AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Tyrosine-protein kinase ABL1

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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.

The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

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

P00519

UPID:

ABL1_HUMAN

Alternative names:

Abelson murine leukemia viral oncogene homolog 1; Abelson tyrosine-protein kinase 1; Proto-oncogene c-Abl; p150

Alternative UPACC:

P00519; A3KFJ3; Q13869; Q13870; Q16133; Q17R61; Q45F09

Background:

Tyrosine-protein kinase ABL1, known as Abelson murine leukemia viral oncogene homolog 1, plays a pivotal role in cell growth, survival, and apoptosis. It is involved in cytoskeleton remodeling, cell motility, receptor endocytosis, and DNA damage response. ABL1's ability to phosphorylate various substrates underlines its significance in cellular signaling pathways.

Therapeutic significance:

ABL1's involvement in chronic myeloid leukemia, due to the Philadelphia chromosome abnormality, and its role in congenital heart defects and skeletal malformations syndrome, highlight its therapeutic potential. Targeting ABL1 could lead to innovative treatments for these conditions.

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