An alignment-free measure based on physicochemical properties of amino acids for protein sequence comparison

Sequence comparison is an important topic in bioinformatics. With the exponential increase of biological sequences, the traditional protein sequence comparison methods — the alignment methods become limited, so the alignment-free methods are widely proposed in the past two decades. In this paper, we considered not only the six typical physicochemical properties of amino acids, but also their frequency and positional distribution. A 51-dimensional vector was obtained to describe the protein sequence. We got a pairwise distance matrix by computing the standardized Euclidean distance, and discriminant analysis and phylogenetic analysis can be made. The results on the Influenza A virus and ND5 datasets indicate that our method is accurate and efficient for classifying proteins and inferring the phylogeny of species.     

A group of 3D graphical representation of DNA sequences based on dual nucleotides

Based on chemical properties of the neighboring dual nucleotides, we reduce a DNA sequence into four 3D graphical representations. Associating with the eigenvalues of the introduced covariance matrix and the introduced measure of similarity, we introduce an approach to make similarity analysis of DNA sequence. © 2008 Wiley Periodicals, Inc. Int J Quantum Chem, 2008     

Physicochemical properties of SARS-CoV-2 for drug targeting,virus inactivation and attenuation,vaccine formulation and quality control

The material properties of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its proteins are discussed. We review the viral structure, size, rigidity, lipophilicity, isoelectric point, buoyant density and centrifugation conditions, stability against pH, temperature, UV light, gamma radiation, and susceptibility to various chemical agents including solvents and detergents. Possible inactivation, downstream, and formulation conditions are given including suitable buffers and some first ideas for quality-control methods. This information supports vaccine development and discussion with competent authorities during vaccine approval and is certainly related to drug-targeting strategies and hygienics. Several instructive tables are given, including the pI and grand average of hydropathicity (GRAVY) of SARS-CoV-1 and -2 proteins in comparison. SARS-CoV-1 and SARS-CoV-2 are similar in many regards, so information can often be derived. Both are unusually stable, but sensitive at their lipophilic membranes. However, since seemingly small differences can have strong effects, for example, on immunologically relevant epitope settings, unevaluated knowledge transfer from SARS-CoV-1 to SARS-CoV-2 cannot be advised. Published knowledge regarding downstream processes, formulations and quality assuring methods is, as yet, limited. However, standard approaches employed for other viruses and vaccines seem to be feasible including virus inactivation, centrifugation conditions, and the use of adjuvants.     

Sequence‐based separation of single‐stranded DNA at high salt concentrations in capillary zone electrophoresis

DNA separation by fragment length can be readily achieved using sieving gels in electrophoresis. Separation by sequence has not been as simple, generally requiring adequate differences in native or induced conformation between single or hybridized strands or differences in thermal or chemical stability of hybridized strands. Previously, it was shown that four single‐stranded DNA (ssDNA) 76‐mers that differ by only a few A‐G substitutions could be separated based solely on sequence by adding guanosine‐5’‐monophosphate to the running buffer in capillary zone electrophoresis (CZE). The separation was attributed to interactions of the ssDNA with self‐assembled guanine‐tetrad structures; however, subsequent studies of an expanded set of ten 76‐mers showed that the separation was a more general phenomenon that occurred at high salt concentrations. With the long‐term goal of using experimental and computational methods to provide insight into the basis of the separation, a set of ssDNA 15‐mers was designed including a poly(dT) 15‐mer and nine variants. Separations were performed using fluorescent‐labeled ssDNA in CZE with laser‐induced fluorescence detection. Results show that separation improves with increasing buffer concentration and decreasing temperature, due at least in part to longer separation times. Migration times increase with increasing purine content, with A having a much larger effect that G. Circular dichroism spectra of the mixtures of the strands suggest that the separation is not due to changes in conformation of the ssDNA at high salt concentrations.     

Development of multiple machine-learning computational techniques for optimization of heterogenous catalytic biodiesel production from waste vegetable oil

Multiple machine learning models were developed in this study to optimize biodiesel production from waste cooking oil in a heterogenous catalytic reaction mode. Several input parameters were considered for the model including reaction temperature, reaction time, catalyst loading, methanol/oil molar ratio, whereas the percent of biodiesel production yield was the only output. Three ensemble models were utilized in this study: Boosted Linear Regression, Boosted Multi-layer Perceptron, and Forest of Randomized Tree for optimization of the yield. We then found their optimized configurations for each model, namely hyper-parameters. This critical task is done by running more than 1000 combinations of hyper-parameters. Finally, The R²-Scores for Boosted Linear Regression, Boosted Multi-layer Perceptron, and Forest of Randomized Tree, respectively, were 0.926, 0.998, and 0.992. MAPE criterion revealed that the error rates for boosted linear regression, boosted multi-layer perceptron, and Forest of Randomized Tree was 5.68 × 10^-2, 5.20 × 10^-2, and 9.83 × 10^-2, respectively. Furthermore, utilizing the input vector (X1 = 165, X2 = 5.72, X3 = 5.55, X4 = 13.0), the proposed technique produces an ideal output value of 96.7 % as the optimum yield in catalytic production of biodiesel from waste cooking oil.     

