AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Rho GTPase-activating protein 15

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.

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 includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

We use our state-of-the-art dedicated workflow for designing focused libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of biological functions.

Our library is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

partner

Reaxense

upacc

Q53QZ3

UPID:

RHG15_HUMAN

Alternative names:

ArhGAP15; Rho-type GTPase-activating protein 15

Alternative UPACC:

Q53QZ3; Q53R36; Q53RD7; Q53RT6; Q53SX9; Q584N9; Q6PJE6; Q86WP1; Q8IXX1; Q9NRL8; Q9NZ77; Q9NZ91

Background:

Rho GTPase-activating protein 15, known as ArhGAP15, plays a pivotal role in cellular processes by acting as a GTPase activator for Rho-type GTPases, transitioning them to an inactive GDP-bound state. It specifically targets RAC1, leading to an increase in actin stress fibers and cell contraction. This protein's activity is crucial for the regulation of cell morphology and motility.

Therapeutic significance:

Understanding the role of Rho GTPase-activating protein 15 could open doors to potential therapeutic strategies. Its involvement in the regulation of actin cytoskeleton and cell motility positions it as a key target for interventions in diseases where these processes are dysregulated.

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