Micropatterning of Porous Silicon Films by Direct Laser Writing

In this study, we demonstrate that porous silicon films can be ablated by the pulsed nitrogen laser of a commercial MALDI mass spectrometer. The extent of laser-induced ablation was found to depend on the doping level and surface chemistry of the porous silicon film. Using direct laser writing with or without a mask, micropatterns were generated on the porous silicon surface. These micropatterns were subsequently used to guide the growth of mammalian cells including neuroblastoma. Excellent selectivity of cell growth toward the laser-ablated regions was established.

Biofuels: thinking clearly about the issues

Dr. Bruce Dale is the recipient of the 2007 Sterling B. Hendricks Memorial Lectureship Award. This perspective is based on a lecture given by Dr. Dale at the Life Sciences and Society Symposium at the University of Missouri on March 14, 2007, and the Award Address he presented for the Sterling B. Hendricks Memorial Lectureship Award at the 234th National Meeting of the American Chemical Society, in Boston, MA, on August 20, 2007.

Floating lipid bilayers deposited on chemically grafted phosphatidylcholine surfaces

Floating supported bilayers (FSBs) are new systems which have emerged over the past few years to produce supported membrane mimics, where the bilayers remain associated with the substrate, but are cushioned from the substrates constraining influence by a large hydration layer. In this paper we describe a new approach to fabricating FSBs using a chemically grafted phospholipid layer as the support for the floating membrane. The grafted lipid layer was produced using a Langmuir-Schaeffer transfer of acryloyl-functionalized lipid onto a pre-prepared substrate, with AIBN-induced cross-polymerization to permanently bind the lipids in place. A bilayer of DSPC was then deposited onto this grafted monolayer using a combination of Langmuir-Blodgett and Langmuir-Schaeffer transfer. The resulting system was characterized by neutron reflection under two water contrasts, and we show that the new system shows a hydrating layer of approximately 17.5 A in the gel phase, which is comparable to previously described FSB systems. We provide evidence that the grafted substrate is reusable after cleaning and suggest that this greatly simplifies the fabrication and characterization of FSBs compared to previous methods.

Chemical engineering challenges and investment opportunities in sustainable energy

The chemical and energy industries are transforming as they adjust to the new era of high-priced petroleum and severe global warming. As a result of the transformation, engineering challenges and investment opportunities abound. Rapid evolution and fast growth are expected in cathode and anode materials as well as polymeric electrolytes for vehicular batteries and in high-performance polymer-ceramic composites for wind turbines, fuel-efficient aircraft, and lighter and safer cars. Unique process-engineering opportunities exist in sand-oil, coal, and possibly also shale liquefaction to produce transportation fuel; and also in genetic engineering of photosynthesizing plants and other organisms for their processing into high-performance biodegradable polymers and high-value-added environmentally friendly chemicals. Also, research on the feasibility of mitigation of global warming through enhancement of CO(2) uptake by the southern oceans by fertilization with trace amounts of iron is progressing. Because chemical engineers are uniquely well trained in mathematical modeling of mass transport, flow, and mixing, and also in cost analysis, they are likely to join the oceanographers and marine biologists in this important endeavor.

Quantitative structure-property relationship studies for predicting flash points of alkanes using group bond contribution method with back-propagation neural network

Models of relationships between structure and flash point of 92 alkanes were constructed by means of artificial neural network (ANN) using group bond contribution method. Group bonds were used as molecular structure descriptors which contained information of both group property and group connectivity in molecules, and the back-propagation (BP) neural network was employed for fitting the possible nonlinear relationship existed between the structure and property. The dataset of 92 alkanes was randomly divided into a training set (62), a validation set (15) and a testing set (15). The optimal condition of the neural network was obtained by adjusting various parameters by trial-and-error. Simulated with the final optimum BP neural network [9-5-1], the results showed that the predicted flash points were in good agreement with the experimental data, with the average absolute deviation being 4.8K, and the root mean square error (RMS) being 6.86, which were shown to be more accurate than those of the multilinear regression method. The model proposed can be used not only to reveal the quantitative relation between flash points and molecular structures of alkanes, but also to predict the flash points of alkanes for chemical engineering.

Hybrid semi-parametric mathematical systems: bridging the gap between systems biology and process engineering

Systems biology is an integrative science that aims at the global characterization of biological systems. Huge amounts of data regarding gene expression, proteins activity and metabolite concentrations are collected by designing systematic genetic or environmental perturbations. Then the challenge is to integrate such data in a global model in order to provide a global picture of the cell. The analysis of these data is largely dominated by nonparametric modelling tools. In contrast, classical bioprocess engineering has been primarily founded on first principles models, but it has systematically overlooked the details of the embedded biological system. The full complexity of biological systems is currently assumed by systems biology and this knowledge can now be taken by engineers to decide how to optimally design and operate their processes. This paper discusses possible methodologies for the integration of systems biology and bioprocess engineering with emphasis on applications involving animal cell cultures. At the mathematical systems level, the discussion is focused on hybrid semi-parametric systems as a way to bridge systems biology and bioprocess engineering.

