AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Intraflagellar transport protein 57 homolog

Available from Reaxense
Predicted by Alphafold

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.

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.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

Our high-tech, dedicated method is applied to construct targeted 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.

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

Q9NWB7

UPID:

IFT57_HUMAN

Alternative names:

Dermal papilla-derived protein 8; Estrogen-related receptor beta-like protein 1; HIP1-interacting protein; MHS4R2

Alternative UPACC:

Q9NWB7; Q96DA9

Background:

Intraflagellar transport protein 57 homolog (IFT57) plays a pivotal role in cilia formation and sonic hedgehog signaling, essential for cellular communication and development. It interacts with HIP1 to induce apoptosis and may regulate transcription of caspase genes, highlighting its multifunctionality. Known by alternative names such as Dermal papilla-derived protein 8 and Estrogen-related receptor beta-like protein 1, IFT57's complexity is underscored by its DNA-binding capability.

Therapeutic significance:

IFT57's involvement in Orofaciodigital syndrome 18, characterized by distinct facial and digital malformations, underscores its therapeutic potential. Understanding IFT57's role could open doors to innovative treatments for this and possibly other ciliopathies, leveraging its fundamental biological functions.

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