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.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated 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 employ our advanced, specialised process to create targeted libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide 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
Q96BR5

UPID:
COA7_HUMAN

ALTERNATIVE NAMES:
Beta-lactamase hcp-like protein; Respiratory chain assembly factor 1; Sel1 repeat-containing protein 1

ALTERNATIVE UPACC:
Q96BR5; Q0P6I7; Q9H9Z9

BACKGROUND:
The protein Cytochrome c oxidase assembly factor 7, known under various names including Beta-lactamase hcp-like protein, is essential for mitochondrial respiratory chain complexes I and IV assembly. Its function is critical for the maintenance of cellular energy metabolism and mitochondrial integrity.

THERAPEUTIC SIGNIFICANCE:
Linked to Spinocerebellar ataxia, autosomal recessive, with axonal neuropathy 3, Cytochrome c oxidase assembly factor 7's mutations manifest in neurological degeneration. The exploration of this protein's function offers a promising avenue for developing novel therapeutic interventions for related neurodegenerative conditions.

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