AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Splicing factor U2AF 35 kDa subunit

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

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.

Our high-tech, dedicated method is applied to construct 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 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

Reaxense

upacc

Q01081

UPID:

U2AF1_HUMAN

Alternative names:

U2 auxiliary factor 35 kDa subunit; U2 small nuclear RNA auxiliary factor 1; U2 snRNP auxiliary factor small subunit

Alternative UPACC:

Q01081; Q701P4; Q71RF1

Background:

The Splicing factor U2AF 35 kDa subunit, also known as U2 auxiliary factor 35 kDa subunit, plays a pivotal role in both constitutive and enhancer-dependent splicing. It facilitates protein-protein and protein-RNA interactions necessary for accurate 3'-splice site selection, recruiting U2 snRNP to the branch point and mediating interactions between U2AF2 and enhancer-bound proteins.

Therapeutic significance:

Given its critical function in splicing and its involvement in Myelodysplastic syndrome (MDS) through mutation-induced aberrant alternative splicing, targeting the Splicing factor U2AF 35 kDa subunit presents a promising avenue for therapeutic intervention in MDS and potentially other splicing-related disorders.

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