AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Zinc finger protein PLAGL1

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.

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 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 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.

partner

Reaxense

upacc

Q9UM63

UPID:

PLAL1_HUMAN

Alternative names:

Lost on transformation 1; Pleiomorphic adenoma-like protein 1; Tumor suppressor ZAC

Alternative UPACC:

Q9UM63; B2RBA4; B2RCM8; E1P595; E1P597; O76019; Q7Z3V8; Q92981; Q96JR9; Q9UIZ0

Background:

Zinc finger protein PLAGL1, also known as Lost on transformation 1, Pleiomorphic adenoma-like protein 1, and Tumor suppressor ZAC, plays a pivotal role as a transcriptional activator. It is crucial in the transcriptional regulation of the type 1 receptor for pituitary adenylate cyclase-activating polypeptide, highlighting its significance in cellular signaling pathways.

Therapeutic significance:

PLAGL1's involvement in transient neonatal diabetes mellitus 1, a condition characterized by early-onset hyperglycemia, underscores its therapeutic potential. Understanding the role of PLAGL1 could open doors to potential therapeutic strategies, especially considering its link to aberrant hypomethylation in the disease's pathogenesis.

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