AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Ras-related protein M-Ras

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.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

We utilise our cutting-edge, exclusive workflow to develop focused libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost 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

O14807

UPID:

RASM_HUMAN

Alternative names:

Ras-related protein R-Ras3

Alternative UPACC:

O14807; B4DIK0; Q86WX8

Background:

Ras-related protein M-Ras, also known as R-Ras3, plays a pivotal role in cell signaling pathways. It is an essential signal transducer that activates the MAP kinase pathway, a critical mechanism in controlling cell proliferation. This protein's involvement in such fundamental cellular processes underscores its importance in biological systems.

Therapeutic significance:

Noonan syndrome 11, characterized by a spectrum of physical and developmental anomalies, is directly linked to variants affecting the Ras-related protein M-Ras gene. Given its crucial role in this condition, targeting M-Ras could offer a novel therapeutic approach for managing Noonan syndrome 11 and potentially other related disorders.

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