Focused On-demand Library for Fizzy-related protein homolog

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 use our state-of-the-art dedicated workflow for designing focused libraries.

Fig. 1. The sreening 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.

Several key aspects differentiate our library:

Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

partner

Reaxense

upacc

Q9UM11

UPID:

FZR1_HUMAN

Alternative names:

CDC20-like protein 1; Cdh1/Hct1 homolog

Alternative UPACC:

Q9UM11; O75869; Q86U66; Q96NW8; Q9UI96; Q9ULH8; Q9UM10; Q9UNQ1; Q9Y2T8

Background:

Fizzy-related protein homolog, also known as CDC20-like protein 1 or Cdh1/Hct1 homolog, plays a pivotal role in cell cycle regulation. It acts as a substrate-specific adapter for the APC/C E3 ubiquitin-protein ligase complex, ensuring the timely degradation of cell cycle regulators. Its activity is crucial for the transition from mitosis to the G1 phase and for DNA damage response, particularly in promoting non-homologous end joining over homologous recombination.

Therapeutic significance:

The involvement of Fizzy-related protein homolog in Developmental and epileptic encephalopathy 109 highlights its potential as a therapeutic target. Understanding the role of this protein could open doors to potential therapeutic strategies for treating this severe neurological disorder.