Are Si-C bonds formed in the environment and/or in technical microbiological systems?

Organosiloxanes are industrially produced worldwide in millions of tons per annum and are widely used by industry, professionals, and consumers. Some of these compounds are PBT (persistent, biaccumulative and toxic) or vPvB (very persistent and very bioaccumulative). If organosiloxanes react at all in the environment, Si-O bonds are hydrolyzed or Si-C bonds are oxidatively cleaved, to result finally in silica and carbon dioxide. In strong contrast and very unexpectedly, recently formation of new Si-CH3 bonds from siloxanes and methane by the action of microorganisms under mild ambient conditions was proposed (in landfills or digesters) and even reported (in a biotrickling filter, 30 °C). This is very surprising in view of the harsh conditions required in industrial Si-CH3 synthesis. Here, we scrutinized the pertinent papers, with the result that evidence put forward for Si-C bond formation from siloxanes and methane in technical microbiological systems is invalid, suggesting such reactions will not occur in the environment where they are even less favored by conditions. The claim of such reactions followed from erroneous calculations and misinterpretation of experimental results. We propose an alternative explanation of the experimental observations, i.e., the putative observation of such reactions was presumably due to confusion of two compounds, hexamethyldisiloxane and dimethylsilanediol, that elute at similar retention times from standard GC columns.

Are Si-C bonds cleaved by microorganisms? A critical review on biodegradation of methylsiloxanes.

Methylsiloxanes, compounds that contain H3C-Si-O subunits in their molecular structure, are emerging ubiquitous pollutants now detected in many environmental compartments. These compounds and generally Si-C bonds do not occur in living nature, but are industrially produced worldwide in millions of tons per annum and are widely used, resulting in their release to the environment. It is an open question whether or to what extent microorganisms are able to decompose these compounds. The presence of methylsiloxanes in many biogases adds to the economic relevance of this question. We here review and critically discuss, for the first time, the evidence obtained for and against degradation of methylsiloxanes by microorganisms, and in particular for microbial cleavage of Si-CH3 bonds. As a result, no convincing demonstration of Si-C cleavage by native environmental microorganisms has been found.

Biodegradation tests of mercaptocarboxylic acids, their esters, related divalent sulfur compounds and mercaptans.

Mercaptocarboxylic acids and their esters, a class of difunctional compounds bearing both a mercapto and a carboxylic acid or ester functional group, are industrial chemicals of potential environmental concern. Biodegradation of such compounds was systematically investigated here, both by literature search and by experiments (Closed Bottle Test OECD 301D and Manometric Respirometry Test OECD 301F). These compounds were found either readily biodegradable or at least biodegradable to a significant extent. Some related compounds of divalent sulfur were tested for comparison (mercaptans, sulfides, disulfides). For the two relevant monofunctional compound classes, carboxylic acids/esters and mercaptans, literature data were compiled, and by comparison with structurally similar compounds without these functional groups, the influence of COOH/COOR' and SH groups on biodegradability was evaluated. Thereby, an existing rule of thumb for biodegradation of carboxylic acids/esters was supported by experimental data, and a rule of thumb could be formulated for mercaptans. Concurrent to biodegradation, abiotic processes were observed in the experiments, rapid oxidative formation of disulfides (dimerisation of monomercaptans and cyclisation of dimercaptans) and hydrolysis of esters. Some problems that compromise the reproducibility of biodegradation test results were discussed.

Octanol-Water Partition Coefficient Measurement by a Simple 1H NMR Method.

We describe a simple miniature shake-flask method to measure the octanol-water partition coefficient of an organic compound. Partition between water and octanol is performed in an NMR tube; the aqueous phase is analyzed by 1H NMR spectroscopy using a benchtop low-field NMR instrument. Neither pre-equilibration of solvents nor isolation of the two phases is required. The procedure is fast and easy enough to be used in a students' laboratory. Scope and limitations as well as possible sources of error are discussed in detail.

Strategies and First Advances in the Development of Prevascularized Bone Implants.

Despite the great regenerative potential of human bone, large bone defects are a serious condition. Commonly, large defects are caused by trauma, bone disease, malignant tumor removal, and infection or medication-related osteonecrosis. Large defects necessitate clinical treatment in the form of autologous bone transplantation or implantation of biomaterials as well as the application of other available methods that enhance bone defect repair. The development and application of prevascularized bone implants are closely related to the development animal models and require dedicated methods in order to reliably predict possible clinical outcomes and the efficacy of implants. Cell sheet engineering, 3D-printing, arteriovenous loops, and naturally derived decellularized scaffolds and their respective testings in animal models are presented as alternative to the autologous bone graft in this article.

A first vascularized skin equivalent as an alternative to animal experimentation.

