AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Kinesin-like protein KIF21A

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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. Our partner 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.

Our top-notch dedicated system is used to design specialised libraries.

 Fig. 1. The sreening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast 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

Q7Z4S6

UPID:

KI21A_HUMAN

Alternative names:

Kinesin-like protein KIF2; Renal carcinoma antigen NY-REN-62

Alternative UPACC:

Q7Z4S6; A8MX28; B0I1R9; B9EGE4; F5H0C3; F5H219; Q2UVF1; Q6UKL9; Q7Z668; Q86WZ5; Q8IVZ8; Q9C0F5; Q9NXU4; Q9Y590

Background:

Kinesin-like protein KIF21A, also known as Kinesin-like protein KIF2 and Renal carcinoma antigen NY-REN-62, is a microtubule-binding motor protein. It plays a crucial role in neuronal axonal transport, moving along microtubules with a plus-end directed motor activity. This protein's function is vital for the proper functioning of neuronal cells.

Therapeutic significance:

KIF21A is implicated in congenital fibrosis of extraocular muscles type 1, a disorder characterized by restrictive ophthalmoplegia, ptosis, and backward tilt of the head. Understanding the role of Kinesin-like protein KIF21A could open doors to potential therapeutic strategies for this and related ocular motility disorders.

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