AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Tyrosine-protein phosphatase non-receptor type 12

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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.

We employ our advanced, specialised process to create targeted libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost 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

Q05209

UPID:

PTN12_HUMAN

Alternative names:

PTP-PEST; Protein-tyrosine phosphatase G1

Alternative UPACC:

Q05209; A4D1C5; B4DKY2; E9PBR5; E9PEH9; Q16130; Q59FD6; Q75MN8; Q86XU4

Background:

Tyrosine-protein phosphatase non-receptor type 12, also known as PTP-PEST and Protein-tyrosine phosphatase G1, plays a pivotal role in cellular signaling by dephosphorylating a variety of proteins. It specifically targets cellular tyrosine kinases like ERBB2 and PTK2B/PYK2, crucial for signaling pathways. This protein selectively dephosphorylates ERBB2 at key tyrosine residues, influencing cellular processes.

Therapeutic significance:

Understanding the role of Tyrosine-protein phosphatase non-receptor type 12 could open doors to potential therapeutic strategies. Its ability to regulate key signaling pathways by dephosphorylation makes it a significant target for drug discovery, aiming to modulate cellular functions and address diseases with dysregulated signaling.

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