In Silico Design and Analysis of Plastic-Binding Peptides

Peptides that bind to inorganic materials can be used to functionalize surfaces, control crystallization, or assist in interfacial self-assembly. In the past, inorganic-binding peptides have been found predominantly through peptide library screening. While this method has successfully identified peptides that bind to a variety of materials, an alternative design approach that can intelligently search for peptides and provide physical insight for peptide affinity would be desirable. In this work, we develop a computational, physics-based approach to design inorganic-binding peptides, focusing on peptides that bind to the common plastics polyethylene, polypropylene, polystyrene, and poly(ethylene terephthalate). The PepBD algorithm, a Monte Carlo method that samples peptide sequence and conformational space, was modified to include simulated annealing, relax hydration constraints, and an ensemble of conformations to initiate design. These modifications led to the discovery of peptides with significantly better scores compared to those obtained using the original PepBD. PepBD scores were found to improve with increasing van der Waals interactions, although strengthening the intermolecular van der Waals interactions comes at the cost of introducing unfavorable electrostatic interactions. The best designs are enriched in amino acids with bulky side chains and possess hydrophobic and hydrophilic patches whose location depends on the adsorbed conformation. Future work will evaluate the top peptide designs in molecular dynamics simulations and experiment, enabling their application in microplastic pollution remediation and plastic-based biosensors.

New Bioactive Peptides from the Mediterranean Seagrass Posidonia oceanica (L.) Delile and Their Impact on Antimicrobial Activity and Apoptosis of Human Cancer Cells

The demand for new molecules to counter bacterial resistance to antibiotics and tumor cell resistance is increasingly pressing. The Mediterranean seagrass Posidonia oceanica is considered a promising source of new bioactive molecules. Polypeptide-enriched fractions of rhizomes and green leaves of the seagrass were tested against Gram-positive (e.g., Staphylococcus aureus, Enterococcus faecalis) and Gram-negative bacteria (e.g., Pseudomonas aeruginosa, Escherichia coli), as well as towards the yeast Candida albicans. The aforementioned extracts showed indicative MIC values, ranging from 1.61 μg/mL to 7.5 μg/mL, against the selected pathogens. Peptide fractions were further analyzed through a high-resolution mass spectrometry and database search, which identified nine novel peptides. Some discovered peptides and their derivatives were chemically synthesized and tested in vitro. The assays identified two synthetic peptides, derived from green leaves and rhizomes of P. oceanica, which revealed interesting antibiofilm activity towards S. aureus, E. coli, and P. aeruginosa (BIC50 equal to 17.7 μg/mL and 70.7 μg/mL). In addition, the natural and derivative peptides were also tested for potential cytotoxic and apoptosis-promoting effects on HepG2 cells, derived from human hepatocellular carcinomas. One natural and two synthetic peptides were proven to be effective against the "in vitro" liver cancer cell model. These novel peptides could be considered a good chemical platform for developing potential therapeutics.

Rational Design of de novo CCL2 Binding Peptides

Chronic levels of inflammation lead to autoimmune diseases such as rheumatoid arthritis and atherosclerosis. A key molecular mediator responsible for the progression of these diseases is Chemokine C-C motif ligand 2 (CCL2), a homodimerized cytokine that dissociates into monomeric form and binds to the CCR2 receptor. CCL2, also known as monocyte chemoattractant protein-1 (MCP-1), attracts monocytes to migrate to areas of injury and mature into macrophages, leading to positive feedback inflammation with further release of proinflammatory molecules such as IL-1β and TNF-α. Sequestering CCL2 to prevent its binding to CCR2 may prevent this inflammatory activity. Prior work adapted an α-helical CCL2-binding peptide (WKNFQTI) from murine CCR2 through extracellular loop analysis. Here, higher-affinity peptide binders were computationally designed through homology modeling and energy calculations, yielding an 11-amino acid peptide with high binding affinity. In addition, Rosetta mutations improved binding affinity in silico with blockage of the CCL2 dimerization site. Future work in analyzing binding kinetics and in vivo inflammation abrogation will confirm the accuracy of computational modeling techniques in de novo rational design of CCL2 cytokine binders.