A space-fractional cable equation for the propagation of action potentials in myelinated neurons

Myelinated neurons are characterized by the presence of myelin, a multilaminated wrapping around the axons formed by specialized neuroglial cells. Myelin acts as an electrical insulator and therefore, in myelinated neurons, the action potentials do not propagate within the axons but happen only at the nodes of Ranvier which are gaps in the axonal myelination. Recent advancements in brain science have shown that the shapes, timings, and propagation speeds of these so-called saltatory action potentials are controlled by various biochemical interactions among neurons, glial cells, and the extracellular space. Given the complexity of brain's structure and processes, the work hypothesis made in this paper is that non-local effects are involved in the optimal propagation of action potentials. A space-fractional cable equation for the action potentials propagation in myelinated neurons is proposed that involves spatial derivatives of fractional order. The effects of non-locality on the distribution of the membrane potential are investigated using numerical simulations.Comment: 20 pages, 14 figures; added reference, updated formulas, added new formulas, corrected typos, added 4 figure

Applications of Discrete Molecular Dynamics in biology and medicine

Discrete Molecular Dynamics (DMD) is a physics-based simulation method using discrete energetic potentials rather than traditional continuous potentials, allowing microsecond time scale simulations of biomolecular systems to be performed on personal computers rather than supercomputers or specialized hardware. With the ongoing explosion in processing power even in personal computers, applications of DMD have similarly multiplied. In the past two years, researchers have used DMD to model structures of disease-implicated protein folding intermediates, study assembly of protein complexes, predict protein-protein binding conformations, engineer rescue mutations in disease-causative protein mutants, design a protein conformational switch to control cell signaling, and describe the behavior of polymeric dispersants for environmental cleanup of oil spills, among other innovative applications

Computational translation of genomic responses from experimental model systems to humans

The high failure rate of therapeutics showing promise in mouse models to translate to patients is a pressing challenge in biomedical science. Though retrospective studies have examined the fidelity of mouse models to their respective human conditions, approaches for prospective translation of insights from mouse models to patients remain relatively unexplored. Here, we develop a semi-supervised learning approach for inference of disease-associated human differentially expressed genes and pathways from mouse model experiments. We examined 36 transcriptomic case studies where comparable phenotypes were available for mouse and human inflammatory diseases and assessed multiple computational approaches for inferring human biology from mouse datasets. We found that semi-supervised training of a neural network identified significantly more true human biological associations than interpreting mouse experiments directly. Evaluating the experimental design of mouse experiments where our model was most successful revealed principles of experimental design that may improve translational performance. Our study shows that when prospectively evaluating biological associations in mouse studies, semi-supervised learning approaches, combining mouse and human data for biological inference, provide the most accurate assessment of human in vivo disease processes. Finally, we proffer a delineation of four categories of model system-to-human "Translation Problems" defined by the resolution and coverage of the datasets available for molecular insight translation and suggest that the task of translating insights from model systems to human disease contexts may be better accomplished by a combination of translation-minded experimental design and computational approaches.Boehringer Ingelheim PharmaceuticalsInstitute for Collaborative Biotechnologies (Grant W911NF-09-0001

Structural and Thermodynamic Effects of Post-translational Modifications in Mutant and Wild Type Cu, Zn Superoxide Dismutase

Aggregation of Cu, Zn superoxide dismutase (SOD1) is implicated in Amyotrophic Lateral Sclerosis (ALS). Glutathionylation and phosphorylation of SOD1 is omnipresent in the human body, even in healthy individuals, and has been shown to increase SOD1 dimer dissociation, which is the first step on the pathway toward SOD1 aggregation. We find that post-translational modification of SOD1, especially glutathionylation, promotes dimer dissociation. We discover an intermediate state in the pathway to dissociation, a conformational change that involves a “loosening” of the β-barrels and a loss or shift of dimer interface interactions. In modified SOD1, this intermediate state is stabilized as compared to unmodified SOD1. The presence of post-translational modifications could explain the environmental factors involved in the speed of disease progression. Because post-translational modifications such as glutathionylation are often induced by oxidative stress, post-translational modification of SOD1 could be a factor in the occurrence of sporadic cases of ALS, which make up 90% of all cases of the disease

A Phosphomimetic Mutation Stabilizes SOD1 and Rescues Cell Viability in the Context of an ALS-Associated Mutation

