Focused On-demand Library for ATP-binding cassette sub-family F member 3

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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 utilise our cutting-edge, exclusive workflow to develop focused 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 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

Q9NUQ8

UPID:

ABCF3_HUMAN

Alternative names:

Alternative UPACC:

Q9NUQ8; A8K241; Q86UA2; Q8NAN1; Q96GS8; Q9H7A8

Background:

ATP-binding cassette sub-family F member 3 (ABCF3) is a protein known for its role in cellular processes, particularly in mediating resistance to various pathogens. It has been identified to display an antiviral effect against flaviviruses, including the West Nile virus (WNV), in synergy with OAS1B. This protein is part of the ATP-binding cassette (ABC) transporters, a large family of proteins that play critical roles in the transport of molecules across extracellular and intracellular membranes.

Therapeutic significance:

Understanding the role of ATP-binding cassette sub-family F member 3 could open doors to potential therapeutic strategies. Its antiviral activity, especially against flaviviruses, highlights its potential as a target for developing antiviral therapies. The exploration of ABCF3's mechanisms and interactions could lead to novel interventions for viral infections.