AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for MORC family CW-type zinc finger protein 3

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.

The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

Our high-tech, dedicated method is applied to construct targeted 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

Q14149

UPID:

MORC3_HUMAN

Alternative names:

Nuclear matrix protein 2; Zinc finger CW-type coiled-coil domain protein 3

Alternative UPACC:

Q14149; A8KA92; Q9UEZ2

Background:

MORC family CW-type zinc finger protein 3, also known as Nuclear matrix protein 2, plays a pivotal role in innate immunity by modulating the interferon response to restrict various viruses. It forms MORC3-NBs through an ATP-dependent mechanism, associates with PML-NBs, and recruits TP53 and SP100, thereby regulating TP53 activity. Additionally, it acts as a histone methylation reader, showing preference for different methylated states of 'Lys-4' on histone H3.

Therapeutic significance:

Understanding the role of MORC family CW-type zinc finger protein 3 could open doors to potential therapeutic strategies.

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