AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Ester hydrolase C11orf54

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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 high-tech, dedicated method is applied to construct targeted libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve 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

Q9H0W9

UPID:

CK054_HUMAN

Alternative names:

-

Alternative UPACC:

Q9H0W9; A8K850; Q6FI88; Q6XYB0; Q96EI3; Q96IX1; Q9Y6B4

Background:

Ester hydrolase C11orf54, encoded by the gene with the accession number Q9H0W9, is known for its ester hydrolase activity, specifically on the substrate p-nitrophenyl acetate. This enzyme plays a crucial role in the hydrolysis of ester bonds, a fundamental biochemical process in various biological systems.

Therapeutic significance:

Understanding the role of Ester hydrolase C11orf54 could open doors to potential therapeutic strategies. Its enzymatic activity suggests a pivotal function in metabolic pathways, which, if modulated, could offer novel approaches to treating diseases.

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