AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Splicing factor 3B subunit 3

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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 our associate Reaxense.

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.

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

 Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.

Our library is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

partner

Reaxense

upacc

Q15393

UPID:

SF3B3_HUMAN

Alternative names:

Pre-mRNA-splicing factor SF3b 130 kDa subunit; STAF130; Spliceosome-associated protein 130

Alternative UPACC:

Q15393; Q6NTI8; Q96GC0; Q9BPY2; Q9UFX7; Q9UJ29

Background:

Splicing factor 3B subunit 3, also known as Pre-mRNA-splicing factor SF3b 130 kDa subunit, STAF130, and Spliceosome-associated protein 130, plays a crucial role in pre-mRNA splicing. It is a component of the SF3B complex within the spliceosome, essential for 'A' complex assembly and U2 snRNP's stable binding to pre-mRNA. Its involvement extends to the assembly of the 'E' complex and the splicing of U12-type introns, highlighting its significance in RNA processing.

Therapeutic significance:

Understanding the role of Splicing factor 3B subunit 3 could open doors to potential therapeutic strategies.

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