AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for MOB kinase activator 3C

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 pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate 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.

We use our state-of-the-art dedicated workflow for designing focused libraries.

 Fig. 1. The sreening 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

Reaxense

upacc

Q70IA8

UPID:

MOB3C_HUMAN

Alternative names:

Mob1 homolog 2C; Mps one binder kinase activator-like 2C

Alternative UPACC:

Q70IA8; D3DQ22; Q0VA98; Q5TC10; Q5TC11; Q8NAZ2; Q8NF28

Background:

MOB kinase activator 3C, also known as Mob1 homolog 2C or Mps one binder kinase activator-like 2C, plays a crucial role in cellular processes by potentially regulating the activity of kinases. This protein, identified by the accession number Q70IA8, is a pivotal component in the signaling pathways that govern cell proliferation, differentiation, and survival.

Therapeutic significance:

Understanding the role of MOB kinase activator 3C could open doors to potential therapeutic strategies. Its involvement in kinase regulation suggests a significant impact on cellular functions, making it a promising target for drug discovery efforts aimed at treating diseases with dysregulated cell signaling.

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