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 top-notch dedicated system is used to design specialised 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 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
Q66K64

UPID:
DCA15_HUMAN

ALTERNATIVE NAMES:
-

ALTERNATIVE UPACC:
Q66K64; B3KS86; Q96DW0; Q9BU31

BACKGROUND:
The DDB1- and CUL4-associated factor 15 (DCAF15) is a key component of the DCX complex, a cullin-4-RING E3 ubiquitin-protein ligase complex essential for protein ubiquitination and degradation. DCAF15 regulates natural killer (NK) cell functions and may play a role in APC activation and NK cell interaction, through the targeted degradation of specific cohesin subunits.

THERAPEUTIC SIGNIFICANCE:
The therapeutic potential of DDB1- and CUL4-associated factor 15 lies in its critical role in cellular regulation and interaction with aryl sulfonamide anticancer drugs. These drugs shift DCAF15's activity towards the degradation of splicing factors such as RBM39, RBM23, and PRPF39, causing lethal splicing defects in cancer cells. This mechanism offers a promising avenue for the development of novel cancer treatments.

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