Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.


We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by Reaxense.


The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.


Our high-tech, dedicated method is applied to construct targeted libraries.


 

Fig. 1. The screening 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 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
Q99972

UPID:
MYOC_HUMAN

ALTERNATIVE NAMES:
Myocilin 55 kDa subunit; Trabecular meshwork-induced glucocorticoid response protein

ALTERNATIVE UPACC:
Q99972; B2RD84; O00620; Q7Z6Q9

BACKGROUND:
The Myocilin protein, integral to cell-matrix adhesion and stress fiber assembly, influences the organization of the actin cytoskeleton and promotes osteoblast differentiation. Its role in ERBB2/ERBB3 signaling mediates myelination in the peripheral nervous system, and it is crucial for mitochondrial depolarization and fluid outflow in the trabecular meshwork.

THERAPEUTIC SIGNIFICANCE:
Linked to primary open angle glaucoma and primary congenital glaucoma, Myocilin's genetic variants affect the gene, leading to these eye diseases. The protein's association with glaucoma, a condition often asymptomatic until advanced stages, underscores the importance of Myocilin in developing new therapeutic approaches. Targeting Myocilin could revolutionize glaucoma treatment, emphasizing the need for further research into its functions and mechanisms.

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