Gap Junction Channels and antibacterial property of chitosan studied by molecular dynamics studies

Abstract

Until now there are more than 20 different type of connexins have been determined in the human genome. And two connexins (hemichannels) dock end-to-end forming a gap junction channel. Gap junction channels allow ions and small molecules to go through and their mutations are associated with various diseases. Electrophysiological studies have identified disparate ion selectivity for different connexin channels, but the molecular basis remains unclear. Several recent molecular dynamics simulations only clouded the picture. We carried out rigorous free-energy calculations using all-atom molecular dynamics simulations for Cx26 and Cx32 hemichannels in explicit phospholipid membrane bilayers. Then we did the same with two mutated systems that were exchanged pore-lining residues between these two x hemichannels. The potentials of mean force for cation and anion permeation explain the cation selectivity for the Cx26 channel and the modest anion selectivity for the Cx32 channel. For Cx26, pore-lining residues K41/M1 and K15/R99/K103 form energy wells for Cl- and barriers for K+, while D46/D50 form a barrier for Cl- and a well for K+. For Cx32, E41/D46/E47 forms a barrier for Cl- whereas M1 forms a barrier for K+. For Cx26 mutated, with K41E mutation, E41 forms a energy well for K+ and a barrier for Cl-, while with D2N, Q48K, D50S and R99Q lost their wells or barriers property. For Cx32 mutated, K41/R99 form energy wells for Cl- and barriers for K+ with E41K, Q99R mutations, while in other mutations (N2D, S50D) D2/D50 form wells for K+ and barriers for Cl-. These results provide a solid foundation for quantitatively rationalizing gap junction channel selectivity and conductance. Chitosan, the deacetylated derivative of chitin, is a cationic biopolymer with a number of application in medicine. There are some researches about the relationship between chitosan and antibacterial activity. However, the molecular interactions have not been detailed yet. In this study, we performed molecular dynamics simulations to study interactions between chitosan and bacterial membranes. We carried out 4 simulation systems of chitosan in environments with 3 different pH values (pH<6, pH = 6, and pH >6) and 2 lipid bilayers that mimic the bacterial cell membranes and mammalian cell membranes. They are 1-palmitoyl-2-oleoyl-sn-glycero-3- phosphoethanolamine (POPE)/ 1-palmitoyl-2-oleoyl -sn-glycero-3- phosphoglycerol (POPG) (ratio = 3:1) lipid and 1-palmitoyl-2-oleoyl-sn- xi glycero-3-phosphocholine(POPC) lipids. Three systems with POPE/POPG and 1 system with POPC in pH>6. A very large scale of simulations were accumulated for each system. The interactions between chitosan and lipid bilayer were observed. And we also carried out free-energy calculations using umbrella sampling simulations. Decreasing the value of pH, the interaction between chitosan and lipid bilayer was stronger. The details of the interactions will be helpful in the future studies of chitosan.