The majority of amyotrophic lateral sclerosis (ALS)-related mutations in the enzyme Cu,Zn superoxide dismutase (SOD1), as well as a post-translational modification, glutathionylation, destabilize the protein and lead to a misfolded oligomer that is toxic to motor neurons. The biophysical role of another physiological SOD1 modification, T2-phosphorylation, has remained a mystery. Here, we find that a phosphomimetic mutation, T2D, thermodynamically stabilizes SOD1 even in the context of a strongly SOD1-destabilizing mutation, A4V, one of the most prevalent and aggressive ALS-associated mutations in North America. This stabilization protects against formation of toxic SOD oligomers and positively impacts motor neuron survival in cellular assays. We solve the crystal structure of T2D-SOD1 and explain its stabilization effect using discrete molecular dynamics (DMD) simulations. These findings imply that T2-phosphorylation may be a plausible innate cellular protection response against SOD1-induced cytotoxicity, and stabilizing the SOD1 native conformation might offer us viable pharmaceutical strategies against currently incurable ALS

14-color flow cytometry to determine the contribution of mitochondrial mass to differences in glycolytic capacity in human immune cell subsets

Mitochondrial metabolism controls immune cell function, but comprehensive tools to assess human primary immune cell metabolic capacity remain rudimentary. We previously demonstrated that CD19+ B cells rely more heavily on anaerobic glycolysis (i.e. are more glycolytic) than CD4+ T cells. Furthermore, both PBMCs and CD4+ T cells from subjects with type 2 diabetes (T2D) are more glycolytic than their counterparts from BMI-matched non-T2D controls. The contribution of mitochondrial mass, an indicator of non-glycolytic metabolism, to the various metabolic phenotypes is untested. To assess the contribution of immune cell subset identity and mitochondrial mass to the enhanced glycolytic capacity of resting B cells and PBMCs from T2D subjects, we designed a 13-color panel based on standard immune cell subset markers and chemokine receptors, and included MitoTracker Green FM (MTG), which quantitatively indicates mitochondrial mass. We used this novel panel to phenotype 63 total samples from BMI-matched subjects in three groups: non-T2D, pre-T2D, and fulminant T2D, as defined by American Diabetes Association guidelines. The panel was built in several iterations to accommodate spillover of MTG fluorescence into neighboring channels and includes, besides MTG and live-dead discriminator, the following surface markers: CD4, CD8, CD19, CD45RA, CD25, CD127, CD14, CCR4, CCR5, CCR6, CXCR3, and CD161. The PBMC samples were run on a 4-laser BD FACSARIA II SORP with pre-established panel-specific PMT voltages tracked using 6-peak Ultrarainbow beads. To normalize MTG fluorescence intensity and thus minimize batch effects, each of 5 total batches included a reference donor PBMC sample that was frozen in multiple aliquots from one blood draw. Using this approach, we quantified the percentages of immune cell populations (CD19+ B cells, CD8+ naïve and memory/effector T cells, and CD4+ cells including Tregs and populations enriched in Th1, Th2 and Th17) along with the relative mitochondrial mass in each subset. We found that CD19+ B cells in PBMCs from both ND and T2D subjects had significantly less mitochondrial mass than CD4+ cells, supporting the demonstration that B cells are more glycolytic than CD4+ T cells. Of all the CD4+ T cell subsets, Th17 cells consistently had the lowest mitochondrial mass, consistent with the interpretation that Th17s are more dependent on glycolysis than previously appreciated. Our results validate the utility of our 13-color panel to simultaneously quantify relative mitochondrial mass in numerous immune cell subsets and thereby provide a new tool to explore metabolism in human primary cells

Discrete Molecular Dynamics Distinguishes Nativelike Binding Poses from Decoys in Difficult Targets

