AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Zinc finger protein PLAG1

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 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.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

We utilise our cutting-edge, exclusive workflow to develop focused libraries.

 Fig. 1. The sreening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of biological functions.

Several key aspects differentiate our library:

  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

partner

Reaxense

upacc

Q6DJT9

UPID:

PLAG1_HUMAN

Alternative names:

Pleiomorphic adenoma gene 1 protein

Alternative UPACC:

Q6DJT9; B4DLC2; Q59GH8; Q9Y4L2

Background:

Zinc finger protein PLAG1, also known as Pleiomorphic adenoma gene 1 protein, plays a pivotal role in cell proliferation and development. It functions as a transcription factor, activating target genes like IGFII, which leads to uncontrolled cell growth. Its overexpression is linked to various tumors, including pleomorphic adenomas of the salivary gland and hepatoblastoma, a common liver tumor in children.

Therapeutic significance:

Given its role in diseases like Silver-Russell syndrome 4 and its association with tumor development, targeting PLAG1 could offer new avenues for therapeutic interventions. Understanding the role of Zinc finger protein PLAG1 could open doors to potential therapeutic strategies.

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