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Perspective: computational modeling of accurate cellular membranes with molecular resolution

JOURNAL OF CHEMICAL PHYSICS 2018年第22期149卷 220901-220901页

作者： Klauda, Jeffery B. Univ Maryland Dept Chem & Biomol Engn College Pk MD 20742 USA Univ Maryland Biophys Grad Program College Pk MD 20742 USA

modeling lipid bilayers using molecular simulations has progressed from short simulations of single-component lipids to currently having the ability to model complex cellular membranes with nearly 100 different lipid types on a mu s time scale. This perspective article presents a review of how the chemical physics field has provided insight into the structure and dynamics of accurate cellular membrane models. A short review of lipid force fields is presented, and how lower-resolution models can allow for assemblies and time scales not attainable with all-atom models. Key examples on membranes that mimic the lipid diversity seen in nature are provided for all-atom and coarse-grained lipid force fields. The article concludes with an outlook for the field on where there exist certain challenges (lipid diversity and leaflet concentration asymmetry) over the next several years. This is an exciting time to be a researcher in the field of modeling cellular membranes with ultimate goals to model not just an accurate cell membrane but in the future modeling a whole cell. Published by AIP Publishing.

关键词： Lipids computational modeling field theory (physics) membrane Cells Atoms Attitude time scales Perspective Lipid Bilayers Researchers

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A combined experimental and computational modeling study on adsorption of propionic acid onto silica-embedded NiO/MgO nanoparticles

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CHEMICAL ENGINEERING JOURNAL 2017年 327卷 666-677页

作者： El-Qanni, Amjad Nassar, Nashaat N. Vitale, Gerardo Univ Calgary Dept Chem & Petr Engn Calgary AB T2N 1N4 Canada An Najah Natl Univ Dept Chem Engn POB 7 Nablus Palestine

Adsorption of propionic acid (PA) onto silica-embedded NiO/MgO nanoparticles (i.e., SiO2-NiO, SiO2-MgO, and SiO2-(Ni0.5Mg0.5)O) was investigated experimentally and theoretically by carrying out computational modeling through molecular mechanics, density functional theory (DFT) calculations, and molecular dynamics (MD) simulations. The experimental adsorption isotherm fit well to the Sips model with a heterogeneity factor between 0.2 and 0.5 in most cases, indicating a heterogeneous adsorption system. SiO2-NiO nanoparticles showed the highest uptake on a normalized surface area basis due to its stability in aqueous solutions. Moreover, the results of thermodynamic studies, namely, changes in Gibbs free energy (DG degrees(ads)) and standard enthalpy (Delta H degrees(ads)), confirmed that the adsorption is spontaneous and exothermic in nature, respectively. Furthermore, computational modeling of the molecular interaction between the PA molecule and the nanoparticle surfaces of both NiO and MgO were implemented to address the adsorption behavior comprehensively. Interestingly, in vacuum media, the computational modeling and DFT calculations showed that MgO favored the PA molecule adsorption stronger than the NiO, contrary to what observed experimentally. MD simulations counted the presence of water molecules and provided more linkable results to the ones observed experimentally. Eventually, by having a meticulous eye of the equilibrated structures of PA molecules at the NiO-water interfaces according to the MD simulation, we could confirm theoretically the maximum adsorption capacity for complete monolayer coverage with the one obtained experimentally which was around 2.8 (molecules/nm(2)). (C) 2017 Elsevier B.V. All rights reserved.

