AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for STE20-like serine/threonine-protein kinase

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.

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.

We use our state-of-the-art dedicated workflow for designing focused 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 stands out due to several important features:

  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

partner

Reaxense

upacc

Q9H2G2

UPID:

SLK_HUMAN

Alternative names:

CTCL tumor antigen se20-9; STE20-related serine/threonine-protein kinase; Serine/threonine-protein kinase 2

Alternative UPACC:

Q9H2G2; D3DRA0; D3DRA1; O00211; Q6P1Z4; Q86WU7; Q86WW1; Q92603; Q9NQL0; Q9NQL1

Background:

The STE20-like serine/threonine-protein kinase, also known as CTCL tumor antigen se20-9, STE20-related serine/threonine-protein kinase, and Serine/threonine-protein kinase 2, plays a crucial role in mediating apoptosis and the dissolution of actin stress fibers. This protein's unique functions highlight its importance in cellular processes and signal transduction pathways.

Therapeutic significance:

Understanding the role of STE20-like serine/threonine-protein kinase could open doors to potential therapeutic strategies. Its involvement in apoptosis and actin stress fiber dissolution positions it as a key target for drug discovery efforts aimed at regulating cell death and cytoskeletal organization.

Looking for more information on this library or underlying technology? Fill out the form below and we'll be in touch with all the details you need.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
No Spam. Cancel Anytime.