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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. 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 employ our advanced, specialised process to create targeted libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive 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
Receptor.AI
 
UPACC
Q8N573

UPID:
OXR1_HUMAN

ALTERNATIVE NAMES:
-

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

BACKGROUND:
The Oxidation resistance protein 1 is instrumental in safeguarding cells from oxidative harm, indicating its vital role in cellular health and longevity. Its ability to counteract oxidative stress underscores its importance in preserving cell viability and preventing oxidative damage-related pathologies.

THERAPEUTIC SIGNIFICANCE:
Given its involvement in a neurodevelopmental disorder characterized by cerebellar hypoplasia/atrophy, epilepsy, and global developmental delay, Oxidation resistance protein 1 emerges as a key target for therapeutic intervention. Exploring its functions and mechanisms may lead to novel treatments for this and potentially other related diseases.

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