Back
2025INF005
Public access from
27/05/2026
Doctoral thesis

Integrating data-driven approach and mechanistic explainability to unveil the molecular mechanism of TAT-RasGAP317-326 in anticancer and antibacterial domains

  • 2025

PhD: Università della Svizzera italiana

TAT-RasGAP317-326
Cell-penetrating peptides
Anticancer peptides
Antibacterial peptides
Molecular dynamics
Machine learning
Genetic algorithms
Optimization peptides
Peptide-membrane interaction
Peptide-protein interaction
English This thesis explores the multifaceted realm of cell-penetrating peptides (CPPs), highlighting their transformative potential in biomedical applications through the integration of genetic algorithms (GA), machine learning (ML), and Molecular Dynamics (MD) simulations. These methodologies are employed to design de novo CPP sequences and explore their multifunctional capabilities, paving the way for innovative therapeutic strategies. CPPs, typically composed of 5 to 30 amino acids and characterized by a net positive charge at physiological pH, have emerged as powerful tools for facilitating efficient intracellular delivery of therapeutic agents. Their ability to traverse cellular membranes while maintaining low cytotoxicity makes them indispensable in drug delivery and targeted therapy. Central to our exploration is the unveiling of TAT-RasGAP317-326 bioactive capabilities, a chimeric CPP-based construct exhibiting both antitumoral and antibacterial activities. This novel peptide demonstrates its efficacy in selectively killing cancer cells through intricate mechanisms that do not conform to established programmed cell death pathways. The antitumoral effect starts with the translocation of the peptide into the cytosol, binding lipids like phosphatidylinositol bisphosphate (PIP2) and phosphatidylserine (PS), which are enriched in the inner leaflet of the membrane. These interactions induce membrane permeabilization and disruption, ultimately leading to cell death. This unique mode of action underscores the peptide's potential as a targeted anticancer agent with minimal off-target effects. Beyond its antitumoral properties, TAT-RasGAP317-326 also demonstrates promising antibacterial capabilities, offering a potential solution to the growing challenge of antibiotic resistance. MD simulations provided detailed insights into the peptide's interactions with the E. coli Bam protein, a critical component of the bacterial outer membrane assembly machinery. These computational investigations uncovered the mechanism by which TAT-RasGAP317-326 inhibits the Bam protein machinery, providing valuable insights into its mode of action and highlighting its potential applications in addressing antibiotic-resistant bacterial strains, such as E. coli. Furthermore, the study proposes novel mutations within the E. coli Bam protein that could modulate its susceptibility to TAT-RasGAP317-326, offering a pathway to enhance or fine-tune the peptide's antibacterial efficacy. This holistic approach underscores the potential of TAT-RasGAP317-326 as a versatile therapeutic agent, capable of addressing both cancer and bacterial infections, while contributing to the broader field of peptide-based drug development. Through this work, we aim to advance the frontiers of biomedical science, offering new tools to combat some of the most pressing health challenges of our time.
Collections
Language
  • English
Classification
Computer science and technology
License
License undefined
Open access status
green
Identifiers
Persistent URL
https://n2t.net/ark:/12658/srd1332052
Statistics
Document views: 12 File downloads:
  • 2025INF005.pdf: 0