AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Cytoskeleton-associated protein 2-like

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner Reaxense.

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal 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 sreening 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.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

upacc

Q8IYA6

UPID:

CKP2L_HUMAN

Alternative names:

Radial fiber and mitotic spindle protein

Alternative UPACC:

Q8IYA6; A8K915; B4DZE3; B7ZAC6; F5H0M5; Q53QF8; Q53RS8; Q8N1J8

Background:

Cytoskeleton-associated protein 2-like, also known as Radial fiber and mitotic spindle protein, plays a crucial role in mitotic spindle formation and cell-cycle progression in neural progenitor cells. Its unique function underscores its importance in cellular division and neural development.

Therapeutic significance:

Linked to Filippi syndrome, a rare disorder with a spectrum of physical and cognitive manifestations, understanding the role of Cytoskeleton-associated protein 2-like could open doors to potential therapeutic strategies. Targeting this protein's pathway may offer insights into treating or managing the syndrome's complex symptoms.

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