Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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 Reaxense.


The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.


We use our state-of-the-art dedicated workflow for designing focused 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
P0DMM9

UPID:
ST1A3_HUMAN

ALTERNATIVE NAMES:
Aryl sulfotransferase 1A3/1A4; Catecholamine-sulfating phenol sulfotransferase; HAST3; M-PST; Monoamine-sulfating phenol sulfotransferase; Placental estrogen sulfotransferase; Sulfotransferase 1A3/1A4; Sulfotransferase, monoamine-preferring; Thermolabile phenol sulfotransferase

ALTERNATIVE UPACC:
P0DMM9; B4DNV0; O95603; P50224; Q1ET66; Q6ZWJ5

BACKGROUND:
The enzyme Sulfotransferase 1A3, with its array of alternative names such as Catecholamine-sulfating phenol sulfotransferase and Placental estrogen sulfotransferase, is pivotal in the sulfate conjugation process of phenolic monoamines and drugs. This process is essential for the metabolism of several neurotransmitters, including dopamine, norepinephrine, and serotonin, and various phenolic and catechol drugs.

THERAPEUTIC SIGNIFICANCE:
The exploration of Sulfotransferase 1A3's function offers a promising avenue for the development of novel therapeutic approaches. Its critical role in neurotransmitter and drug metabolism underscores its potential impact on treatments for neurological disorders and drug efficacy.

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