AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Ras-like protein family member 12

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 top-notch dedicated system is used to design specialised libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage activity and selectivity.

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

Q9NYN1

UPID:

RASLC_HUMAN

Alternative names:

Ras-like protein Ris

Alternative UPACC:

Q9NYN1; B2RC29; B4DJW2; B4DU82

Background:

The Ras-like protein family member 12, also known as Ras-like protein Ris, is a pivotal component of cellular signaling pathways. Its role, although not fully delineated, is crucial for the regulation of cell division, growth, and differentiation. The protein's unique structure and alternative names highlight its significance in cellular functions.

Therapeutic significance:

Understanding the role of Ras-like protein family member 12 could open doors to potential therapeutic strategies. Its involvement in key cellular processes makes it a promising target for drug discovery, aiming to modulate its activity for therapeutic benefits.

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