AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for MOB-like protein phocein

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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.

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.

 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.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

upacc

Q9Y3A3

UPID:

PHOCN_HUMAN

Alternative names:

2C4D; Class II mMOB1; Mob1 homolog 3; Mps one binder kinase activator-like 3; Preimplantation protein 3

Alternative UPACC:

Q9Y3A3; B4DML0; Q53SE0; Q7Z4Y6; Q9H2P3; Q9H5J1; Q9Y4T8

Background:

MOB-like protein phocein, known by alternative names such as 2C4D and Mob1 homolog 3, is implicated in crucial cellular processes, including membrane trafficking and budding reactions. This protein's intricate involvement in cellular dynamics underscores its significance in maintaining cellular integrity and function.

Therapeutic significance:

Understanding the role of MOB-like protein phocein could open doors to potential therapeutic strategies. Its pivotal role in membrane dynamics positions it as a key target for modulating cellular processes, offering avenues for innovative treatments.

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