AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Probable phospholipid-transporting ATPase IIA

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.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate 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 for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.

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

O75110

UPID:

ATP9A_HUMAN

Alternative names:

ATPase class II type 9A

Alternative UPACC:

O75110; E1P5Y3; E1P5Y4; Q5TFW5; Q5TFW6; Q5TFW9; Q6ZMF3; Q9NQK6; Q9NQK7

Background:

The Probable phospholipid-transporting ATPase IIA, also known as ATPase class II type 9A, is pivotal in regulating membrane trafficking, including endosome to plasma membrane recycling and endosome to trans-Golgi network retrograde transport. It activates RAB5 and RAB11, and in complex with MON2 and DOP1B, it oversees SNX3 retromer-mediated endosomal sorting of WLS, crucial for Wnt morphogen transport in development. Additionally, it plays a role in intercellular communication by modulating exosome release and is essential for maintaining neurite morphology and synaptic transmission.

Therapeutic significance:

Linked to a neurodevelopmental disorder characterized by developmental delay, intellectual impairment, and behavioral abnormalities, understanding the role of Probable phospholipid-transporting ATPase IIA could open doors to potential therapeutic strategies.

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