New invariant of DNA sequence based on 3DD-curves and its application on phylogeny

The Z_inv, a new invariant based on 3DD-curves of DNA sequence, which is simple for calculation and it approximates to the leading eigenvalues of the matrix associated with DNA sequence. The utility of our invariant is illustrated on the DNA sequence of 11 species. In this study, we use the Z_inv to analyze the phylogenetic relationships for the seven HA (H5N1) sequences of avian influenza virus.     

A method for DNA detection in a microchannel: fluid dynamics phenomena and optimization of microchannel structure

A simple DNA diagnosis method using microfluidics has been developed which requires simple and straightforward procedures such as injection of sample and probe DNA solutions. This method takes advantage of the highly accurate control of fluids in microchannels, and is superior to DNA microarray diagnosis methods due to its simplicity, highly quantitative determination, and high-sensitivity. The method is capable of detecting DNA hybridization for molecules as small as a 20 mer. This suggests the difference in microfluidic behavior between single strand DNA (ssDNA) and double stranded DNA (dsDNA). In this work, influence of both the inertial force exerted on DNA molecules and the diffusion of DNA molecules was investigated. Based on the determination of these parameters for both ssDNA and dsDNA by experiments, a numerical model describing the phenomena in the microchannel was designed. Computational simulation results using this model were in good agreement with previously reported experimental results. The simulation results showed that appropriate selection of the analysis point and the design of microchannel structure are important to bring out the diffusion and inertial force effects suitably and increase the sensitivity of the detection of DNA hybridization, that is, the analytical performance of the microfluidic DNA chip.     

Process design based on physicochemical properties for the example of obtaining valuable products from plant-based extracts

Herbal ingredients for use in the food, cosmetic and pharmaceutical industry are mainly gained from plant extracts. The challenge of producing these ingredients is the economic optimization of the design for the corresponding technical processes. To achieve this goal, a systematic, model-based approach is necessary, which is not yet available for complex mixtures (Bart and Pilz, 2010 [11]). The general basis for modeling and simulation of industrial processes is the knowledge of the physical properties of the system. A cost-effective option to get hold of separation factors of mixtures is the direct characterization of the multicomponent system, which has been the subject of earlier publications (Josch et al., 2012 [2]; Josch and Strube, 2012 [3]; Bart and Pilz, 2010 [11]). In this work, a systematic approach is illustrated on how to effectively characterize complex mixtures for a first process design. In addition, physical properties for individual plant components can be determined for modeling to optimize industrial processes. For this purpose, those processes which are well established in the chemical industry, including the use of substance databases and calculation of properties by means of thermodynamic theories, will be discussed. In addition, limitations of these approaches and resulting research requirements are shown.     

Virus-sized DNA nanoparticles for gene delivery based on micelles of cationic calixarenes

Macrocyclic amphiphilic molecules based on calix[4]arenes are highly attractive for controlled supramolecular assembly of DNA into small nanoparticles, since they present a unique conical architecture and can bear multiple charged groups. In the present work, we synthesized new amphiphilic calixarenes bearing cationic groups at the upper rim and alkyl chains at the lower rim. Their self-assembly in aqueous solution was characterized by fluorescent probes, fluorescence correlation spectroscopy, dynamic light scattering, gel electrophoresis and atomic force microscopy. We found that calixarenes bearing long alkyl chains (octyl) self-assemble into micelles of 6 nm diameter at low critical micellar concentration and present the unique ability to condense DNA into small nanoparticles of about 50 nm diameter. In contrast, the short-chain (propyl) analogues that cannot form micelles at low concentrations failed to condense DNA, giving large polydisperse DNA complexes. Thus, formation of small DNA nanoparticles is hierarchical, requiring assembly of calixarenes into micellar building blocks that further co-assemble with DNA into small virus-sized particles. The latter showed much better gene transfection efficiency in cell cultures relative to the large DNA complexes with the short-chain analogues, which indicates that gene delivery of calixarene/DNA complexes depends strongly on their structure. Moreover, all cationic calixarenes studied showed low cytotoxicity. Thus, this work presents a two-step hierarchical assembly of small DNA nanoparticles for gene delivery based on amphiphilic cone-shaped cationic calixarenes.     

