Characterizing Residue-Bilayer Interactions Using Gramicidin A as a Scaffold and Tryptophan Substitutions as Probes

This document is the Accepted Manuscript version of a Published Work that appeared in final form in Journal of Chemical Theory and Computation, copyright © American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see http://doi.org/10.1021/acs.jctc.7b00400.Previous experiments have shown that the lifetime of a gramicidin A dimer channel (which forms from two non-conducting monomers) in a lipid bilayer is modulated by mutations of the tryptophan (Trp) residues at the bilayer-water interface. We explore this further using extensive molecular dynamics simulations of various gA dimer and monomer mutants at the Trp positions in phosphatidylcholine bilayers with different tail lengths. gA interactions with the surrounding bilayer are strongly modulated by mutating these Trp residues. There are three principal effects: eliminating residue hydrogen bonding ability (i.e., reducing the channel-monolayer coupling strength) reduces the extent of the bilayer deformation caused by the assembled dimeric channel; a residue’s size and geometry affects its orientation, leading to different hydrogen bonding partners; and increasing a residue’s hydrophobicity increases the depth of gA monomer insertion relative to the bilayer center, thereby increasing the lipid bending frustration

Advances in Molecular Quantum Chemistry Contained in the Q-Chem 4 Program Package

A summary of the technical advances that are incorporated in the fourth major release of the Q-Chem quantum chemistry program is provided, covering approximately the last seven years. These include developments in density functional theory methods and algorithms, nuclear magnetic resonance (NMR) property evaluation, coupled cluster and perturbation theories, methods for electronically excited and open-shell species, tools for treating extended environments, algorithms for walking on potential surfaces, analysis tools, energy and electron transfer modelling, parallel computing capabilities, and graphical user interfaces. In addition, a selection of example case studies that illustrate these capabilities is given. These include extensive benchmarks of the comparative accuracy of modern density functionals for bonded and non-bonded interactions, tests of attenuated second order Møller–Plesset (MP2) methods for intermolecular interactions, a variety of parallel performance benchmarks, and tests of the accuracy of implicit solvation models. Some specific chemical examples include calculations on the strongly correlated Cr2 dimer, exploring zeolite-catalysed ethane dehydrogenation, energy decomposition analysis of a charged ter-molecular complex arising from glycerol photoionisation, and natural transition orbitals for a Frenkel exciton state in a nine-unit model of a self-assembling nanotube

Characterizing Residue-Bilayer Interactions Using Gramicidin A as a Scaffold and Tryptophan Substitutions as Probes

Previous experiments have shown that the lifetime of a gramicidin A dimer channel (which forms from two nonconducting monomers) in a lipid bilayer is modulated by mutations of the tryptophan (Trp) residues at the bilayer-water interface. We explore this further using extensive molecular dynamics simulations of various gA dimer and monomer mutants at the Trp positions in phosphatidylcholine bilayers with different tail lengths. gA interactions with the surrounding bilayer are strongly modulated by mutating these Trp residues. There are three principal effects: eliminating residue hydrogen bonding ability (i.e., reducing the channel-monolayer coupling strength) reduces the extent of the bilayer deformation caused by the assembled dimeric channel; a residue’s size and geometry affects its orientation, leading to different hydrogen bonding partners; and increasing a residue’s hydrophobicity increases the depth of gA monomer insertion relative to the bilayer center, thereby increasing the lipid bending frustration

Discriminating Survival Outcomes in Patients with Glioblastoma Using a Simulation-Based, Patient-Specific Response Metric

<div><p>Accurate clinical assessment of a patient's response to treatment for glioblastoma multiforme (GBM), the most malignant type of primary brain tumor, is undermined by the wide patient-to-patient variability in GBM dynamics and responsiveness to therapy. Using computational models that account for the unique geometry and kinetics of individual patients' tumors, we developed a method for assessing treatment response that discriminates progression-free and overall survival following therapy for GBM. Applying these models as untreated virtual controls, we generate a patient-specific “Days Gained” response metric that estimates the number of days a therapy delayed imageable tumor progression. We assessed treatment response in terms of Days Gained scores for 33 patients at the time of their first MRI scan following first-line radiation therapy. Based on Kaplan-Meier analyses, patients with Days Gained scores of 100 or more had improved progression-free survival, and patients with scores of 117 or more had improved overall survival. Our results demonstrate that the Days Gained response metric calculated at the routinely acquired first post-radiation treatment time point provides prognostic information regarding progression and survival outcomes. Applied prospectively, our model-based approach has the potential to improve GBM treatment by accounting for patient-to-patient heterogeneity in GBM dynamics and responses to therapy.</p> </div

Kaplan-Meier analyses on progression-free and overall survival.

<p><i>a</i>: Analysis on progression-free survival data revealed a significant difference between the patients with Days Gained scores greater than or equal to 100 and those with lower scores. <i>b</i>: Overall survival analysis also revealed a significant difference between the patients with Days Gained scores greater than or equal to 117 and those with lower scores.</p