AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for N-acetyltransferase ESCO2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced 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 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 employ our advanced, specialised process to create targeted 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 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

Reaxense

upacc

Q56NI9

UPID:

ESCO2_HUMAN

Alternative names:

Establishment factor-like protein 2; Establishment of cohesion 1 homolog 2

Alternative UPACC:

Q56NI9; B3KW59; Q49AP4

Background:

N-acetyltransferase ESCO2, also known as Establishment factor-like protein 2, plays a crucial role in sister chromatid cohesion. This protein ensures that only sister chromatids are paired together by acetylating the cohesin component SMC3, a process vital for DNA replication and cell division.

Therapeutic significance:

Mutations in ESCO2 are linked to Roberts-SC phocomelia syndrome and Juberg-Hayward syndrome, disorders characterized by limb and facial abnormalities. Understanding the role of N-acetyltransferase ESCO2 could open doors to potential therapeutic strategies for these genetic conditions.

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