Focused On-demand Library for Acidic leucine-rich nuclear phosphoprotein 32 family member A

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.

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 high-tech, dedicated method is applied to construct targeted libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse biological functions.

Our library is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.







Alternative names:

Acidic nuclear phosphoprotein pp32; Leucine-rich acidic nuclear protein; Mapmodulin; Potent heat-stable protein phosphatase 2A inhibitor I1PP2A; Putative HLA-DR-associated protein I

Alternative UPACC:

P39687; B2R6T4; Q53FK4; Q5J8L8; Q7M4N6


Acidic leucine-rich nuclear phosphoprotein 32 family member A (ALNP32A) is a multifunctional protein involved in tumor suppression, apoptosis, cell cycle progression, and transcription. It promotes apoptosis through caspase-9 activation and apoptosome formation. ALNP32A also modulates histone acetylation and transcription, inhibiting the histone-acetyltransferase activity of EP300/CREBBP. It binds to unmodified histone H3, inhibiting its acetylation and phosphorylation, leading to cell growth inhibition. Additionally, it regulates mRNA nuclear-to-cytoplasmic translocation and stability, and plays a role in viral genome replication.

Therapeutic significance:

Understanding the role of Acidic leucine-rich nuclear phosphoprotein 32 family member A could open doors to potential therapeutic strategies.

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