AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Kinesin-like protein KIF1C

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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. Our collaborator, Reaxense, aids in their synthesis and provision.

The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

We use our state-of-the-art dedicated workflow for designing focused libraries.

 Fig. 1. The sreening 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 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

Reaxense

upacc

O43896

UPID:

KIF1C_HUMAN

Alternative names:

-

Alternative UPACC:

O43896; D3DTL6; O75186; Q5U618

Background:

Kinesin-like protein KIF1C plays a pivotal role in cellular transport mechanisms, specifically in the retrograde transport of Golgi vesicles to the endoplasmic reticulum. Its unique motor function, driven by microtubule plus end-directed motility, is crucial for maintaining cellular homeostasis and proper organelle distribution.

Therapeutic significance:

KIF1C's involvement in Spastic ataxia 2, an autosomal recessive neurologic disorder, underscores its potential as a therapeutic target. Understanding the role of Kinesin-like protein KIF1C could open doors to potential therapeutic strategies for treating this debilitating condition without affecting cognitive functions.

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