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1.
BMC Bioinformatics ; 23(1): 370, 2022 Sep 10.
Artigo em Inglês | MEDLINE | ID: mdl-36088285

RESUMO

BACKGROUND: Development of new methods for analysis of protein-protein interactions (PPIs) at molecular and nanometer scales gives insights into intracellular signaling pathways and will improve understanding of protein functions, as well as other nanoscale structures of biological and abiological origins. Recent advances in computational tools, particularly the ones involving modern deep learning algorithms, have been shown to complement experimental approaches for describing and rationalizing PPIs. However, most of the existing works on PPI predictions use protein-sequence information, and thus have difficulties in accounting for the three-dimensional organization of the protein chains. RESULTS: In this study, we address this problem and describe a PPI analysis based on a graph attention network, named Struct2Graph, for identifying PPIs directly from the structural data of folded protein globules. Our method is capable of predicting the PPI with an accuracy of 98.89% on the balanced set consisting of an equal number of positive and negative pairs. On the unbalanced set with the ratio of 1:10 between positive and negative pairs, Struct2Graph achieves a fivefold cross validation average accuracy of 99.42%. Moreover, Struct2Graph can potentially identify residues that likely contribute to the formation of the protein-protein complex. The identification of important residues is tested for two different interaction types: (a) Proteins with multiple ligands competing for the same binding area, (b) Dynamic protein-protein adhesion interaction. Struct2Graph identifies interacting residues with 30% sensitivity, 89% specificity, and 87% accuracy. CONCLUSIONS: In this manuscript, we address the problem of prediction of PPIs using a first of its kind, 3D-structure-based graph attention network (code available at https://github.com/baranwa2/Struct2Graph ). Furthermore, the novel mutual attention mechanism provides insights into likely interaction sites through its unsupervised knowledge selection process. This study demonstrates that a relatively low-dimensional feature embedding learned from graph structures of individual proteins outperforms other modern machine learning classifiers based on global protein features. In addition, through the analysis of single amino acid variations, the attention mechanism shows preference for disease-causing residue variations over benign polymorphisms, demonstrating that it is not limited to interface residues.


Assuntos
Algoritmos , Proteínas , Sequência de Aminoácidos , Aminoácidos , Aprendizado de Máquina , Proteínas/química
2.
J Chem Phys ; 156(12): 124705, 2022 Mar 28.
Artigo em Inglês | MEDLINE | ID: mdl-35364875

RESUMO

Understanding and controlling the energy transfer between silicon nanocrystals is of significant importance for the design of efficient optoelectronic devices. However, previous studies on silicon nanocrystal energy transfer were limited because of the strict requirements to precisely control the inter-dot distance and to perform all measurements in air-free environments to preclude the effect of ambient oxygen. Here, we systematically investigate the distance-dependent resonance energy transfer in alkyl-terminated silicon nanocrystals for the first time. Silicon nanocrystal solids with inter-dot distances varying from 3 to 5 nm are fabricated by varying the length and surface coverage of alkyl ligands in solution-phase and gas-phase functionalized silicon nanocrystals. The inter-dot energy transfer rates are extracted from steady-state and time-resolved photoluminescence measurements, enabling a direct comparison to theoretical predictions. Our results reveal that the distance-dependent energy transfer rates in Si NCs decay faster than predicted by the Förster mechanism, suggesting higher-order multipole interactions.

