Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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 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.


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


 

Fig. 1. The screening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage activity and selectivity.


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
Q15800

UPID:
MSMO1_HUMAN

ALTERNATIVE NAMES:
C-4 methylsterol oxidase; Sterol-C4-methyl oxidase

ALTERNATIVE UPACC:
Q15800; A8K8Q3; A8MYF6; D3DP32; Q32Q24

BACKGROUND:
Methylsterol monooxygenase 1, identified by its alternative names C-4 methylsterol oxidase and Sterol-C4-methyl oxidase, is pivotal in cholesterol biosynthesis. It efficiently demethylates specific sterols, a necessary step for their conversion into cholesterol, essential for cellular health and hormone synthesis. Its ability to metabolize eldecalcitol into active vitamin D forms further demonstrates its significant biochemical capabilities and impact on human health.

THERAPEUTIC SIGNIFICANCE:
Given its critical function in cholesterol metabolism and the development of congenital disorders like Microcephaly, congenital cataract, and psoriasiform dermatitis, Methylsterol monooxygenase 1 emerges as a key target in drug discovery. Exploring its mechanisms offers a promising avenue for developing novel therapies for metabolic diseases and improving outcomes for affected individuals.

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