Focused On-demand Libraries - Receptor.AI 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.


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.


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


Several key aspects differentiate our library:


  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.

  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.

  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.

  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.


PARTNER
Receptor.AI
 
UPACC
P07919

UPID:
QCR6_HUMAN

ALTERNATIVE NAMES:
Complex III subunit 6; Complex III subunit VIII; Cytochrome c1 non-heme 11 kDa protein; Mitochondrial hinge protein; Ubiquinol-cytochrome c reductase complex 11 kDa protein

ALTERNATIVE UPACC:
P07919; B2R4V9; D3DQ18; Q5TDF6; Q6LDB8; Q9BQ91

BACKGROUND:
The Cytochrome b-c1 complex subunit 6, a key player in the mitochondrial respiratory chain, is essential for energy production in cells. It is involved in the Q cycle, a process that contributes to the creation of an electrochemical gradient necessary for ATP synthesis. This protein's function underscores its importance in cellular metabolism and energy homeostasis.

THERAPEUTIC SIGNIFICANCE:
Given its critical role in mitochondrial function, Cytochrome b-c1 complex subunit 6's dysfunction is associated with Mitochondrial complex III deficiency, nuclear type 11. Targeting this protein could offer novel therapeutic avenues for treating mitochondrial diseases, highlighting the importance of further research into its mechanisms and potential drug targets.

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