3.
Chirality ; 34(12): 1494-1502, 2022 12.
Artigo em Inglês | MEDLINE | ID: mdl-36221174

RESUMO

Chiral carbon nanoparticles (CNPs) represent a rapidly evolving area of research for optical and biomedical technologies. Similar to small molecules, applications of CNPs as well as fundamental relationships between their optical activity and structural asymmetry would greatly benefit from their enantioselective separations by chromatography. However, this technique remains in its infancy for chiral carbon and other nanoparticles. The possibility of effective separations using high performance liquid chromatography (HPLC) with chiral stationary phases remains an open question whose answer can also shed light on the components of multiscale chirality of the nanoparticles. Herein, we report a detailed methodology of HPLC for successful separation of chiral CNPs and establish a path for its future optimization. A mobile phase of water/acetonitrile was able to achieve chiral separation of CNPs derived from L- and D-cysteine denoted as L-CNPs and D-CNPs. Molecular dynamics simulations show that the teicoplanin-based stationary phase has a higher affinity for L-CNPs than for D-CNPs, in agreement with experiments. The experimental and computational findings jointly indicate that chiral centers of chiral CNPs are present at their surface, which is essential for the multiple applications of these chiral nanostructures and equally essential for interactions with biomolecules and circularly polarized photons.


Assuntos
Nanopartículas , Teicoplanina , Estereoisomerismo , Teicoplanina/química , Cromatografia Líquida de Alta Pressão/métodos , Carbono/química , Nanopartículas/química
4.
Bioinformatics ; 36(8): 2547-2553, 2020 04 15.
Artigo em Inglês | MEDLINE | ID: mdl-31879763

RESUMO

MOTIVATION: Understanding the mechanisms and structural mappings between molecules and pathway classes are critical for design of reaction predictors for synthesizing new molecules. This article studies the problem of prediction of classes of metabolic pathways (series of chemical reactions occurring within a cell) in which a given biochemical compound participates. We apply a hybrid machine learning approach consisting of graph convolutional networks used to extract molecular shape features as input to a random forest classifier. In contrast to previously applied machine learning methods for this problem, our framework automatically extracts relevant shape features directly from input SMILES representations, which are atom-bond specifications of chemical structures composing the molecules. RESULTS: Our method is capable of correctly predicting the respective metabolic pathway class of 95.16% of tested compounds, whereas competing methods only achieve an accuracy of 84.92% or less. Furthermore, our framework extends to the task of classification of compounds having mixed membership in multiple pathway classes. Our prediction accuracy for this multi-label task is 97.61%. We analyze the relative importance of various global physicochemical features to the pathway class prediction problem and show that simple linear/logistic regression models can predict the values of these global features from the shape features extracted using our framework. AVAILABILITY AND IMPLEMENTATION: https://github.com/baranwa2/MetabolicPathwayPrediction. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.


Assuntos
Aprendizado Profundo , Redes Neurais de Computação , Aprendizado de Máquina , Redes e Vias Metabólicas , Software
5.
Phys Chem Chem Phys ; 23(7): 4326-4333, 2021 Feb 25.
Artigo em Inglês | MEDLINE | ID: mdl-33587735

RESUMO

An important step in predicting the growth of soot nanoparticles is understanding how gas phase variations affect the formation of their aromatic precursors. Once formed, these aromatic structures begin to assemble into nanoparticles and, regardless of the clustering process, the molecular properties of the aromatic precursors play an important role. Leveraging existing experimental data collected from a coflow Jet A-1 surrogate diffusion flame, in this paper we report on a detailed study of the spatial evolution of molecular structures of polycyclic aromatic compounds (PACs) and their corresponding formation pathways. To this end, we employed the SNapS2 kinetic Monte Carlo software to simulate the chemical evolution of PACs along multiple streamlines. The results show that growth only occurs along streamlines that traverse regions of high acetylene concentrations in the center of the flame. The PACs predicted in various conditions show diverse chemical properties, including aliphatic chains, five-membered, and heteroaromatic rings. PACs in streamlines close to the flame wings begin growing immediately due to the high temperature and large amounts of radical species, while PACs originating along inner streamlines do not appreciably grow until they pass through an area characterized by high radical concentrations. Using graph theory and network analysis, we investigated the complex reaction network generated by SNapS2 and determined that the growth pathways of many PACs center around a few stable structures that also promote oxygen addition reactions due to their morphology and long lifetimes. These pathways play a more significant role along streamlines near the centerline, compared to the flame wings, which show more variety due to the highly reactive environment encountered during early growth. The results of this study provide insights on the reaction pathways that determine the properties of PACs at different flame locations as well as information on the chemical characteristics of the formed PACs, with emphasis on oxygenated structures.

