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 extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved activity, selectivity, and safety.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

Our top-notch dedicated system is used to design specialised 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.

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.

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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