Focused On-demand Library for Intraflagellar transport protein 27 homolog

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 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.

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

Q9BW83

UPID:

IFT27_HUMAN

Alternative names:

Putative GTP-binding protein RAY-like; Rab-like protein 4

Alternative UPACC:

Q9BW83; O60897

Background:

Intraflagellar transport protein 27 homolog (IFT27), also known as Putative GTP-binding protein RAY-like and Rab-like protein 4, plays a crucial role in ciliary function. It is a component of the intraflagellar transport (IFT) complex B, essential for cilia exit of the BBSome complex, hedgehog signaling, and sperm flagella formation. IFT27's involvement in kidney and testis development highlights its importance in cellular structures rich in ciliated cells.

Therapeutic significance:

IFT27's association with Bardet-Biedl syndrome 19, a genetic disorder characterized by severe symptoms including pigmentary retinopathy and obesity, underscores its therapeutic potential. Understanding the role of IFT27 could open doors to potential therapeutic strategies for this syndrome and related ciliopathies.