q15427

UPID:
SF3B4_HUMAN

ALTERNATIVE NAMES:
Pre-mRNA-splicing factor SF3b 49 kDa subunit; Spliceosome-associated protein 49

ALTERNATIVE UPACC:
Q15427; Q5SZ63

BACKGROUND:
The Splicing factor 3B subunit 4, known for its involvement in the SF3B complex, is integral to the pre-mRNA splicing process. This protein ensures the correct assembly of spliceosomal complexes, facilitating the precise removal of introns from pre-mRNA. Its role in the minor spliceosome's function in U12-type intron splicing further underscores its importance in gene expression regulation.

THERAPEUTIC SIGNIFICANCE:
Given its critical function in RNA splicing, mutations in SF3B4 are associated with Acrofacial dysostosis 1, Nager type, a disorder affecting craniofacial and limb development. Targeting SF3B4's pathway offers a promising avenue for therapeutic intervention in this and potentially other splicing-related diseases.

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