Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced 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.


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

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
Receptor.AI
 
UPACC
Q9Y496

UPID:
KIF3A_HUMAN

ALTERNATIVE NAMES:
Microtubule plus end-directed kinesin motor 3A

ALTERNATIVE UPACC:
Q9Y496; A8MSW9; Q59EN1; Q86XE9; Q9Y6V4

BACKGROUND:
The Kinesin-like protein KIF3A, alternatively named Microtubule plus end-directed kinesin motor 3A, plays a crucial role in the intracellular transport system. Its functions include facilitating the anterograde translocation of membranous organelles along microtubules, contributing to primary cilia formation, and ensuring the proper organization and function of centrioles and subdistal appendages. This protein's involvement in the recruitment of DCTN1 for subdistal appendage formation and in establishing ciliary basal feet formation is vital for cellular architecture and function.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Kinesin-like protein KIF3A could open doors to potential therapeutic strategies.

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