Focused On-demand Libraries - Receptor.AI 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 carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. 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 top-notch dedicated system is used to design specialised libraries.


 

Fig. 1. The screening 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.


Key features that set our library apart include:


  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.

  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.

  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.

  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.


PARTNER
Receptor.AI
 
UPACC
P35249

UPID:
RFC4_HUMAN

ALTERNATIVE NAMES:
Activator 1 37 kDa subunit; Activator 1 subunit 4; Replication factor C 37 kDa subunit

ALTERNATIVE UPACC:
P35249; B4DM41; D3DNV2; Q6FHX7

BACKGROUND:
The protein Replication factor C subunit 4, with alternative names such as Activator 1 subunit 4 and Replication factor C 37 kDa subunit, is integral to the DNA replication process. It assists in the elongation phase, working alongside PCNA and activator 1 to ensure the accurate duplication of the genetic material. This subunit's role is vital for maintaining the integrity of the genome during cell division.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of Replication factor C subunit 4 reveals significant therapeutic potential. By delving into its mechanisms within DNA replication and repair, researchers can identify novel approaches to combat genetic diseases and cancer, where genomic integrity is compromised. The protein's critical role offers a promising avenue for drug discovery and development.

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