Molecular Engineering as an Approach to Design New Functional Properties of Alginate

Through enzymatic modification, we are now able to manipulate the composition and sequential nanostructures of alginate, one of the most versatile gelling polymers found in nature. Here we report the application of a set of processive polymer-modifying epimerases for the preparation of novel alginates with highly improved functional properties essential for numerous applications as gel matrices. Gels of enzymatically engineered alginate were found to be more elastic and compact, less permeable, and extremely stable under physiological conditions, offering significant advantages over native alginates. As a result, this study shows that, by controlling alginate nanostructure, its macroscopic properties can be highly controlled. The ability to tailor alginate has a great impact on the wide use of this biomaterial in industry and medicine. More importantly, this adds more knowledge to the link between polymer nanostructure and macroscopic properties and may serve as a model system for other polymer-based materials.

AllChem: generating and searching 1020 synthetically accessible structures

AllChem is a system that is intended to make practical the generation and searching of an unprecedentedly vast number ( approximately 10(20)) of synthetically accessible and medicinally relevant structures. Also, by providing possible synthetic routes to a structure along with its design rationale, AllChem encourages simultaneous consideration of both costs and benefits during each lead discovery and optimization decision, thereby promising to be effective with synthetic chemists among its primary users. AllChem is still under intensive development so the following initial description necessarily has more the character of an interim progress report than of a finished research publication.

Chemically engineered extracts as an alternative source of bioactive natural product-like compounds

The access to libraries of molecules with interesting biomolecular properties is a limiting step in the drug discovery process. By virtue of a long molecular evolution process, natural products are recognized as biologically validated starting points in structural space for library development. We introduce here a strategy to generate natural product-like libraries. A semisynthetic mixture of compounds was produced by diversification of a natural product extract through the chemical transformation of common chemical functionalities in natural products into chemical functionalities rarely found in nature. The resulting mixture showed antifungal activity against Candida albicans, whereas the starting extract did not show such activity. Bioguided fractionation led to the isolation of a previously undescribed active semisynthetic pyrazole. The result illustrates how biological activity can be generated by designed chemical diversification of a natural product mixture, and represents the proof of principle of an alternative strategy for producing natural product-like libraries from natural products libraries.

Universal scaling for polymer chain scission in turbulence

We report that previous polymer chain scission experiments in strong flows, long analyzed according to accepted laminar flow scission theories, were in fact affected by turbulence. We reconcile existing anomalies between theory and experiment with the hypothesis that the local stress at the Kolmogorov scale generates the molecular tension leading to polymer covalent bond breakage. The hypothesis yields a universal scaling for polymer scission in turbulent flows. This surprising reassessment of over 40 years of experimental data simplifies the theoretical picture of polymer dynamics leading to scission and allows control of scission in commercial polymers and genomic DNA.

Engineering plant-microbe symbiosis for rhizoremediation of heavy metals

The use of plants for rehabilitation of heavy-metal-contaminated environments is an emerging area of interest because it provides an ecologically sound and safe method for restoration and remediation. Although a number of plant species are capable of hyperaccumulation of heavy metals, the technology is not applicable for remediating sites with multiple contaminants. A clever solution is to combine the advantages of microbe-plant symbiosis within the plant rhizosphere into an effective cleanup technology. We demonstrated that expression of a metal-binding peptide (EC20) in a rhizobacterium, Pseudomonas putida 06909, not only improved cadmium binding but also alleviated the cellular toxicity of cadmium. More importantly, inoculation of sunflower roots with the engineered rhizobacterium resulted in a marked decrease in cadmium phytotoxicity and a 40% increase in cadmium accumulation in the plant root. Owing to the significantly improved growth characteristics of both the rhizobacterium and plant, the use of EC20-expressing P. putida endowed with organic-degrading capabilities may be a promising strategy to remediate mixed organic-metal-contaminated sites.

The role of molecular modeling in bionanotechnology

Molecular modeling is advocated here as a key methodology for research and development in bionanotechnology. Molecular modeling provides nanoscale images at atomic and even electronic resolution, predicts the nanoscale interaction of unfamiliar combinations of biological and inorganic materials, and evaluates strategies for redesigning biopolymers for nanotechnological uses. The methodology is illustrated in this paper through reviewing three case studies. The first one involves the use of single-walled carbon nanotubes as biomedical sensors where a computationally efficient, yet accurate, description of the influence of biomolecules on nanotube electronic properties through nanotube-biomolecule interactions was developed; this development furnishes the ability to test nanotube electronic properties in realistic biological environments. The second case study involves the use of nanopores manufactured into electronic nanodevices based on silicon compounds for single molecule electrical recording, in particular, for DNA sequencing. Here, modeling combining classical molecular dynamics, material science and device physics, described the interaction of biopolymers, e.g., DNA, with silicon nitrate and silicon oxide pores, furnished accurate dynamic images of pore translocation processes, and predicted signals. The third case study involves the development of nanoscale lipid bilayers for the study of embedded membrane proteins and cholesterol. Molecular modeling tested scaffold proteins, redesigned apolipoproteins found in mammalian plasma that hold the discoidal membranes in the proper shape, and predicted the assembly as well as final structure of the nanodiscs. In entirely new technological areas such as bionanotechnology, qualitative concepts, pictures and suggestions are sorely needed; these three case studies document that molecular modeling can serve a critical role in this respect, even though it may still fall short on quantitative precision.

