Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved activity, selectivity, and safety.


We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are 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 use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage 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
P09104

UPID:
ENOG_HUMAN

ALTERNATIVE NAMES:
2-phospho-D-glycerate hydro-lyase; Enolase 2; Neural enolase; Neuron-specific enolase

ALTERNATIVE UPACC:
P09104; B7Z2X9; Q96J33

BACKGROUND:
Gamma-enolase, known for its critical functions in the CNS, supports neuron survival and health. This protein, with alternative names such as Neural enolase and Neuron-specific enolase, binds to neurons in a calcium-dependent manner, showcasing its neuroprotective and neurotrophic effects. Its involvement in neuronal development underscores its importance in maintaining neural function.

THERAPEUTIC SIGNIFICANCE:
The exploration of Gamma-enolase's functions presents a promising pathway for developing therapeutic strategies. Its neuroprotective properties highlight its potential in addressing neurodegenerative conditions, making it a target of interest in the quest for novel treatments.

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