AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Protein tyrosine phosphatase type IVA 2

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 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.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

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

 Fig. 1. The sreening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance 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

Q12974

UPID:

TP4A2_HUMAN

Alternative names:

HU-PP-1; OV-1; PTP(CAAXII); Protein-tyrosine phosphatase 4a2; Protein-tyrosine phosphatase of regenerating liver 2

Alternative UPACC:

Q12974; A8K9I8; B4DM39; D3DPP0; E9PGJ6; O00649; Q15197; Q15259; Q15260; Q15261; R4GN50

Background:

Protein tyrosine phosphatase type IVA 2, known by alternative names such as HU-PP-1, OV-1, and PTP(CAAXII), plays a pivotal role in cell cycle progression, specifically facilitating the transition from G1 to S phase during mitosis. Its activity is characterized by the inhibition of geranylgeranyl transferase type II, impacting the association between RABGGTA and RABGGTB, which is crucial for tumor promotion.

Therapeutic significance:

Understanding the role of Protein tyrosine phosphatase type IVA 2 could open doors to potential therapeutic strategies, particularly in the realm of cancer treatment where its tumor-promoting activities are evident.

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