关键词： Propionic acid Silica-embedded NiO/MgO Nanosorbcats Adsorption computational modeling

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Stents: Biomechanics, Biomaterials, and Insights from computational modeling

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ANNALS OF BIOMEDICAL ENGINEERING 2017年第4期45卷 853-872页

作者： Karanasiou, Georgia S. Papafaklis, Michail I. Conway, Claire Michalis, Lampros K. Tzafriri, Rami Edelman, Elazer R. Fotiadis, Dimitrios I. Univ Ioannina Unit Med Technol & Intelligent Informat Syst Dept Mat Sci Univ Campus Ioannina Ioannina 45100 Greece Fdn Res & Technol Hellas FORTH Ioannina Greece Univ Ioannina Sch Med Second Dept Cardiol Ioannina Greece Univ Ioannina Michailide Cardiac Ctr Ioannina Greece MIT Inst Med Engn & Sci 77 Massachusetts Ave Cambridge MA 02139 USA CBSET Lexington MA USA Harvard Med Sch Brigham & Womens Hosp Cardiovasc Div Boston MA USA

Coronary stents have revolutionized the treatment of coronary artery disease. Improvement in clinical outcomes requires detailed evaluation of the performance of stent biomechanics and the effectiveness as well as safety of biomaterials aiming at optimization of endovascular devices. Stents need to harmonize the hemodynamic environment and promote beneficial vessel healing processes with decreased thrombogenicity. Stent design variables and expansion properties are critical for vessel scaffolding. Drug-elution from stents, can help inhibit in-stent restenosis, but adds further complexity as drug release kinetics and coating formulations can dominate tissue responses. Biodegradable and bioabsorbable stents go one step further providing complete absorption over time governed by corrosion and erosion mechanisms. The advances in computing power and computational methods have enabled the application of numerical simulations and the in silico evaluation of the performance of stent devices made up of complex alloys and bioerodible materials in a range of dimensions and designs and with the capacity to retain and elute bioactive agents. This review presents the current knowledge on stent biomechanics, stent fatigue as well as drug release and mechanisms governing biodegradability focusing on the insights from computational modeling approaches.

关键词： Stent computational modeling Biomechanics Biomaterials Degradation Corrosion Drug-elution Hemodynamic environment

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Comparing 3d and 2d computational modeling of an oil well blowout using MOHID platform - A case study in the Campos Basin

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SCIENCE OF THE TOTAL ENVIRONMENT 2017年 595卷 633-641页

作者： Paiva, P. M. Lugon Junior, J. Barreto, A. N. Silva, J. A. F. Silva Neto, A. J. Inst Fed Fluminense IFFluminense Campus Macae Macae RJ Brazil Univ Estado Rio de Janeiro Inst Politecn Nova Friburgo RJ Brazil

The oil well blowout releases hydrocarbons into the marine environment as an oil droplets and gas bubbles dispersion. The oil trajectory is strongly influenced by physical, chemical and biological processes. In general, the ocean oil drift studies are based on a two-dimensional approach, whereas the whole oil from a well blowout can be represented by a surface oil leak in the same geographical coordinates. This work is a case study, where MOHID software is used at the Campos Basin region, in which the Lagrangian results of the surface oil leaks were confronted to their well blowout scenarios in different conditions of depth, seasonality (summer and winter), and use of dispersants at the source of the leak. The research results reinforced the importance of the three-dimensional approach to the scenario of deep and ultra-deepwaters, especially for cases in which the dispersant injection into the source of the leak was considered. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Oil leak computational modeling Three-dimensional model Blowout Trajectory Dispersants

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Catalytic Cycle of Haloalkane Dehalogenases Toward Unnatural Substrates Explored by computational modeling

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JOURNAL OF CHEMICAL INFORMATION AND modeling 2017年第8期57卷 1970-1989页

作者： Marques, Sergio M. Dunajova, Zuzana Prokop, Zbynek Chaloupkova, Radka Brezovsky, Jan Damborsky, Jiri Masaryk Univ Dept Expt Biol Loschmidt Labs Kamenice 5-A13 Brno 62500 Czech Republic Masaryk Univ Res Ctr Toxic Cpds Environm RECETOX Fac Sci Kamenice 5-A13 Brno 62500 Czech Republic St Annes Univ Hosp Brno Int Clin Res Ctr Pekarska 53 CS-60365 Brno Czech Republic