Tissue-engineered skin equivalents mimic key aspects of the human skin, and can thus be employed as wound coverage for large skin defects or as in vitro test systems as an alternative to animal models. However, current skin equivalents lack a functional vasculature limiting clinical and research applications. This study demonstrates the generation of a vascularized skin equivalent with a perfused vascular network by combining a biological vascularized scaffold (BioVaSc) based on a decellularized segment of a porcine jejunum and a tailored bioreactor system. Briefly, the BioVaSc was seeded with human fibroblasts, keratinocytes, and human microvascular endothelial cells. After 14 days at the air-liquid interface, hematoxylin & eosin and immunohistological staining revealed a specific histological architecture representative of the human dermis and epidermis including a papillary-like architecture at the dermal-epidermal-junction. The formation of the skin barrier was measured non-destructively using impedance spectroscopy. Additionally, endothelial cells lined the walls of the formed vessels that could be perfused with a physiological volume flow. Due to the presence of a complex in-vivo-like vasculature, the here shown skin equivalent has the potential for skin grafting and represents a sophisticated in vitro model for dermatological research.

y-Randomization and its variants in QSPR/QSAR.

y-Randomization is a tool used in validation of QSPR/QSAR models, whereby the performance of the original model in data description (r2) is compared to that of models built for permuted (randomly shuffled) response, based on the original descriptor pool and the original model building procedure. We compared y-randomization and several variants thereof, using original response, permuted response, or random number pseudoresponse and original descriptors or random number pseudodescriptors, in the typical setting of multilinear regression (MLR) with descriptor selection. For each combination of number of observations (compounds), number of descriptors in the final model, and number of descriptors in the pool to select from, computer experiments using the same descriptor selection method result in two different mean highest random r2 values. A lower one is produced by y-randomization or a variant likewise based on the original descriptors, while a higher one is obtained from variants that use random number pseudodescriptors. The difference is due to the intercorrelation of real descriptors in the pool. We propose to compare an original model's r2 to both of these whenever possible. The meaning of the three possible outcomes of such a double test is discussed. Often y-randomization is not available to a potential user of a model, due to the values of all descriptors in the pool for all compounds not being published. In such cases random number experiments as proposed here are still possible. The test was applied to several recently published MLR QSAR equations, and cases of failure were identified. Some progress also is reported toward the aim of obtaining the mean highest r2 of random pseudomodels by calculation rather than by tedious multiple simulations on random number variables.

Molecules in silico: a graph description of chemical reactions.

A general mathematical description, mostly in terms of graph theory, is given for reactions of organic chemistry. The corresponding computer program generates all products that can result from a given set of starting materials interacting according to a given set of reaction schemes. Example reactions from combinatorial chemistry, synthetic organic chemistry, and mass spectroscopic structure elucidation are considered in detail.

Sulfonylureas and glinides exhibit peroxisome proliferator-activated receptor gamma activity: a combined virtual screening and biological assay approach.

Most drugs currently employed in the treatment of type 2 diabetes either target the sulfonylurea receptor stimulating insulin release (sulfonylureas, glinides), or target the peroxisome proliferator-activated receptor (PPARgamma) improving insulin resistance (thiazolidinediones). Our work shows that sulfonylureas and glinides additionally bind to PPARgamma and exhibit PPARgamma agonistic activity. This activity was predicted in silico by virtual screening and confirmed in vitro in a binding assay, a transactivation assay, and by measuring the expression of PPARgamma target genes. Among the measured compounds, gliquidone and glipizide (two sulfonylureas), as well as nateglinide (a glinide), exhibit PPARgamma agonistic activity at concentrations comparable with those reached under pharmacological treatment. The most active of these compounds, gliquidone, is shown to be as potent as pioglitazone at inducing PPARgamma target gene expression. This dual mode of action of sulfonylureas and glinides may open new perspectives for the molecular pharmacology of antidiabetic drugs, because it provides evidence that drugs can be designed that target both the sulfonylurea receptor and PPARgamma. Targeting both receptors could increase pancreatic insulin secretion and improve insulin resistance. Glinides, sulfonylureas, and other acidified sulfonamides may be promising leads in the development of new PPARgamma agonists. In addition, we provide a unified concept of the PPARgamma binding ability of seemingly disparate compound classes.

2D QSAR of PPARgamma agonist binding and transactivation.

Multilinear QSAR models are developed for the largest and most diverse set of PPARgamma agonists treated hitherto. Binding of these small molecules to the human nuclear receptor PPARgamma is described by models that are built on simple 2D molecular descriptors and nevertheless are of good quality and predictive power (e.g., 144 compounds, 10 descriptors, r2=0.79, r2(cv)=0.76). The models presented are thoroughly validated by crossvalidation, randomization experiments, bootstrapping, and training set/test set partitioning. They may therefore be helpful in the design of new antidiabetic drug candidates. For gene transactivation, the functional activity of the agonists, a corresponding model for a similarly diverse compound set is of somewhat lower statistical quality.

