Focused On-demand Library for Notch homolog 2 N-terminal-like protein C

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.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate Reaxense.

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.

Our high-tech, dedicated method is applied to construct targeted 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.

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

P0DPK4

UPID:

NT2NC_HUMAN

Alternative names:

Alternative UPACC:

P0DPK4; A0A494C1K9

Background:

Notch homolog 2 N-terminal-like protein C plays a pivotal role in brain development by regulating the Notch signaling pathway. It promotes neural progenitor proliferation, contributing to the evolutionary expansion of the brain neocortex. This protein enhances Notch signaling both directly, through interaction with NOTCH2, and indirectly, by inhibiting cis DLL1-NOTCH2 interactions, thus delaying neuronal differentiation.

Therapeutic significance:

Linked to diseases such as Neuronal intranuclear inclusion disease, hereditary essential tremor 6, and oculopharyngodistal myopathy 3, understanding the role of Notch homolog 2 N-terminal-like protein C could open doors to potential therapeutic strategies. Its involvement in these conditions highlights its importance in neural function and disease.