The anthropogenic toxic compound 1,2,3-trichloropropane is poorly degradable by natural enzymes. We have previously constructed the haloalkane dehalogenase DhaA31 by focused directed evolution (Pavlova, M. et al. Nat. Chem. Biol. 2009, 5, 727-733), which is 32 times more active than the wild-type enzyme and is currently the most active variant known against that substrate. Recent evidence has shown that the structural basis responsible for the higher activity of DhaA31 was poorly understood. Here we have undertaken a comprehensive computational study of the main steps involved in the biocatalytic hydrolysis of 1,2,3-trichloropropane to decipher the structural basis for such enhancements. Using molecular dynamics and quantum mechanics approaches we have surveyed (i) the substrate binding, (ii) the formation of the reactive complex, (iii) the chemical step, and (iv) the release of the products. We showed that the binding of the substrate and its transport through the molecular tunnel to the active site is a relatively fast process. The cleavage of the carbon halogen bond was previously identified as the rate-limiting step in the wild-type. Here we demonstrate that this step was enhanced in DhaA31 due to a significantly higher number of reactive configurations of the substrate and a decrease of the energy barrier to the S(N)2 reaction. C176Y and V245F were identified as the key mutations responsible for most of those improvements. The release of the alcohol product was found to be the rate-limiting step in DhaA31 primarily due to the C176Y mutation. Mutational dissection of DhaA31 and kinetic analysis of the intermediate mutants confirmed the theoretical observations. Overall, our comprehensive computational approach has unveiled mechanistic details of the catalytic cycle which will enable a balanced design of more efficient enzymes. This approach is applicable to deepen the biochemical knowledge of a large number of other systems and may contribute to robust strategie

关键词： haloalkane dehalogenase alcohol product Substrates Energy barrier Alkyl halides balanced design Dynamic analysis computational modeling Catalysis

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Researching Fiber Networks computational modeling of complex fibrous tissue geometries.

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IEEE PULSE 2017年第4期8卷 58-61页

作者： Makarov, Sergey Leone, Alvaro-Pascual Nummenmaa, Aapo Worcester Polytech Inst Dept Elect & Comp Engn Worcester MA 01609 USA Harvard Med Sch Massachusetts Gen Hosp Athinoula A Martinos Ctr Biomed Imaging Boston MA 02115 USA Harvard Med Sch Beth Israel Deaconess Med Ctr Div Cognit Neurol Boston MA USA

Many types of human tissue-such as the brain and spinal cord of the central nervous system, the peripheral nervous system, and muscles, including the heart muscle-are fibrous in nature. Isotropic human models that ass... 详细信息

关键词： Optical fiber networks Magnetic resonance imaging computational modeling Brain modeling Biomedical imaging Image reconstruction

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Impaired Flexible Reward-Based Decision-Making in Binge Eating Disorder: Evidence from computational modeling and Functional Neuroimaging

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NEUROPSYCHOPHARMACOLOGY 2017年第3期42卷 628-637页

作者： Reiter, Andrea M. F. Heinze, Hans-Jochen Schlagenhauf, Florian Deserno, Lorenz Max Planck Inst Human Cognit & Brain Sci Max Planck Fellow Grp Cognit & Affect Control Beh Leipzig Germany Tech Univ Dresden Dept Psychol Dresden Germany Otto Von Guericke Univ Dept Neurol Magdeburg Germany Leibniz Inst Neurobiol Dept Behav Neurol Magdeburg Germany Charite Univ Med Berlin Campus Charite Mitte Dept Psychiat & Psychotherapy Berlin Germany

