AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Palladin

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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.

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

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

Q8WX93

UPID:

PALLD_HUMAN

Alternative names:

SIH002; Sarcoma antigen NY-SAR-77

Alternative UPACC:

Q8WX93; B3KTG2; B5MD56; B7ZMM5; Q7L3E0; Q7Z3W0; Q86WE8; Q8N1M2; Q9UGA0; Q9UQF5; Q9Y2J6; Q9Y3E9

Background:

Palladin, known by alternative names SIH002 and Sarcoma antigen NY-SAR-77, is a cytoskeletal protein essential for the organization of the actin cytoskeleton. It plays a pivotal role in cell morphology, motility, adhesion, and interactions with the extracellular matrix across various cell types. Palladin functions as a scaffolding molecule, influencing actin polymerization and the assembly of actin filaments into higher-order structures. It is localized in areas of active actin remodeling such as lamellipodia and membrane ruffles, with different isoforms possibly having distinct functions.

Therapeutic significance:

Given its involvement in the cytoskeletal changes associated with dendritic cell maturation and its association with Pancreatic cancer 1, Palladin presents a promising target for therapeutic intervention. Understanding the role of Palladin could open doors to potential therapeutic strategies, particularly in combating pancreatic cancer by targeting the pathways influenced by this protein.

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