Focused On-demand Library for Kinesin-like protein KIF7

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 utilise our cutting-edge, exclusive workflow to develop focused libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive 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
Q2M1P5

UPID:
KIF7_HUMAN

ALTERNATIVE NAMES:
-

ALTERNATIVE UPACC:
Q2M1P5; Q3SXY0; Q6UXE9; Q8IW72

BACKGROUND:
The Kinesin-like protein KIF7 is integral to the hedgehog signaling pathway, serving as a regulator of sonic and Indian hedgehog pathways. It ensures proper ciliary function and microtubule organization, crucial for cell signaling and development. KIF7's regulatory capacity spans from preventing the activation of transcriptional activators in the absence of ligands to facilitating the correct processing of transcription factors, underlining its significance in cellular homeostasis.

THERAPEUTIC SIGNIFICANCE:
Mutations in KIF7 are implicated in several autosomal recessive syndromes, each characterized by distinct developmental and structural anomalies. These include Bardet-Biedl syndrome, characterized by retinopathy and obesity, and Joubert syndrome 12, known for cerebellar ataxia and psychomotor delay. The exploration of KIF7's functions and its involvement in these diseases offers a promising avenue for the development of targeted therapeutic strategies.

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