Focused On-demand Libraries - Receptor.AI 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.


Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed 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.


We utilise our cutting-edge, exclusive workflow to develop focused libraries.


 

Fig. 1. The screening 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
Receptor.AI
 
UPACC
O43395

UPID:
PRPF3_HUMAN

ALTERNATIVE NAMES:
Pre-mRNA-splicing factor 3; U4/U6 snRNP 90 kDa protein

ALTERNATIVE UPACC:
O43395; B4DSY9; O43446; Q5VT54

BACKGROUND:
U4/U6 small nuclear ribonucleoprotein Prp3, known alternatively as Pre-mRNA-splicing factor 3 and U4/U6 snRNP 90 kDa protein, is integral to the pre-mRNA splicing process. It is involved in the assembly of the U4/U6-U5 tri-snRNP complex and the precatalytic spliceosome (spliceosome B complex), essential for spliceosome assembly.

THERAPEUTIC SIGNIFICANCE:
Linked to Retinitis pigmentosa 18, a condition marked by retinal pigment deposits and photoreceptor cell loss leading to night blindness and peripheral vision loss, the gene encoding U4/U6 small nuclear ribonucleoprotein Prp3 is a target for understanding disease mechanisms and developing treatments.

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