Focused On-demand Library for Protein MEMO1

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.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

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 high-tech, dedicated method is applied to construct targeted libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse biological functions.

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.







Alternative names:

C21orf19-like protein; Hepatitis C virus NS5A-transactivated protein 7; Mediator of ErbB2-driven cell motility 1

Alternative UPACC:

Q9Y316; B4DLS0; D6W575; Q5R2V8; Q5R2V9; Q6NSL5


Protein MEMO1, also known as C21orf19-like protein, Hepatitis C virus NS5A-transactivated protein 7, and Mediator of ErbB2-driven cell motility 1, plays a pivotal role in cell migration. It acts by transmitting extracellular chemotactic signals to the microtubule cytoskeleton, primarily through the MEMO1-RHOA-DIAPH1 signaling pathway. This pathway is crucial for ERBB2-dependent microtubule stabilization at the cell cortex, influencing the localization of APC, CLASP2, and MACF1, which are essential for microtubule capture and stabilization.

Therapeutic significance:

Understanding the role of Protein MEMO1 could open doors to potential therapeutic strategies.

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