Focused On-demand Libraries - Receptor.AI 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. Reaxense aids in their synthesis and provision.


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.


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


 

Fig. 1. The screening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.


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
Receptor.AI
 
UPACC
O95057

UPID:
DIRA1_HUMAN

ALTERNATIVE NAMES:
Distinct subgroup of the Ras family member 1; Ras-related inhibitor of cell growth; Small GTP-binding tumor suppressor 1

ALTERNATIVE UPACC:
O95057

BACKGROUND:
The GTP-binding protein Di-Ras1, with alternative names such as Distinct subgroup of the Ras family member 1, Ras-related inhibitor of cell growth, and Small GTP-binding tumor suppressor 1, exhibits low GTPase activity, primarily existing in its GTP-bound state. This protein's function as a molecular switch, cycling between active and inactive forms, is vital for the regulation of various cellular activities.

THERAPEUTIC SIGNIFICANCE:
Exploring the function of GTP-binding protein Di-Ras1 holds promise for identifying novel therapeutic approaches. Its pivotal role in cellular signaling pathways presents an opportunity for the development of drugs aimed at precisely modulating its activity, offering potential benefits in disease treatment.

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