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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


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.


We employ our advanced, specialised process to create 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 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
P00338

UPID:
LDHA_HUMAN

ALTERNATIVE NAMES:
Cell proliferation-inducing gene 19 protein; LDH muscle subunit; Renal carcinoma antigen NY-REN-59

ALTERNATIVE UPACC:
P00338; B4DKQ2; B7Z5E3; D3DQY3; F8W819; Q53G53; Q6IBM7; Q6ZNV1; Q9UDE8; Q9UDE9

BACKGROUND:
L-lactate dehydrogenase A chain, alternatively known as Cell proliferation-inducing gene 19 protein, LDH muscle subunit, and Renal carcinoma antigen NY-REN-59, is essential for converting pyruvate to lactate while interchanging NADH with NAD(+). This enzymatic activity is crucial for maintaining cellular energy balance and responding to metabolic demands.

THERAPEUTIC SIGNIFICANCE:
The association of L-lactate dehydrogenase A chain with Glycogen storage disease 11, a disorder resulting from gene variants affecting this enzyme, underscores its potential as a therapeutic target. Exploring the enzyme's role could unveil new strategies for managing symptoms and improving the quality of life for affected individuals.

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