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

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

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.

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

 Fig. 1. The sreening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast 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

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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