Alteration of lipid bilayer mechanics by volatile anesthetics: insights from μs-long molecular dynamics simulations

Very few drugs in clinical practice feature the chemical diversity, narrow therapeutic window, unique route of administration, and reversible cognitive effects of volatile anesthetics. The correlation between their hydrophobicity and their potency and the increasing amount of evidence suggesting that anesthetics exert their action on transmembrane proteins, justifies the investigation of their effects on phospholipid bilayers at the molecular level, given the strong functional and structural link between transmembrane proteins and the surrounding lipid matrix. Molecular dynamics simulations of a model lipid bilayer in the presence of ethylene, desflurane, methoxyflurane, and the nonimmobilizer 1,2-dichlorohexafluorocyclobutane (also called F6 or 2N) at different concentrations highlight the structural consequences of VA partitioning in the lipid phase, with a decrease of lipid order and bilayer thickness, an increase in overall lipid lateral mobility and area-per-lipid, and a marked reduction in the mechanical stiffness of the membrane, that strongly correlates with the compounds' hydrophobicity

In silico investigation of molecular interactions of Volatile Anesthetics: Effects on phospholipid membranes and subcellular targets

The ability of anesthetics to reversibly suppress consciousness must reside in the effects exerted onto specific molecular tar- gets. Interactions between Volatile Anesthetics and the phospholipid mem- brane as well as intracellular tubulin, were investigated using Computational Molecular Modelling, which showed rapid ligand partitioning inside the membrane and significant effects on the mechanical char- acteristics thereof, while transient binding locations have been found on the tubulin dimer

Insights into the interaction dynamics between volatile anesthetics and tubulin through computational molecular modelling

General anesthetics, able to reversibly suppress all conscious brain activity, have baffled medical science for decades, and little is known about their exact molecular mechanism of action. Given the recent scientific interest in the exploration of microtubules as putative functional targets of anesthetics, and the involvement thereof in neurodegenerative disorders, the present work focuses on the investigation of the interaction between human tubulin and four volatile anesthetics: ethylene, desflurane, halothane and methoxyflurane. Interaction sites on different tubulin isotypes are predicted through docking, along with an estimate of the binding affinity ranking. The analysis is expanded by Molecular Dynamics simulations, where the dimers are allowed to freely interact with anesthetics in the surrounding medium. This allowed for the determination of interaction hotspots on tubulin dimers, which could be linked to different functional consequences on the microtubule architecture, and confirmed the weak, Van der Waals-type interaction, occurring within hydrophobic pockets on the dimer. Both docking and MD simulations highlighted significantly weaker interactions of ethylene, consistent with its far lower potency as a general anesthetic. Overall, simulations suggest a transient interaction between anesthetics and microtubules in general anesthesia, and contact probability analysis shows interaction strengths consistent with the potencies of the four compounds

PAMAM and PPI dendrimers as potential anti-cancer drug carriers: a computational investigation

Photodynamic therapy (PDT) is a promising technique for several types of anti-cancer therapy, exploiting a photosensitizer, a light source and oxygen. The present work computationally investigates the properties of poly(amidoamine) (PAMAM) and poly(propyleneimine) (PPI) dendrimers of generation 3 and 4 as potential nanoscale drug delivery systems for Rose Bengal (RB), a candidate photosensitizer for PDT

Electronic energy migration in Microtubules

The repeating arrangement of tubulin dimers confers great mechanical strength to microtubules, which are used as scaffolds for intracellular macromolecular transport in cells and exploited in biohybrid devices. The crystalline order in a microtubule, with lattice constants short enough to allow energy transfer between amino acid chromophores, is similar to synthetic structures designed for light harvesting. After photoexcitation, can these amino acid chromophores transfer excitation energy along the microtubule like a natural or artificial light-harvesting system? Here, we use tryptophan autofluorescence lifetimes to probe energy hopping between aromatic residues in tubulin and microtubules. By studying how the quencher concentration alters tryptophan autofluorescence lifetimes, we demonstrate that electronic energy can diffuse over 6.6 nm in microtubules. We discover that while diffusion lengths are influenced by tubulin polymerization state (free tubulin versus tubulin in the microtubule lattice), they are not significantly altered by the average number of protofilaments (13 versus 14). We also demonstrate that the presence of the anesthetics etomidate and isoflurane reduce exciton diffusion. Energy transport as explained by conventional Förster theory (accommodating for interactions between tryptophan and tyrosine residues) does not sufficiently explain our observations. Our studies indicate that microtubules are, unexpectedly, effective light harvesters

Application of effective operator technique in crystal field theory

Bibliography: p. 157-162

Molecular signaling network complexity is correlated with cancer patient survivability

The 5-y survival for cancer patients after diagnosis and treatment is strongly dependent on tumor type. Prostate cancer patients have a >99% chance of survival past 5 y after diagnosis, and pancreatic patients have <6% chance of survival past 5 y. Because each cancer type has its own molecular signaling network, we asked if there are “signatures” embedded in these networks that inform us as to the 5-y survival. In other words, are there statistical metrics of the network that correlate with survival? Furthermore, if there are, can such signatures provide clues to selecting new therapeutic targets? From the Kyoto Encyclopedia of Genes and Genomes Cancer Pathway database we computed several conventional and some less conventional network statistics. In particular we found a correlation (R(2) = 0.7) between degree-entropy and 5-y survival based on the Surveillance Epidemiology and End Results database. This correlation suggests that cancers that have a more complex molecular pathway are more refractory than those with less complex molecular pathway. We also found potential new molecular targets for drugs by computing the betweenness—a statistical metric of the centrality of a node—for the molecular networks