6.
Fuel (Lond) ; 2832021 Jan 01.
Artigo em Inglês | MEDLINE | ID: mdl-33446939

RESUMO

The 16th International Congress on Combustion By-Products and their Health Effects (PIC2019) was held in Ann Arbor, Michigan, from July 10 to 12, 2019. For the last 28 years, this conference has served as an interdisciplinary platform for the discussion of the formation, environmental fate, health effects, policy, and remediation of combustion by-products. The technical areas for PIC2019 included mobile and stationary sources in urban environments, open fires, indoor air pollution, and halogenated pollutants. The congress was sponsored by the National Institute of Environmental Health Sciences (NIEHS), the U.S. EPA, the School of Public Health at the University of Michigan, the Civil and Environmental Engineering Department at the University of Michigan, the Mechanical Engineering Department at the University of Michigan, the Aerospace Engineering Department at the University of Michigan, and the Climate and Space Sciences and Engineering Department at the University of Michigan. Special features of the conference included a career path and round table discussion on translating research and engaging communities.

7.
Proc Natl Acad Sci U S A ; 113(30): 8374-9, 2016 07 26.
Artigo em Inglês | MEDLINE | ID: mdl-27410045

RESUMO

Many oxygenated hydrocarbon species formed during combustion, such as furans, are highly toxic and detrimental to human health and the environment. These species may also increase the hygroscopicity of soot and strongly influence the effects of soot on regional and global climate. However, large furans and associated oxygenated species have not previously been observed in flames, and their formation mechanism and interplay with polycyclic aromatic hydrocarbons (PAHs) are poorly understood. We report on a synergistic computational and experimental effort that elucidates the formation of oxygen-embedded compounds, such as furans and other oxygenated hydrocarbons, during the combustion of hydrocarbon fuels. We used ab initio and probabilistic computational techniques to identify low-barrier reaction mechanisms for the formation of large furans and other oxygenated hydrocarbons. We used vacuum-UV photoionization aerosol mass spectrometry and X-ray photoelectron spectroscopy to confirm these predictions. We show that furans are produced in the high-temperature regions of hydrocarbon flames, where they remarkably survive and become the main functional group of oxygenates that incorporate into incipient soot. In controlled flame studies, we discovered ∼100 oxygenated species previously unaccounted for. We found that large alcohols and enols act as precursors to furans, leading to incorporation of oxygen into the carbon skeletons of PAHs. Our results depart dramatically from the crude chemistry of carbon- and oxygen-containing molecules previously considered in hydrocarbon formation and oxidation models and spearhead the emerging understanding of the oxidation chemistry that is critical, for example, to control emissions of toxic and carcinogenic combustion by-products, which also greatly affect global warming.


Assuntos
Poluentes Atmosféricos/análise , Incêndios , Furanos/química , Hidrocarbonetos/química , Oxigênio/química , Aerossóis/análise , Carbono/análise , Biologia Computacional/métodos , Espectrometria de Massas/métodos , Estrutura Molecular , Espectroscopia Fotoeletrônica/métodos , Hidrocarbonetos Policíclicos Aromáticos/análise , Fumaça/análise , Fuligem/análise
8.
J Phys Chem A ; 121(23): 4475-4485, 2017 Jun 15.
Artigo em Inglês | MEDLINE | ID: mdl-28521094

