AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Lipoxygenase homology domain-containing 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.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner Reaxense.

The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

Our top-notch dedicated system is used to design specialised libraries.

 Fig. 1. The sreening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast 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

Q8IVV2

UPID:

LOXH1_HUMAN

Alternative names:

-

Alternative UPACC:

Q8IVV2; B7WNN3; B7WNT1; B7WPI9; H7BZ41; Q6ZRY7; Q86WW9; Q96DL7

Background:

Lipoxygenase homology domain-containing protein 1 plays a pivotal role in auditory processes, essential for the normal functioning of hair cells in the inner ear. This protein's involvement is crucial for maintaining the integrity of auditory mechanisms, facilitating sound wave transduction into neural signals.

Therapeutic significance:

Deafness, autosomal recessive, 77, a condition marked by progressive hearing loss, is directly linked to mutations in the gene encoding this protein. Understanding the role of Lipoxygenase homology domain-containing protein 1 could open doors to potential therapeutic strategies, offering hope for individuals affected by this form of hearing impairment.

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