Focused On-demand Library for Neuroepithelial cell-transforming gene 1 protein

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner Reaxense.

The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

We utilise our cutting-edge, exclusive workflow to develop focused 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.

Our library distinguishes itself through several key aspects:

The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.

partner

Reaxense

upacc

Q7Z628

UPID:

ARHG8_HUMAN

Alternative names:

Proto-oncogene p65 Net1; Rho guanine nucleotide exchange factor 8

Alternative UPACC:

Q7Z628; Q12773; Q96D82; Q99903; Q9UEN6

Background:

Neuroepithelial cell-transforming gene 1 protein, also known as Proto-oncogene p65 Net1 and Rho guanine nucleotide exchange factor 8, plays a crucial role in cellular processes. It acts as a guanine nucleotide exchange factor (GEF) for RhoA GTPase, pivotal in the activation of the SAPK/JNK pathway. This protein is instrumental in stimulating genotoxic stress-induced RHOB activity in breast cancer cells, leading to cell death.

Therapeutic significance:

Understanding the role of Neuroepithelial cell-transforming gene 1 protein could open doors to potential therapeutic strategies. Its involvement in critical pathways and cell death mechanisms in cancer cells highlights its potential as a target for innovative cancer therapies.