Virtual screening is one of the major tools used in computer-aided drug discovery. In structure-based virtual screening, the scoring function is critical to identifying the correct docking pose and accurately predicting the binding affinities of compounds. However, the performance of existing scoring functions has been shown to be uneven for different targets, and some important drug targets have proven especially challenging. In these targets, scoring functions cannot accurately identify the native or near-native binding pose of the ligand from among decoy poses, which affects both the accuracy of the binding affinity prediction and the ability of virtual screening to identify true binders in chemical libraries. Here, we present an approach to discriminating native poses from decoys in difficult targets for which several scoring functions failed to correctly identify the native pose. Our approach employs Discrete Molecular Dynamics simulations to incorporate protein-ligand dynamics and the entropic effects of binding. We analyze a collection of poses generated by docking and find that the residence time of the ligand in the native and nativelike binding poses is distinctly longer than that in decoy poses. This finding suggests that molecular simulations offer a unique approach to distinguishing the native (or nativelike) binding pose from decoy poses that cannot be distinguished using scoring functions that evaluate static structures. The success of our method emphasizes the importance of protein-ligand dynamics in the accurate determination of the binding pose, an aspect that is not addressed in typical docking and scoring protocols

Traffic within the Cytochrome b 6 f Lipoprotein Complex: Gating of the Quinone Portal

The cytochrome bc complexes b6f and bc1 catalyze proton-coupled quinol/quinone redox reactions to generate a transmembrane proton electrochemical gradient. Quinol oxidation on the electrochemically positive (p) interface of the complex occurs at the end of a narrow quinol/quinone entry/exit Qp portal, 11 Å long in bc complexes. Superoxide, which has multiple signaling functions, is a by-product of the p-side quinol oxidation. Although the transmembrane core and the chemistry of quinone redox reactions are conserved in bc complexes, the rate of superoxide generation is an order of magnitude greater in the b6f complex, implying that functionally significant differences in structure exist between the b6f and bc1 complexes on the p-side. A unique structure feature of the b6f p-side quinol oxidation site is the presence of a single chlorophyll-a molecule whose function is unrelated to light harvesting. This study describes a cocrystal structure of the cytochrome b6f complex with the quinol analog stigmatellin, which partitions in the Qp portal of the bc1 complex, but not effectively in b6f. It is inferred that the Qp portal is partially occluded in the b6f complex relative to bc1. Based on a discrete molecular-dynamics analysis, occlusion of the Qp portal is attributed to the presence of the chlorophyll phytyl tail, which increases the quinone residence time within the Qp portal and is inferred to be a cause of enhanced superoxide production. This study attributes a novel (to our knowledge), structure-linked function to the otherwise enigmatic chlorophyll-a in the b6f complex, which may also be relevant to intracellular redox signaling

Thermal Unfolding Pathway of PHD2 Catalytic Domain in Three Different PHD2 Species: Computational Approaches

Prolyl hydroxylase domain 2 containing protein (PHD2) is a key protein in regulation of angiogenesis and metastasis. In normoxic condition, PHD2 triggers the degradation of hypoxia-inducible factor 1 (HIF-1α) that induces the expression of hypoxia response genes. Therefore the correct function of PHD2 would inhibit angiogenesis and consequent metastasis of tumor cells in normoxic condition. PHD2 mutations were reported in some common cancers. However, high levels of HIF-1α protein were observed even in normoxic metastatic tumors with normal expression of wild type PHD2. PHD2 malfunctions due to protein misfolding may be the underlying reason of metastasis and invasion in such cases. In this study, we scrutinize the unfolding pathways of the PHD2 catalytic domain’s possible species and demonstrate the properties of their unfolding states by computational approaches. Our study introduces the possibility of aggregation disaster for the prominent species of PHD2 during its partial unfolding. This may justify PHD2 inability to regulate HIF-1α level in some normoxic tumor types

Structural and Dynamic Determinants of Protein-Peptide Recognition

Protein-peptide interactions play important roles in many cellular processes, including signal transduction, trafficking, and immune recognition. Protein conformational changes upon binding, an ill-defined peptide binding surface, and the large number of peptide degrees of freedom make the prediction of protein-peptide interactions particularly challenging. To address these challenges, we perform rapid molecular dynamics simulations in order to examine the energetic and dynamic aspects of protein-peptide binding. We find that, in most cases, we recapitulate the native binding sites and native-like poses of protein-peptide complexes. Inclusion of electrostatic interactions in simulations significantly improves the prediction accuracy. Our results also highlight the importance of protein conformational flexibility, especially side-chain movement, which allows the peptide to optimize its conformation. Our findings not only demonstrate the importance of sufficient sampling of the protein and peptide conformations, but also reveal the possible effects of electrostatics and conformational flexibility on peptide recognition