Focused On-demand Library for Replication factor C subunit 1

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.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

We employ our advanced, specialised process to create targeted libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse 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.







Alternative names:

Activator 1 140 kDa subunit; Activator 1 large subunit; Activator 1 subunit 1; DNA-binding protein PO-GA; Replication factor C 140 kDa subunit; Replication factor C large subunit

Alternative UPACC:

P35251; A8K6E7; Q5XKF5; Q6PKU0; Q86V41; Q86V46


Replication factor C subunit 1, also known as Activator 1 140 kDa subunit, plays a crucial role in DNA replication and repair. It is essential for the elongation of primed DNA templates by DNA polymerase delta and epsilon, facilitated by its interaction with PCNA and activator 1. This protein binds to primer-template junctions and recognizes non-primer template DNA structures, indicating its significance in maintaining genomic stability.

Therapeutic significance:

The protein is linked to Cerebellar ataxia, neuropathy, and vestibular areflexia syndrome, a neurologic disease caused by intronic AAGGG repeat expansions affecting its gene. Understanding the role of Replication factor C subunit 1 could lead to novel therapeutic strategies for this and potentially other related genetic disorders.

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