Focused On-demand Library for Optineurin

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.


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.


Our high-tech, dedicated method is applied to construct 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 stands out due to several important features:


  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.

  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.

  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.

  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

PARTNER
Receptor.AI
 
UPACC
Q96CV9

UPID:
OPTN_HUMAN

ALTERNATIVE NAMES:
E3-14.7K-interacting protein; Huntingtin yeast partner L; Huntingtin-interacting protein 7; Huntingtin-interacting protein L; NEMO-related protein; Optic neuropathy-inducing protein; Transcription factor IIIA-interacting protein

ALTERNATIVE UPACC:
Q96CV9; B3KP00; D3DRS4; D3DRS8; Q5T672; Q5T673; Q5T674; Q5T675; Q7LDL9; Q8N562; Q9UET9; Q9UEV4; Q9Y218

BACKGROUND:
The protein Optineurin, with alternative names such as E3-14.7K-interacting protein and Huntingtin-interacting protein 7, plays a critical role in the maintenance of the Golgi complex, exocytosis, and the activation of the innate immune response. It acts as an autophagy receptor, targeting ubiquitin-coated bacteria, and may serve as a cellular target for viruses to inhibit innate immune responses. Its neuroprotective function in the eye and optic nerve is of significant interest.

THERAPEUTIC SIGNIFICANCE:
Given Optineurin's association with primary open angle glaucoma, normal pressure glaucoma, and amyotrophic lateral sclerosis 12, its study is crucial for drug discovery. The protein's involvement in these diseases suggests that targeting Optineurin could offer new therapeutic avenues, potentially leading to breakthrough treatments for patients with these conditions.

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