AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Intraflagellar transport protein 52 homolog

Available from Reaxense
Predicted by Alphafold

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.

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 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 distinguishes itself through several key aspects:

  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.

partner

Reaxense

upacc

Q9Y366

UPID:

IFT52_HUMAN

Alternative names:

Protein NGD5 homolog

Alternative UPACC:

Q9Y366; B3KMA1; E1P5W9; Q5H8Z0; Q9H1G3; Q9H1G4; Q9H1H2

Background:

Intraflagellar transport protein 52 homolog (IFT52), also known as Protein NGD5 homolog, plays a crucial role in ciliogenesis. It is part of a complex involved in intraflagellar transport (IFT), essential for the assembly, maintenance, and functioning of primary cilia. IFT52 facilitates the anterograde transport of IFT88, a process critical for ciliary biogenesis and function.

Therapeutic significance:

IFT52 is linked to Short-rib thoracic dysplasia 16 with or without polydactyly, a condition characterized by skeletal abnormalities and potential non-skeletal involvement. Understanding the role of IFT52 could open doors to potential therapeutic strategies for this and related ciliopathies.

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