RESUMO

We present a critical evaluation of photoionization efficiency (PIE) measurements coupled with aerosol mass spectrometry for the identification of condensed soot-precursor species extracted from a premixed atmospheric-pressure ethylene/oxygen/nitrogen flame. Definitive identification of isomers by any means is complicated by the large number of potential isomers at masses likely to comprise particles at flame temperatures. This problem is compounded using PIE measurements by the similarity in ionization energies and PIE-curve shapes among many of these isomers. Nevertheless, PIE analysis can provide important chemical information. For example, our PIE curves show that neither pyrene nor fluoranthene alone can describe the signal from C16H10 isomers and that coronene alone cannot describe the PIE signal from C24H12 species. A linear combination of the reference PIE curves for pyrene and fluoranthene yields good agreement with flame-PIE curves measured at 202 u, which is consistent with pyrene and fluoranthene being the two major C16H10 isomers in the flame samples, but does not provide definite proof. The suggested ratio between fluoranthene and pyrene depends on the sampling conditions. We calculated the values of the adiabatic-ionization energy (AIE) of 24 C16H10 isomers. Despite the small number of isomers considered, the calculations show that the differences in AIEs between several of the isomers can be smaller than the average thermal energy at room temperature. The calculations also show that PIE analysis can sometimes be used to separate hydrocarbon species into those that contain mainly aromatic rings and those that contain significant aliphatic content for species sizes investigated in this study. Our calculations suggest an inverse relationship between AIE and the number of aromatic rings. We have demonstrated that further characterization of precursors can be facilitated by measurements that test species volatility.

9.
J Phys Chem A ; 121(23): 4447-4454, 2017 Jun 15.
Artigo em Inglês | MEDLINE | ID: mdl-28521096

RESUMO

We have measured photoionization-efficiency curves for pyrene, fluoranthene, chrysene, perylene, and coronene in the photon energy range of 7.5-10.2 eV and derived their photoionization cross-section curves in this energy range. All measurements were performed using tunable vacuum ultraviolet (VUV) radiation generated at the Advanced Light Source synchrotron at Lawrence Berkeley National Laboratory. The VUV radiation was used for photoionization, and detection was performed using a time-of-flight mass spectrometer. We measured the photoionization efficiency of 2,5-dimethylfuran simultaneously with those of pyrene, fluoranthene, chrysene, perylene, and coronene to obtain references of the photon flux during each measurement from the known photoionization cross-section curve of 2,5-dimethylfuran.

10.
Phys Chem Chem Phys ; 16(17): 7969-79, 2014 May 07.
Artigo em Inglês | MEDLINE | ID: mdl-24647536

RESUMO

Nanoparticles formed in gas phase environments, such as combustion, have an important impact on society both as engineering components and hazardous pollutants. A new software package, the Stochastic Nanoparticle Simulator (SNAPS) was developed, applying a stochastic chemical kinetics methodology, to computationally investigate the growth of nanoparticle precursors through trajectories of chemical reactions. SNAPS was applied to characterize the growth of polycyclic aromatic hydrocarbons (PAHs), important precursors of carbonaceous nanoparticles and soot, in a premixed laminar benzene flame, using a concurrently developed PAH growth chemical reaction mechanism, as well as an existing benzene oxidation mechanism. Simulations of PAH ensembles successfully predicted existing experimentally measured data and provided novel insight into chemical composition and reaction pathways. The most commonly observed PAH isomers in simulations showed the importance of 5-membered rings, which contrasts with traditionally assumed compositions involving primarily pericondensed 6-membered rings. In addition, the chemical growth of PAHs involved complex sequences of highly reversible reactions, rather than relatively direct routes of additions and ring closures. Furthermore, the most common reactions involved 5-membered rings, suggesting their importance to PAH growth. The framework developed in this work will facilitate future investigation of particle inception and soot formation and will benefit engineering of novel combustion technologies to mitigate harmful emissions.

