Focused On-demand Library for ADP-ribosylation factor-like protein 4C

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 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.

Our top-notch dedicated system is used to design specialised libraries.

Fig. 1. The sreening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of biological functions.

Key features that set our library apart include:

The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

upacc

P56559

UPID:

ARL4C_HUMAN

Alternative names:

ADP-ribosylation factor-like protein 7; ADP-ribosylation factor-like protein LAK

Alternative UPACC:

P56559; Q4A519; Q53R10; Q9BVN1; Q9UQ34

Background:

ADP-ribosylation factor-like protein 4C (ARL4C) is a small GTP-binding protein that transitions between inactive GDP-bound and active GTP-bound forms. This cycling is regulated by guanine nucleotide exchange factors (GEF) and GTPase-activating proteins (GAP). ARL4C is involved in transport processes between perinuclear compartments and the plasma membrane, particularly in the ABCA1-mediated cholesterol secretion pathway. It also plays a role in recruiting CYTH family members to the plasma membrane and regulates microtubule-dependent vesicular transport.

Therapeutic significance:

Understanding the role of ADP-ribosylation factor-like protein 4C could open doors to potential therapeutic strategies.