Evanescent fluorobiosensor for the detection of polyaromatic hydrocarbon based on DNA intercalation

A flow-injection analysis (FIA) system coupled with an evanescent wave (EW) Biosensor employing total internal reflection of fluorescence radiation (TIRF) for the detection of polyaromatic hydrocarbon that intercalates into DNA is reported. A highly fluorescent intercalator, “ethidium bromide,” has been used as the reference compound for detection. The EW Biosensor was developed according to the procedure described earlier (1,2). Data on the analysis of Naphthalene, 3-methy cholanthrene, 7,12-dimethylbenz(a)anthracene, 1,2-benzanthracene, and some standard reference materials supplied by the National Institute of Standards and Technology are reported. The relative ability of the polyaromatic hydrocarbon to displace ethidium bromide, based on the relative binding ratio, is found to be on the order of 7,12-dimethylbenz[a]anthracene > 3-methylcholanthrene > 1,2-benzanthracene > napthalene.     

Development of a new parameter optimization scheme for a reactive force field based on a machine learning approach

Reactive molecular dynamics (MD) simulation is performed using a reactive force field (ReaxFF). To this end, we developed a new method to optimize the ReaxFF parameters based on a machine learning approach. This approach combines the k-nearest neighbor and random forest regressor algorithm to efficiently locate several possible ReaxFF parameter sets. As a pilot test of the developed approach, the optimized ReaxFF parameter set was applied to perform chemical vapor deposition (CVD) of an α-Al₂O₃ crystal. The crystal structure of α-Al₂O₃ was reasonably reproduced even at a relatively high temperature (2000 K). The reactive MD simulation suggests that the (110) surface grows faster than the (0001) surface, indicating that the developed parameter optimization technique could be used for understanding the chemical reaction in the CVD process. © 2019 Wiley Periodicals, Inc.     

A simple visual method for DNA detection based on the formation of gold nanoparticles

A simple visual method for DNA detection during the formation of gold nanoparticles (AuNPs) was developed based on different electrostatic properties of single strand DNA (ssDNA) and double strand DNA (dsDNA). Since the ssDNA is easy to bind to AuNPs due to its exposed bases which could prevent salt-induced aggregation of AuNPs. The dsDNA always present negative charge because its negatively charged phosphate backbone is exposed. In this case, the dsDNA could disturb the adsorption between dsDNA and AuNPs and result in non-aggregation of AuNPs. After hybridization, chloroauric acid and ascorbic acid were added to the mixture solution, and the solution changed to red immediately and turned to purple in 10 min in the present of target DNA. TEM results confirmed that the change of color stemed from aggregation of AuNPs. In order to obtain accurate results by naked eye, the DNA detection assay should be conducted under pH 7.0.     

Effects of impregnation sequence on the microstructure and performances of Cu-Co based catalysts for the synthesis of higher alcohols

Silica-supported CuCo catalysts were prepared by impregnation method with different impregnation sequence for higher alcohols synthesis. These catalysts were characterized by H2-TPR, XRD, N2 adsorption, XPS techniques and CO selective hydrogenation reaction measurement. The effects of impregnation sequence on the structure and performance of catalysts were investigated, and there were important influences on the selectivity to higher alcohols. There was a strong synergistic effect between copper and cobalt for the co-impregnated sample. The CuCo/SiO2 catalyst prepared by co- impregnation showed a better yield of total alcohols, and a higher selectivity to total alcohols which reached 51.5%.     

A simple visual method for DNA detection based on the formation of gold nanoparticles

A simple visual method for DNA detection during the formation of gold nanoparticles (AuNPs) was developed based on different electrostatic properties of single strand DNA (ssDNA) and double strand DNA (dsDNA). It could identify target DNA in 10 min.     

Zn、Mo对CuCo基催化剂合成低碳醇性能的促进作用

采用超声辅助的反相共沉淀法制备CO加氢合成低碳醇用CuCo基催化剂,研究过渡金属Zn、Mo助剂对CuCo基催化剂结构与性能的影响,借助N2吸附（BET）、X射线衍射（XRD）、程序升温还原（H2-TPR）和程序升温脱附（CO-TPD）等测试技术对催化剂进行表征.结果表明,Zn、Mo均在一定程度上增加了催化剂的比表面积、...