Focused On-demand Library for Guanine nucleotide-binding protein-like 3

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.

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 is unique due to several crucial aspects:

Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

partner

Reaxense

upacc

Q9BVP2

UPID:

GNL3_HUMAN

Alternative names:

E2-induced gene 3 protein; Novel nucleolar protein 47; Nucleolar GTP-binding protein 3; Nucleostemin

Alternative UPACC:

Q9BVP2; B2RDC1; Q5PU80; Q96SV6; Q96SV7; Q9UJY0

Background:

Guanine nucleotide-binding protein-like 3, also known as Nucleostemin, plays a crucial role in maintaining the proliferative capacity of stem cells. It achieves this by stabilizing MDM2, preventing its ubiquitination and subsequent proteasomal degradation. This protein is alternatively known as E2-induced gene 3 protein, Novel nucleolar protein 47, and Nucleolar GTP-binding protein 3.

Therapeutic significance:

Understanding the role of Guanine nucleotide-binding protein-like 3 could open doors to potential therapeutic strategies.