Despite its clinical relevance and the recent recognition as a diagnostic category in the DSM-5, binge eating disorder (BED) has rarely been investigated from a cognitive neuroscientific perspective targeting a more precise neurocognitive profiling of the disorder. BED patients suffer from a lack of behavioral control during recurrent binge eating episodes and thus fail to adapt their behavior in the face of negative consequences, eg, high risk for obesity. To examine impairments in flexible reward-based decision-making, we exposed BED patients (n = 22) and matched healthy individuals (n = 22) to a reward-guided decision-making task during functional resonance imaging (fMRI). Performing fMRI analysis informed via computational modeling of choice behavior, we were able to identify specific signatures of altered decision-making in BED. On the behavioral level, we observed impaired behavioral adaptation in BED, which was due to enhanced switching behavior, a putative deficit in striking a balance between exploration and exploitation appropriately. This was accompanied by diminished activation related to exploratory decisions in the anterior insula/ventro-lateral prefrontal cortex. Moreover, although so-called model-free reward prediction errors remained intact, representation of ventro medial prefrontal leaming signatures, incorporating inference on unchosen options, was reduced in BED, which was associated with successful decision-making in the task. On the basis of a computational psychiatry account, the presented findings contribute to defining a neurocognitive phenotype of BED.

关键词： computational modeling decision making FLEXIBLE Functional Neuroimaging Behavior Control Error of prediction Binge Eating Disorder

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A whole-brain computational modeling approach to explain the alterations in resting-state functional connectivity during progression of Alzheimer's disease

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NEUROIMAGE-CLINICAL 2017年 16卷 343-354页

作者： Demirtas, Murat Falcon, Carles Tucholka, Alan Domingo Gispert, Juan Luis Molinuevo, Jose Deco, Gustavo Univ Pompeu Fabra Dept Informat & Commun Technol Computat Neurosci Grp Ctr Brain & Cognit Barcelona 08018 Spain Yale Univ Psychiat Dept New Haven CT 06510 USA ICREA Barcelona 08010 Spain Pasqual Maragall Fdn Barcelonasseta Brain Res Ctr Barcelona Spain Ctr Invest Biomed Red Bioingn Biomat & Nanomed CI Zaragoza Spain Max Planck Inst Human Cognit & Brain Sci Dept Neuropsychol D-04103 Leipzig Germany Monash Univ Sch Psychol Sci Melbourne Vic Australia

Alzheimer's disease (AD) is the most common dementia with dramatic consequences. The research in structural and functional neuroimaging showed altered brain connectivity in AD. In this study, we investigated the whole-brain resting state functional connectivity (FC) of the subjects with preclinical Alzheimer's disease (PAD), mild cognitive impairment due to AD (MCI) and mild dementia due to Alzheimer's disease (AD), the impact of APOE4 carriership, as well as in relation to variations in core AD CSF biomarkers. The synchronization in the whole-brain was monotonously decreasing during the course of the disease progression. Furthermore, in AD patients we found widespread significant decreases in functional connectivity (FC) strengths particularly in the brain regions with high global connectivity. We employed a whole-brain computational modeling approach to study the mechanisms underlying these alterations. To characterize the causal interactions between brain regions, we estimated the effective connectivity (EC) in the model. We found that the significant EC differences in AD were primarily located in left temporal lobe. Then, we systematically manipulated the underlying dynamics of the model to investigate simulated changes in FC based on the healthy control subjects. Furthermore, we found distinct patterns involving CSF biomarkers of amyloid-beta (A beta 1 - 42) total tau (t-tau) and phosphorylated tau (p-tau). CSF A beta 1 - 42 was associated to the contrast between healthy control subjects and clinical groups. Nevertheless, tau CSF biomarkers were associated to the variability in whole-brain synchronization and sensory integration regions. These associations were robust across clinical groups, unlike the associations that were found for CSF A beta 1 - 42. APOE4 carriership showed no significant correlations with the connectivity measures.

