AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Cleavage and polyadenylation specificity factor subunit 3

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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 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.

Our top-notch dedicated system is used to design specialised libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage 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

Reaxense

upacc

Q9UKF6

UPID:

CPSF3_HUMAN

Alternative names:

Cleavage and polyadenylation specificity factor 73 kDa subunit; mRNA 3'-end-processing endonuclease CPSF-73

Alternative UPACC:

Q9UKF6; O14769; Q53RS2; Q96F36

Background:

Cleavage and polyadenylation specificity factor subunit 3, also known as CPSF-73, plays a pivotal role in mRNA 3'-end formation, recognizing the AAUAAA signal sequence. It exhibits endonuclease activity, crucial for pre-mRNA processing and histone 3'-end pre-mRNA processing. CPSF-73's involvement in cell cycle progression and microRNA biogenesis underscores its multifunctionality in cellular processes.

Therapeutic significance:

The protein's link to Neurodevelopmental disorder with microcephaly, hypotonia, nystagmus, and seizures highlights its clinical relevance. Understanding CPSF-73's role could open doors to potential therapeutic strategies for this genetic disorder.

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