AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Oxidation resistance protein 1

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

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 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

Q8N573

UPID:

OXR1_HUMAN

Alternative names:

-

Alternative UPACC:

Q8N573; A6NK11; A8KA34; B3KXL1; B7Z402; B7Z8N5; D3HIS6; Q3LIB5; Q6ZVK9; Q8N8V0; Q9H266; Q9NWC7

Background:

Oxidation resistance protein 1 plays a crucial role in cellular defense mechanisms, primarily through its involvement in protecting cells from oxidative damage. This protein's function is pivotal in maintaining cellular integrity and function by mitigating the detrimental effects of oxidative stress, which can lead to cellular damage and disease.

Therapeutic significance:

The association of Oxidation resistance protein 1 with Cerebellar hypoplasia/atrophy, epilepsy, and global developmental delay highlights its potential therapeutic significance. Understanding the role of Oxidation resistance protein 1 could open doors to potential therapeutic strategies aimed at treating or managing this neurodevelopmental disorder.

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