Focused On-demand Library for Protein unc-119 homolog A

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 employ our advanced, specialised process to create targeted libraries.

Fig. 1. The sreening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse biological functions.

Our library stands out due to several important features:

The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

partner

Reaxense

upacc

Q13432

UPID:

U119A_HUMAN

Alternative names:

Retinal protein 4

Alternative UPACC:

Q13432; A8K8G4; F1T095; O95126

Background:

Protein unc-119 homolog A, also known as Retinal protein 4, plays a pivotal role in various cellular processes. It is essential for synaptic functions in photoreceptor cells, signal transduction in immune cells as a Src family kinase activator, endosome recycling, and the uptake of bacteria and endocytosis. This protein is crucial for protein trafficking in sensory neurons and acts as a lipid-binding chaperone for myristoylated proteins, facilitating their localization.

Therapeutic significance:

Immunodeficiency 13, a rare syndrome characterized by a significant reduction in CD4 T-lymphocyte count, is linked to mutations affecting Protein unc-119 homolog A. Understanding the role of this protein could open doors to potential therapeutic strategies for treating or managing this immunodeficiency.