Computational investigation of peptide binding to fibrin for the design of targeted molecular imaging agents
Embargo Date
2026-09-10
OA Version
Citation
Abstract
Abdominal adhesions are bands of fibrous scar tissue that can connect tissues and organs that normally slide across each other. Complications can cause chronic pain, infertility, and many additional therapeutic costs. Current clinical imaging techniques, such as Magnetic Resonance Imaging (MRI) and ultrasound (US), are ineffective for early detection, so exploratory surgeries are the only method to identify their exact location. However, these surgeries may lead to more adhesions and thus there is a need for alternative visualization methods. Imaging is thus crucial for identifying adhesion location and formation, and for conducting treatment studies. Fibrin is a major component in early adhesion formation and consequently is an attractive molecular target. The goal of this thesis is to design optimized peptides that bind to fibrin for tissue targeting. Analysis of fibrin binding sites was performed using data from literature and the Protein Data Bank (PDB). Fibrin-peptide structures were visualized in Maestro, a molecular modeling software package, to compare peptide binding locations. The fibrin structure was also analyzed with FTMap, a computational method that locates binding site hot spots on the surface of proteins. The X-ray position of known peptide binders—fragments of fibrin involved in the polymerization mechanism but not useful in targeting agents— were reproduced as a control. The predicted binding affinity of the control peptides also served as a benchmark for the selection of improved peptides. Binding mode and affinity of a potential peptides for use in targeting fibrin, CREKA (Cys-Arg-Glu-Lys-Ala) and its analogs were computationally analyzed. Dynamic light scattering results to determine the effect of the peptides on fibrin polymerization were consistent with the modeling. This thesis provides detailed molecular models of peptide-fibrin binders as starting points for the development of improved peptides for tissue targeting. Peptides further optimized from the acquired data will provide a basis for further research into a targeted contrast agent to visually detect newly forming adhesions.