Focused On-demand Library for KIF-binding protein

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.


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 screening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse 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
Receptor.AI
 
UPACC
Q96EK5

UPID:
KBP_HUMAN

ALTERNATIVE NAMES:
KIF1-binding protein; Kinesin family binding protein

ALTERNATIVE UPACC:
Q96EK5; A8K5M8; Q9BR89; Q9ULE1; Q9Y428

BACKGROUND:
The KIF-binding protein, alternatively known as Kinesin family binding protein, is required for the proper organization of axonal microtubules. Its function is pivotal for axonal outgrowth and the maintenance of neural pathways in both the peripheral and central nervous system.

THERAPEUTIC SIGNIFICANCE:
Linked to Goldberg-Shprintzen syndrome, characterized by intellectual disability and microcephaly, the KIF-binding protein's gene variants play a significant role. Exploring the functions of KIF-binding protein offers a promising avenue for developing therapeutic interventions for this condition.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.


Page 39 of 8789