AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for RAC-beta serine/threonine-protein kinase

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 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

P31751

UPID:

AKT2_HUMAN

Alternative names:

Protein kinase Akt-2; Protein kinase B beta; RAC-PK-beta

Alternative UPACC:

P31751; B2RBD8; Q05BV0; Q0VAN0; Q0VAN1; Q68GC0

Background:

RAC-beta serine/threonine-protein kinase, also known as Protein kinase Akt-2, plays a pivotal role in cellular processes such as metabolism, proliferation, cell survival, growth, and angiogenesis. It achieves this through the phosphorylation of various substrates, including those involved in glucose uptake and glycogen storage, thereby regulating insulin signaling and glucose homeostasis.

Therapeutic significance:

Given its critical role in insulin signaling and glucose homeostasis, AKT2 is directly implicated in Type 2 diabetes mellitus and Hypoinsulinemic hypoglycemia with hemihypertrophy. Targeting AKT2's activity or its downstream effects presents a promising avenue for developing treatments for these metabolic disorders.

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