Uppsats

Computational modelling of phospholipids in plasma membranes

H

Chalmers tekniska högskola / Institutionen för mikroteknologi och nanovetenskap (MC2)

Publicerad: 2022

Språk: Engelska

Sammanfattning

The purpose of this project was to investigate if the constituents of phospholipids in plasma membranes affecthow cells interact with graphene (G) and graphene oxide (GO). It has previously been shown that verticallygrown graphene flakes are effective in killing bacteria whilst keeping mammalian cells intact. However, themechanism behind this phenomena is not known, and is at the same time difficult to measure experimentally.Therefore we choose density functional theory as a tool, with the goal to enhance the understanding. Thisthesis dives into the plasma membranes of bacterial and mammalian cells, and target different phospholipidsin these membranes. The project started off by creation of a library of single phospholipids. These were puttogether into systems of pairs for calculation of bonding between different phospholipids. Further, both a Gand a GO flake were created, and incorporated into the systems with the phospholipid pairs. Analysis ofthe interaction energies between these flakes with the phospholipid pairs was performed, both when the flakesapproach the phospholipids, and upon penetration of the membrane. Calculations show that the most abundantphospholipids in mammalian cells have stronger bonding to each other, compared to bacterial phospholipids.Further, when the G/GO flakes enter between the phospholipid pairs, the bacterial pair exhibits less repulsiveinteractions, and a more stable system with the flakes were found. Therefore, these variables may contribute tothe diverse robustness between bacterial and mammalian cells, and thus, the composition of phospholipids canbe an important factor in explaining the difference in viability between organisms.

Information

Författare
Lanai, Victor
Lärosäte / institution
Chalmers tekniska högskola / Institutionen för mikroteknologi och nanovetenskap (MC2)
Publiceringsdatum
2022
Uppsatstyp
H
Språk
Engelska

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