Focused On-demand Libraries - Receptor.AI 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.


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.


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 for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage 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
Receptor.AI
 
UPACC
Q8WYK0

UPID:
ACO12_HUMAN

ALTERNATIVE NAMES:
Acyl-CoA thioester hydrolase 12; Acyl-coenzyme A thioesterase 12; Cytoplasmic acetyl-CoA hydrolase 1; START domain-containing protein 15

ALTERNATIVE UPACC:
Q8WYK0; B3KVK9; Q5FWE9

BACKGROUND:
The enzyme Acetyl-coenzyme A thioesterase, identified by the accession number Q8WYK0, is integral to cellular energy homeostasis. It preferentially hydrolyzes acetyl-CoA, thereby balancing the intracellular levels of free fatty acids and coenzyme A, essential for metabolic processes. Its alternative names, including Acyl-coenzyme A thioesterase 12 and START domain-containing protein 15, reflect its diverse functions and structural features.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Acetyl-coenzyme A thioesterase unveils potential pathways for therapeutic intervention. Given its central role in metabolic regulation, targeting this enzyme could lead to novel treatments for conditions associated with impaired metabolism and energy production.

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