Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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 use our state-of-the-art dedicated workflow for designing focused libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse 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
Q8IYA6

UPID:
CKP2L_HUMAN

ALTERNATIVE NAMES:
Radial fiber and mitotic spindle protein

ALTERNATIVE UPACC:
Q8IYA6; A8K915; B4DZE3; B7ZAC6; F5H0M5; Q53QF8; Q53RS8; Q8N1J8

BACKGROUND:
The protein Cytoskeleton-associated protein 2-like, alternatively named Radial fiber and mitotic spindle protein, is essential for the assembly of mitotic spindles and the progression of the cell cycle in neural progenitor cells. This indicates its pivotal role in cell division and the development of the nervous system.

THERAPEUTIC SIGNIFICANCE:
Given its association with Filippi syndrome, characterized by developmental anomalies and neurological issues, the study of Cytoskeleton-associated protein 2-like presents a promising avenue for therapeutic intervention. Exploring its function and mechanisms may lead to novel treatments for this and potentially other related disorders.

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