AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Kinesin-like protein KIF13A

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

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.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

Our high-tech, dedicated method is applied to construct targeted 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.

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

Q9H1H9

UPID:

KI13A_HUMAN

Alternative names:

Kinesin-like protein RBKIN

Alternative UPACC:

Q9H1H9; A0JP21; A0JP22; F2Z382; Q5THQ2; Q5THQ3; Q9H193; Q9H194; Q9H1H8

Background:

Kinesin-like protein KIF13A, also known as RBKIN, is a microtubule-dependent motor protein crucial for intracellular transport. It plays a pivotal role in processes such as mannose-6-phosphate receptor transport to the plasma membrane, endosomal sorting during melanosome biogenesis, and cytokinesis. KIF13A facilitates the movement of M6PR-containing vesicles from the trans-Golgi network to the plasma membrane and is essential for melanosome maturation and cytokinesis.

Therapeutic significance:

Understanding the role of Kinesin-like protein KIF13A could open doors to potential therapeutic strategies.

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