The role and application of in silico docking in chemical genomics research

In silico docking techniques are being used to investigate the complementarity at the molecular level of a ligand and a protein target. As such, docking studies can be used to identify the structural features that are important for binding and for in silico screening efforts in which suitable binding partners can be identified. Here we describe a practical approach for setting up docking simulations using different docking programs. We also cover the analysis and rescoring of the obtained docking poses. Possible pitfalls in the docking studies are discussed and hints are provided to resolve commonly occurring problems.

Chemistry for chemical genomics

New methods and strategies have been developed to design and use small molecules that allow the functional dissection of molecular pathways, cells, and organisms by selective small-molecule ligands or modulators. In this overview, we are focusing on diversity aspects, design methods, and chemical synthesis strategies for the application of small molecules as tools for chemical genomics. Examples for different successful chemical-genomics strategies include the selection of diverse drug-like molecules, target family-focused compound libraries, natural-product chemistry, and diversity-oriented synthesis.

The centroidal algorithm in molecular similarity and diversity calculations on confidential datasets

Chemical structure provides exhaustive description of a compound, but it is often proprietary and thus an impediment in the exchange of information. For example, structure disclosure is often needed for the selection of most similar or dissimilar compounds. Authors propose a centroidal algorithm based on structural fragments (screens) that can be efficiently used for the similarity and diversity selections without disclosing structures from the reference set. For an increased security purposes, authors recommend that such set contains at least some tens of structures. Analysis of reverse engineering feasibility showed that the problem difficulty grows with decrease of the screen's radius. The algorithm is illustrated with concrete calculations on known steroidal, quinoline, and quinazoline drugs. We also investigate a problem of scaffold identification in combinatorial library dataset. The results show that relatively small screens of radius equal to 2 bond lengths perform well in the similarity sorting, while radius 4 screens yield better results in diversity sorting. The software implementation of the algorithm taking SDF file with a reference set generates screens of various radii which are subsequently used for the similarity and diversity sorting of external SDFs. Since the reverse engineering of the reference set molecules from their screens has the same difficulty as the RSA asymmetric encryption algorithm, generated screens can be stored openly without further encryption. This approach ensures an end user transfers only a set of structural fragments and no other data. Like other algorithms of encryption, the centroid algorithm cannot give 100% guarantee of protecting a chemical structure from dataset, but probability of initial structure identification is very small-order of 10(-40) in typical cases.

Can topological indices transmit information on properties but not on structures?

A survey of several topological indices (TIs) is provided according to the nature (integers or real numbers) of the local vertex invariants (LOVIs) and of the resulting molecular descriptor (TI). The 1st generation TIs such as the Wiener index when both the LOVIs and the TI are integers have a very high degeneracy. This fact can become an asset for the problem under discussion: when confronted with the "inverse problem" (reverse engineering) such indices lead to a combinatorial explosion of possible solutions. On the other extreme, TIs with very low degeneracy may also offer the possibility to transmit information on properties but not on structures, because they may be too difficult to lend themselves to reverse engineering in a reasonable amount of time. Several such indices are discussed: the novel second-generation index G (derived from the average distance-based connectivity index J in order to include a dependence on graph size and cyclicity), and third-generation indices such as the triplet TI denoted by DN2S(4) or the Kier-Hall index TOTOP. The intercorrelation of these indices is discussed: G is almost linearly-correlated with DN2S(4), and shows a different type of correlation with TOTOP.

Plastics from bacteria and for bacteria: poly(beta-hydroxyalkanoates) as natural, biocompatible, and biodegradable polyesters

Hence, PHB belongs to the family of poly(beta-hydroxyalkanoates), PHA, all of which are usually formed as intracellular inclusions under unbalanced growth conditions. Recently, it became of industrial interest to evaluate PHA polyesters as natural, biodegradable, and biocompatible plastics for a wide range of possible applications such as surgical sutures or packaging containers. For industrial applications, the controlled incorporation of repeating units with different chain lengths into a series of copolymers is desirable in order to produce polyesters with a range of material properties because physical and chemical characteristics depend strongly on the polymer composition. Such "tailormade" copolymers can be produced under controlled growth conditions, in that if a defined mixture of substrates for a certain type of microorganisms is supplied, a well defined and reproducible copolymer is formed.