11.
J Phys Chem A ; 118(6): 1067-76, 2014 Feb 13.
Artigo em Inglês | MEDLINE | ID: mdl-24344976

RESUMO

Environmental and energy security concerns have motivated an increased focus on developing clean, efficient combustors, which increasingly relies on insight into the combustion chemistry of fuels. In particular, naphthenes (cycloalkanes and alkylcycloalkanes) are important chemical components of distillate fuels, such as diesel and jet fuels. As such, there is a growing interest in describing napthene reactivity with kinetic mechanisms. Use of these mechanisms in predictive combustion models aids in the development of combustors. This study focuses on the pyrolysis of n-butylcyclohexane (n-BCH), an important representative of naphthenes in jet fuels. Seven different unimolecular decomposition pathways of C-C bond fission were explored utilizing ab initio/DFT methods. Accurate reaction energies were computed using the high-level quantum composite G3B3 method. Variational transition state theory, Rice-Ramsperger-Kassel-Marcus/master equation simulations provided temperature- and pressure-dependent rate constants. Implementation of these pathways into an existing chemical kinetic mechanism improved the prediction of experimental OH radical and H2O speciation in shock tube oxidation. Simulations of this combustion showed a change in the expected decomposition chemistry of n-BCH, predicting increased production of cyclic alkyl radicals instead of straight-chain alkenes. The most prominent reaction pathway for the decomposition of n-BCH is n-BCH = C3H7 + C7H13. The results of this study provide insight into the combustion of n-BCH and will aid in the future development of naphthene kinetic mechanisms.

12.
J Phys Chem A ; 118(44): 10188-200, 2014 Nov 06.
Artigo em Inglês | MEDLINE | ID: mdl-25234586

RESUMO

Product formation from R + O2 reactions relevant to low-temperature autoignition chemistry was studied for 2,5-dimethylhexane, a symmetrically branched octane isomer, at 550 and 650 K using Cl-atom initiated oxidation and multiplexed photoionization mass spectrometry (MPIMS). Interpretation of time- and photon-energy-resolved mass spectra led to three specific results important to characterizing the initial oxidation steps: (1) quantified isomer-resolved branching ratios for HO2 + alkene channels; (2) 2,2,5,5-tetramethyltetrahydrofuran is formed in substantial yield from addition of O2 to tertiary 2,5-dimethylhex-2-yl followed by isomerization of the resulting ROO adduct to tertiary hydroperoxyalkyl (QOOH) and exhibits a positive dependence on temperature over the range covered leading to a higher flux relative to aggregate cyclic ether yield. The higher relative flux is explained by a 1,5-hydrogen atom shift reaction that converts the initial primary alkyl radical (2,5-dimethylhex-1-yl) to the tertiary alkyl radical 2,5-dimethylhex-2-yl, providing an additional source of tertiary alkyl radicals. Quantum-chemical and master-equation calculations of the unimolecular decomposition of the primary alkyl radical reveal that isomerization to the tertiary alkyl radical is the most favorable pathway, and is favored over O2-addition at 650 K under the conditions herein. The isomerization pathway to tertiary alkyl radicals therefore contributes an additional mechanism to 2,2,5,5-tetramethyltetrahydrofuran formation; (3) carbonyl species (acetone, propanal, and methylpropanal) consistent with ß-scission of QOOH radicals were formed in significant yield, indicating unimolecular QOOH decomposition into carbonyl + alkene + OH.


Assuntos
Hexanos/química , Temperatura , Espectrometria de Massas , Estrutura Molecular , Oxirredução , Processos Fotoquímicos , Teoria Quântica
13.
J Org Chem ; 78(12): 5898-908, 2013 Jun 21.
Artigo em Inglês | MEDLINE | ID: mdl-23679139

