Binding free energy calculation of peptides to carbon nanotubes using molecular dynamics with a linear interaction energy approach

Molecular dynamics simulation of non-covalent single-walled carbon nanotube functionalization with surfactant peptides

Non-covalent functionalized single-walled carbon nanotubes (SWCNTs) with improved solubility and biocompatibility can successfully transfer drugs, DNA, RNA, and proteins into the target cells. Theoretical studies such as molecular docking and molecular dynamics simulations in fully atomistic scale were used to investigate the hydrophobic and aromatic π-π-stacking interaction of designing four novel surfactant peptides for non-covalent functionalization of SWCNTs. The results indicated that the designed peptides have binding affinity towards SWCNT with constant interactions during MD simulation times, and it can even be improved by increasing the number of tryptophan residues. The aromatic content of the peptides plays a significant role in their adsorption in SWCNT wall. The data suggest that π-π stacking interaction between the aromatic rings of tryptophan and π electrons of SWCNTs is more important than hydrophobic effects for dispersing carbon nanotubes; nevertheless SWCNTs are strongly hydrophobic in front of smooth surfaces. The usage of aromatic content of peptides for forming SWCNT/peptide complex was proved successfully, providing new insight into peptide design strategies for future nano-biomedical applications.

Molecular dynamics simulations of simple aromatic compounds adsorption on single-walled carbon nanotubes

We have conducted MD simulations and RDG calculations to reveal the mechanisms of simple aromatic compounds adsorption on SWCNTs.

Molecular modeling in structural nano-toxicology: interactions of nano-particles with nano-machinery of cells

Over the past two decades, nanotechnology has emerged as a key player in various disciplines of science and technology. Some of the most exciting applications are in the field of biomedicine - for theranostics (for combined diagnostic and therapeutic purposes) as well as for exploration of biological systems. A detailed understanding of the molecular interactions between nanoparticles and biological nano-machinery - macromolecules, membranes, and intracellular organelles - is crucial for obtaining adequate information on mechanisms of action of nanomaterials as well as a perspective on the long term effects of these materials and their possible toxicological outcomes. This review focuses on the use of structure-based computational molecular modeling as a tool to understand and to predict the interactions between nanomaterials and nano-biosystems. We review major approaches and provide examples of computational analysis of the structural principles behind such interactions. A rationale on how nanoparticles of different sizes, shape, structure and chemical properties can affect the organization and functions of nano-machinery of cells is also presented.