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.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best 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

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 distinguishes itself through several key aspects:


  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.

  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.

  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.

  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
Q16795

UPID:
NDUA9_HUMAN

ALTERNATIVE NAMES:
Complex I-39kD; NADH-ubiquinone oxidoreductase 39 kDa subunit

ALTERNATIVE UPACC:
Q16795; Q14076; Q2NKX0

BACKGROUND:
The protein NADH dehydrogenase [ubiquinone] 1 alpha subcomplex subunit 9, mitochondrial, known alternatively as Complex I-39kD or NADH-ubiquinone oxidoreductase 39 kDa subunit, is integral to mitochondrial function. It is not directly involved in catalysis but is required for the assembly of Complex I, which facilitates electron transfer from NADH to ubiquinone in the respiratory chain.

THERAPEUTIC SIGNIFICANCE:
Linked to Mitochondrial complex I deficiency, nuclear type 26, this protein's dysfunction manifests in a wide range of clinical disorders, including neurodegenerative diseases and cardiomyopathy, affecting approximately 1 in 5-10000 live births. Targeting this protein's pathway offers a promising avenue for developing treatments for these mitochondrial disorders.

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