RESUMO

In recent years, biodiesel fuels, consisting of long-chain alkyl (methyl, ethyl, propyl) esters, have emerged as viable alternatives to petroleum-based fuels. From a combustion chemistry standpoint, there is great interest in developing accurate reaction models for these new molecules that can be used to predict their behaviors in various regimes. In this paper, we report a detailed study of the unimolecular decomposition pathways of methyl butanoate (MB), a short-chain ester that contains the basic chemical structure of biodiesel fuels. Using ab initio/DFT methods, we identified five homolytic fissions of C-C and C-O bonds and five hydrogen transfer reactions. Rate constants were determined using the G3B3 theory coupled with both variational transition state theory and Rice-Ramsperger-Kassel-Marcus/master equation simulations with hindered rotation corrections. Branching ratios in the temperature range 1500-2200 K indicate that the main pathway for thermal decomposition of MB is the reaction CH3CH2CH2C(═O)OCH3 → C2H5 + CH2C(═O)OCH3. The results, in terms of reaction pathways and rate constants, can be used for future development of mechanisms for long alkyl-chain esters.

14.
Membranes (Basel) ; 13(2)2023 Jan 21.
Artigo em Inglês | MEDLINE | ID: mdl-36837641

RESUMO

A growing body of work has linked key biological activities to the mechanical properties of cellular membranes, and as a means of identification. Here, we present a computational approach to simulate and compare the vibrational spectra in the low-THz region for mammalian and bacterial membranes, investigating the effect of membrane asymmetry and composition, as well as the conserved frequencies of a specific cell. We find that asymmetry does not impact the vibrational spectra, and the impact of sterols depends on the mobility of the components of the membrane. We demonstrate that vibrational spectra can be used to distinguish between membranes and, therefore, could be used in identification of different organisms. The method presented, here, can be immediately extended to other biological structures (e.g., amyloid fibers, polysaccharides, and protein-ligand structures) in order to fingerprint and understand vibrations of numerous biologically-relevant nanoscale structures.

15.
Phys Rev E ; 108(3-2): 035211, 2023 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-37849136

RESUMO

Finite-size effects in the static structure factor S(k) are analyzed for an amorphous substance. As the number of particles is reduced, S(0) increases greatly, up to an order of magnitude. Meanwhile, there is a decrease in the height of the first peak S_{peak}. These finite-size effects are modeled accurately by the Binder formula for S(0) and our empirical formula for S_{peak}. Procedures are suggested to correct for finite-size effects in S(k) data and in the hyperuniformity index H≡S(0)/S_{peak}. These principles generally apply to S(k) obtained from particle positions in noncrystalline substances. The amorphous substance we simulate is a two-dimensional liquid, with a soft Yukawa interaction modeling a dusty plasma experiment.

16.
Nat Comput Sci ; 3(5): 393-402, 2023 May.
Artigo em Inglês | MEDLINE | ID: mdl-38177838

RESUMO

Although challenging, the accurate and rapid prediction of nanoscale interactions has broad applications for numerous biological processes and material properties. While several models have been developed to predict the interaction of specific biological components, they use system-specific information that hinders their application to more general materials. Here we present NeCLAS, a general and efficient machine learning pipeline that predicts the location of nanoscale interactions, providing human-intelligible predictions. NeCLAS outperforms current nanoscale prediction models for generic nanoparticles up to 10-20 nm, reproducing interactions for biological and non-biological systems. Two aspects contribute to these results: a low-dimensional representation of nanoparticles and molecules (to reduce the effect of data uncertainty), and environmental features (to encode the physicochemical neighborhood at multiple scales). This framework has several applications, from basic research to rapid prototyping and design in nanobiotechnology.


Assuntos
Nanopartículas , Humanos , Nanopartículas/química , Proteínas/química
17.
Commun Chem ; 6(1): 223, 2023 Oct 16.
Artigo em Inglês | MEDLINE | ID: mdl-37845500

RESUMO

Polycyclic aromatic hydrocarbons are the main precursors to soot particles in combustion systems. A lack of direct experimental evidence has led to controversial theoretical explanations for the transition from gas-phase species to organic soot clusters. This work focuses on sampling infant soot particles from well-defined flames followed by analysis using state-of-the-art mass spectrometry. We found that PAH molecules present in soot particles are all stabilomers. Kinetic Monte Carlo simulations and thermodynamic stability calculations further identify the detected PAHs as peri-condensed and without aliphatic chains. Van der Waals forces can easily link PAHs of such size and shape to form PAH dimers and larger clusters under the specified flame conditions. Our results provide direct experimental evidence that soot inception is initiated by a physical process under typical flame conditions. This work improves our understanding of aerosol particulates, which has implications for their environmental and climate change impacts.