关键词： Resting state fMRI Dynamic functional connectivity computational modeling Alzheimer's disease Biomarkers

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Membrane proteins structures: A review on computational modeling tools

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BIOCHIMICA ET BIOPHYSICA ACTA-BIOMEMBRANES 2017年第10期1859卷 2021-2039页

作者： Almeida, Jose G. Preto, Antonio J. Koukos, Panagiotis I. Bonvin, Alexandre M. J. J. Moreira, Irina S. Univ Coimbra CNC Ctr Neurosci & Cell Biol FMUC Rua LargaPolo 11 Andar P-3004517 Coimbra Portugal Univ Utrecht Bijvoet Ctr Biomol Res Fac Sci Chem Padualaan 8 NL-3584 CH Utrecht Netherlands

Background: Membrane proteins (MPs) play diverse and important functions in living organisms. They constitute 20% to 30% of the known bacterial, archaean and eukaryotic organisms' genomes. In humans, their importance is emphasized as they represent 50% of all known drug targets. Nevertheless, experimental determination of their three-dimensional (3D) structure has proven to be both time consuming and rather expensive, which has led to the development of computational algorithms to complement the available experimental methods and provide valuable insights. Scope of review: This review highlights the importance of membrane proteins and how computational methods are capable of overcoming challenges associated with their experimental characterization. It covers various MP structural aspects, such as lipid interactions, allostery, and structure prediction, based on methods such as Molecular Dynamics (MD) and Machine-Learning (ML). Major conclusions: Recent developments in algorithms, tools and hybrid approaches, together with the increase in both computational resources and the amount of available data have resulted in increasingly powerful and trustworthy approaches to model MPs. General significance: Even though MPs are elementary and important in nature, the determination of their 3D structure has proven to be a challenging endeavor. computational methods provide a reliable alternative to experimental methods. In this review, we focus on computational techniques to determine the 3D structure of MP and characterize their binding interfaces. We also summarize the most relevant databases and software programs available for the study of MPs. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Membrane proteins computational modeling Machine-learning Transporters GPCRs

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Reaction dynamics analysis of a reconstituted Escherichia coli protein translation system by computational modeling

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PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 2017年第8期114卷 E1336-E1344页

作者： Matsuura, Tomoaki Tanimura, Naoki Hosoda, Kazufumi Yomo, Tetsuya Shimizu, Yoshihiro Osaka Univ Grad Sch Engn Dept Biotechnol Suita Osaka 5650871 Japan Mizuho Informat & Res Inst Sci Solut Div Chiyoda Ku Tokyo 1018443 Japan Osaka Univ Inst Acad Initiat Humanware Innovat Program Suita Osaka 5650871 Japan Osaka Univ Grad Sch Informat & Sci Dept Bioinformat Engn Suita Osaka 5650871 Japan RIKEN Quantitat Biol Ctr Lab Cell Free Prot Synth Suita Osaka 5650874 Japan

To elucidate the dynamic features of a biologically relevant large-scale reaction network, we constructed a computational model of minimal protein synthesis consisting of 241 components and 968 reactions that synthesize theMet-Gly-Gly (MGG) peptide based on an Escherichia colibased reconstituted in vitro protein synthesis system. We performed a simulation using parameters collected primarily from the literature and found that the rate of MGG peptide synthesis becomes nearly constant in minutes, thus achieving a steady state similar to experimental observations. In addition, concentration changes to 70% of the components, including intermediates, reached a plateau in a few minutes. However, the concentration change of each component exhibits several temporal plateaus, or a quasi-stationary state (QSS), before reaching the final plateau. To understand these complex dynamics, we focused on whether the components reached a QSS, mapped the arrangement of components in a QSS in the entire reaction network structure, and investigated time-dependent changes. We found that components in a QSS form clusters that grow over time but not in a linear fashion, and that this process involves the collapse and regrowth of clusters before the formation of a final large single cluster. These observations might commonly occur in other largescale biological reaction networks. This developed analysis might be useful for understanding large-scale biological reactions by visualizing complex dynamics, thereby extracting the characteristics of the reaction network, including phase transitions.

关键词： computational modeling protein translation cell-free protein synthesis quasi-stationary state network analysis

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