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.


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.


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


 

Fig. 1. The screening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.


Our library stands out due to several important features:


  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.

  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.

  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.

  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
O00189

UPID:
AP4M1_HUMAN

ALTERNATIVE NAMES:
AP-4 adaptor complex mu subunit; Adaptor-related protein complex 4 subunit mu-1; Mu subunit of AP-4; Mu-adaptin-related protein 2; Mu4-adaptin

ALTERNATIVE UPACC:
O00189; D6W5U1; Q8WV65; Q9UHK9

BACKGROUND:
The AP-4 complex subunit mu-1, known for its involvement in the adaptor protein complex 4 (AP-4), is pivotal in non-clathrin-associated vesicle formation departing the TGN. It ensures the precise targeting and sorting of proteins to the endosomal-lysosomal system and the basolateral membrane. Its role extends to the asymmetric localization of somatodendritic proteins in neurons, highlighting its significance in cellular function and protein trafficking.

THERAPEUTIC SIGNIFICANCE:
Given its association with Spastic paraplegia 50, a condition marked by progressive weakness and spasticity, the study of AP-4 complex subunit mu-1 holds promise for uncovering novel therapeutic avenues. Understanding its function and involvement in disease mechanisms could lead to breakthroughs in treatment strategies.

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