18.
Phys Rev E ; 106(5-2): 055212, 2022 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-36559416

RESUMO

Especially small values of the static structure factor S(k) at long wavelengths, i.e., small k, were obtained in an analysis of experimental data, for a two-dimensional dusty plasma in its liquid state. For comparison, an analysis of S(k) data was carried out for many previously published experiments with other liquids. The latter analysis indicates that the magnitude of S(k) at small k is typically in a range 0.02-0.13. In contrast, the corresponding value for a dusty plasma liquid was found to be as small as 0.0139. Another basic finding for the dusty plasma liquid is that S(k) at small k generally increases with temperature, with its lowest value, noted above, occurring near the melting point. Simulations were carried out for the dusty plasma liquid, and their results are generally consistent with the experiment. Since a dusty plasma has a soft interparticle interaction, our findings support earlier theoretical suggestions that a useful design strategy for creating materials having exceptionally low values of S(0), so-called hyperuniform materials, is the use of a condensed material composed of particles that interact softly at their periphery.

19.
Nat Comput Sci ; 2(4): 243-252, 2022 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-38177552

RESUMO

Biomimetic nanoparticles are known to serve as nanoscale adjuvants, enzyme mimics and amyloid fibrillation inhibitors. Their further development requires better understanding of their interactions with proteins. The abundant knowledge about protein-protein interactions can serve as a guide for designing protein-nanoparticle assemblies, but the chemical and biological inputs used in computational packages for protein-protein interactions are not applicable to inorganic nanoparticles. Analysing chemical, geometrical and graph-theoretical descriptors for protein complexes, we found that geometrical and graph-theoretical descriptors are uniformly applicable to biological and inorganic nanostructures and can predict interaction sites in protein pairs with accuracy >80% and classification probability ~90%. We extended the machine-learning algorithms trained on protein-protein interactions to inorganic nanoparticles and found a nearly exact match between experimental and predicted interaction sites with proteins. These findings can be extended to other organic and inorganic nanoparticles to predict their assemblies with biomolecules and other chemical structures forming lock-and-key complexes.

20.
J Chem Phys ; 134(4): 044537, 2011 Jan 28.
Artigo em Inglês | MEDLINE | ID: mdl-21280778

RESUMO

The accurate knowledge of transport properties of pure and mixture fluids is essential for the design of various chemical and mechanical systems that include fluxes of mass, momentum, and energy. In this study we determine the mutual diffusion coefficients of mixtures composed of heptane isomers and nitrogen using molecular dynamics (MD) simulations with fully atomistic intermolecular potential parameters, in conjunction with the Green-Kubo formula. The computed results were compared with the values obtained using the Chapman-Enskog (C-E) equation with Lennard-Jones (LJ) potential parameters derived from the correlations of state values: MD simulations predict a maximum difference of 6% among isomers while the C-E equation presents that of 3% in the mutual diffusion coefficients in the temperature range 500-1000 K. The comparison of two approaches implies that the corresponding state principle can be applied to the models, which are only weakly affected by the anisotropy of the interaction potentials and the large uncertainty will be included in its application for complex polyatomic molecules. The MD simulations successfully address the pure effects of molecular structure among isomers on mutual diffusion coefficients by revealing that the differences of the total mutual diffusion coefficients for the six mixtures are caused mainly by heptane isomers. The cross interaction potential parameters, collision diameter σ(12), and potential energy well depth ɛ(12) of heptane isomers and nitrogen mixtures were also computed from the mutual diffusion coefficients.

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