Focused On-demand Library for Cell division cycle-associated protein 7

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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.

The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

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

Q9BWT1

UPID:

CDCA7_HUMAN

Alternative names:

Protein JPO1

Alternative UPACC:

Q9BWT1; B4DLP8; B4DV66; Q53EW5; Q580W9; Q658K4; Q658N4; Q8NBY9; Q96BV8; Q96SP5

Background:

Cell division cycle-associated protein 7, also known as Protein JPO1, plays a pivotal role in MYC-mediated cell transformation and apoptosis. It promotes anchorage-independent growth and enhances clonogenicity in lymphoblastoid cells. While not directly tumorigenic when overexpressed, it significantly contributes to MYC-mediated tumorigenesis and may act as a transcriptional regulator.

Therapeutic significance:

The protein is linked to Immunodeficiency-centromeric instability-facial anomalies syndrome 3, a rare disorder with symptoms including recurrent infections and growth retardation. Understanding the role of Cell division cycle-associated protein 7 could open doors to potential therapeutic strategies for this syndrome.