AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Kinesin-like protein KIF1B

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.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

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.

We employ our advanced, specialised process to create targeted libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse 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

O60333

UPID:

KIF1B_HUMAN

Alternative names:

-

Alternative UPACC:

O60333; A6NFS8; A6NKQ4; Q4VXC3; Q4VXC4; Q4VXC5; Q4VXC6; Q96Q94; Q9BV80; Q9P280

Background:

Kinesin-like protein KIF1B, encoded by the gene with accession number O60333, plays a pivotal role in the anterograde transport of mitochondria and synaptic vesicles within neuronal cells. Its activity is crucial for maintaining the proper function and distribution of mitochondria and synaptic vesicles, which are essential for neuronal health and signaling.

Therapeutic significance:

KIF1B is implicated in several diseases, including Charcot-Marie-Tooth disease, axonal, 2A1, a peripheral nervous system disorder; Neuroblastoma 1, a common early childhood neoplasm; and Pheochromocytoma, a tumor of the adrenal medulla. Understanding the role of Kinesin-like protein KIF1B could open doors to potential therapeutic strategies for these conditions.

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