AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for N-acetyltransferase ESCO1

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.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner 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.

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

 Fig. 1. The sreening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost 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

Q5FWF5

UPID:

ESCO1_HUMAN

Alternative names:

CTF7 homolog 1; Establishment factor-like protein 1; Establishment of cohesion 1 homolog 1

Alternative UPACC:

Q5FWF5; B0YJ11; B0YJ12; Q69YG4; Q69YS3; Q6IMD7; Q8N3Z5; Q8NBG2; Q96PX7

Background:

N-acetyltransferase ESCO1, also known as CTF7 homolog 1, plays a pivotal role in sister chromatid cohesion. This enzyme is essential for the acetylation of the cohesin component SMC3, a process crucial for the pairing of sister chromatids during the S phase of the cell cycle. Its activity ensures the accurate separation of chromosomes during cell division.

Therapeutic significance:

Understanding the role of N-acetyltransferase ESCO1 could open doors to potential therapeutic strategies. Its fundamental role in chromosome segregation highlights its potential as a target in diseases characterized by genomic instability.

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