QSPR using MOLGEN-QSPR: the challenge of fluoroalkane boiling points.

By means of the new software MOLGEN-QSPR, a multilinear regression model for the boiling points of lower fluoroalkanes is established. The model is based exclusively on simple descriptors derived directly from molecular structure and nevertheless describes a broader set of data more precisely than previous attempts that used either more demanding (quantum chemical) descriptors or more demanding (nonlinear) statistical methods such as neural networks. The model's internal consistency was confirmed by leave-one-out cross-validation. The model was used to predict all unknown boiling points of fluorobutanes, and the quality of predictions was estimated by means of comparison with boiling point predictions for fluoropentanes.

QSPR using MOLGEN-QSPR: the example of haloalkane boiling points.

MOLGEN-QSPR is a software newly developed for use in quantitative structure property relationships (QSPR) work. It allows to import, to manually edit, or to generate chemical structures, to detect duplicate structures, to import or to manually input property values, to calculate the values of a broad pool of molecular descriptors, to establish QSPR equations (models), and using such models to predict unknown property values. In connection with the molecule generator MOLGEN, MOLGEN-QSPR is able to predict property values for all compounds in a predetermined structure space (inverse QSPR). Some of the features of MOLGEN-QSPR are demonstrated on the example of haloalkane boiling points. The data basis used here is broader than in previous studies, and the models established are both more precise and simpler than those previously reported.

Manual construction and mathematics- and computer-aided counting of stereoisomers. The example of oligoinositols.

Two methods to obtain numbers of stereoisomers and of achiral stereoisomers of a given molecular structure are detailed on the example of di- and triinositols. The first method is manual exhaustive construction free of redundance of all stereoisomers, which is rendered feasible by symmetry considerations despite the large number of isomeric triinositols (82176). The second method is counting without constructing, made possible by use of a mathematical tool, the Cauchy-Frobenius lemma, which actually is a formalized manner of considering symmetry. The results are compared to those obtained by computer-aided stereoisomer generation using the program MOLGEN 3.5. It is demonstrated that in their results all three methods agree.

Organic synthesis--art or science?

The LHASA rules for finding strategic bonds in polycyclic target structures are analyzed with respect to the following question: Do the strategic bonds tend to give the greatest simplification upon disconnection, as measured by recently introduced indices of molecular complexity? The answer is yes, at least for the more general rules. This result implies that the bonds most useful for retrosynthetic disconnection can now be identified by a simple calculation rather than by application of a body of rules. It is concluded that organic synthesis, as far as described by these rules, has a mathematical basis and consequently can be considered a science as well as an art.

MOLGEN-CID--A canonizer for molecules and graphs accessible through the Internet.

The MOLGEN Chemical Identifier MOLGEN-CID is a software module freely accessible via the Internet. For a molecule or graph entered in molfile format (2D) it produces, by a canonical renumbering procedure, a canonical molfile and a unique character string that is easily compared by computer to a similar string. The mode of operation of MOLGEN-CID is detailed and visualized with examples.

Walking backward: walk counts of negative order.

A closed formula is derived for walk counts of negative order k in a graph or molecule, as defined recently by Lukovits and Trinajstic. Some unexpected observations made by these authors easily follow from this formula. Gratifyingly, the formula is very similar to the one obtained earlier for usual walk counts. Moreover, while for walk counts of k --> + infinity the numerically largest eigenvalue of the adjacency matrix plays an important part, for walk counts of k --> - infinity the numerically smallest eigenvalue plays a corresponding part.

Exploring the limits of graph invariant- and spectrum-based discrimination of (sub)structures.

The limits of a recently proposed computer method for finding all distinct substructures of a chemical structure are systematically explored within comprehensive graph samples which serve as supersets of the graphs corresponding to saturated hydrocarbons, both acyclic (up to n = 20) and (poly)cyclic (up to n = 10). Several pairs of smallest graphs and compounds are identified that cannot be distinguished using selected combinations of invariants such as combinations of Balaban's index J and graph matrix eigenvalues. As the most important result, it can now be stated that the computer program NIMSG, using J and distance eigenvalues, is safe within the domain of mono- through tetracyclic saturated hydrocarbon substructures up to n = 10 (oligocyclic decanes) and of all acyclic alkane substructures up to n = 19 (nonadecanes), i.e., it will not miss any of these substructures. For the regions surrounding this safe domain, upper limits are found for the numbers of substructures that may be lost in the worst case, and these are low. This taken together means that the computer program can be reasonably employed in chemistry whenever one is interested in finding the saturated hydrocarbon substructures. As to unsaturated and heteroatom containing substructures, there are reasons to conjecture that the method's resolving power for them is similar.