AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Thiosulfate sulfurtransferase/rhodanese-like domain-containing protein 2

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.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

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 use our state-of-the-art dedicated workflow for designing focused libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of biological functions.

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

Q5T7W7

UPID:

TSTD2_HUMAN

Alternative names:

Rhodanese domain-containing protein 2

Alternative UPACC:

Q5T7W7; A6NMJ4; A8K584; Q6ZQZ6; Q8IYM3; Q8WY73; Q96ML6; Q96MU1

Background:

Thiosulfate sulfurtransferase/rhodanese-like domain-containing protein 2, also known as Rhodanese domain-containing protein 2, plays a crucial role in sulfur metabolism. This protein is pivotal in catalyzing the transfer of sulfur atoms in various biological processes, thereby influencing cellular function and homeostasis.

Therapeutic significance:

Understanding the role of Thiosulfate sulfurtransferase/rhodanese-like domain-containing protein 2 could open doors to potential therapeutic strategies. Its involvement in sulfur metabolism suggests its potential impact on diseases where sulfur transfer is disrupted.

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