Focused On-demand Library for Folliculin-interacting protein 2

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.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner Reaxense.

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

We use our state-of-the-art dedicated workflow for designing focused 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.

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

Q9P278

UPID:

FNIP2_HUMAN

Alternative names:

FNIP1-like protein; O6-methylguanine-induced apoptosis 1 protein

Alternative UPACC:

Q9P278; Q05DC3; Q96I31; Q9H994

Background:

Folliculin-interacting protein 2, also known as FNIP1-like protein or O6-methylguanine-induced apoptosis 1 protein, plays a pivotal role in cellular response to amino acid availability. It regulates the mTORC1 signaling cascade, influencing the activity of MiT/TFE factors TFEB and TFE3. This protein is crucial in the lysosomal folliculin complex, affecting mTORC1 activity and autophagy through its interaction with GABARAP. Additionally, it serves as a co-chaperone of HSP90AA1/Hsp90, modulating its ATPase activity and client protein interaction.

Therapeutic significance:

Understanding the role of Folliculin-interacting protein 2 could open doors to potential therapeutic strategies.