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.


We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.


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


 

Fig. 1. The screening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize 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
P11310

UPID:
ACADM_HUMAN

ALTERNATIVE NAMES:
Medium chain acyl-CoA dehydrogenase

ALTERNATIVE UPACC:
P11310; Q5T4U4; Q9NYF1

BACKGROUND:
The mitochondrial enzyme, Medium-chain specific acyl-CoA dehydrogenase (MCAD), is crucial for breaking down fatty acids into acetyl-CoA, facilitating energy production. Acting on 6 to 12 carbon long saturated fatty acyl-CoAs, MCAD's activity is essential for the first step of fatty acid beta-oxidation, highlighting its role in metabolic processes.

THERAPEUTIC SIGNIFICANCE:
Deficiencies in MCAD activity due to genetic mutations result in acyl-CoA dehydrogenase medium-chain deficiency, characterized by fasting hypoglycemia and severe metabolic complications. The exploration of MCAD's mechanisms and its impact on mitochondrial fatty acid metabolism is vital for devising novel therapeutic strategies for affected individuals.

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