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.


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.


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
P16157

UPID:
ANK1_HUMAN

ALTERNATIVE NAMES:
Ankyrin-R; Erythrocyte ankyrin

ALTERNATIVE UPACC:
P16157; A0PJN8; A6NJ23; E5RFL7; O43400; Q13768; Q53ER1; Q59FP2; Q8N604; Q99407

BACKGROUND:
The protein Ankyrin-1, with aliases Ankyrin-R and Erythrocyte ankyrin, is integral to the ankyrin-1 complex, ensuring erythrocyte membrane stability and morphology. It connects membrane proteins to the cytoskeleton, interacting with proteins such as band 4.2, Na-K ATPase, and spectrin, among others. Its function is crucial for maintaining the proper shape and functionality of erythrocytes.

THERAPEUTIC SIGNIFICANCE:
Linked to the severe form of Spherocytosis 1, Ankyrin-1's dysfunction results in chronic hemolytic anemia and abnormal erythrocyte shapes. Exploring Ankyrin-1's mechanisms offers a promising avenue for developing targeted treatments for Spherocytosis 1, emphasizing the importance of membrane protein interactions in erythrocyte stability.

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