Distributed Atomic Polarizabilities of Amino Acids and their Hydrogen-Bonded Aggregates

With the purpose of rational design of optical materials, distributed atomic polarizabilities of amino acid molecules and their hydrogen-bonded aggregates are calculated in order to identify the most efficient functional groups, able to buildup larger electric susceptibilities in crystals. Moreover, we carefully analyze how the atomic polarizabilities depend on the one-electron basis set or the many-electron Hamiltonian, including both wave function and density functional theory methods. This is useful for selecting the level of theory that best combines high accuracy and low computational costs, very important in particular when using the cluster method to estimate susceptibilities of molecular-based materials.

The Chemical Space Project

One of the simplest questions that can be asked about molecular diversity is how many organic molecules are possible in total? To answer this question, my research group has computationally enumerated all possible organic molecules up to a certain size to gain an unbiased insight into the entire chemical space. Our latest database, GDB-17, contains 166.4 billion molecules of up to 17 atoms of C, N, O, S, and halogens, by far the largest small molecule database reported to date. Molecules allowed by valency rules but unstable or nonsynthesizable due to strained topologies or reactive functional groups were not considered, which reduced the enumeration by at least 10 orders of magnitude and was essential to arrive at a manageable database size. Despite these restrictions, GDB-17 is highly relevant with respect to known molecules. Beyond enumeration, understanding and exploiting GDBs (generated databases) led us to develop methods for virtual screening and visualization of very large databases in the form of a “periodic system of molecules” comprising six different fingerprint spaces, with web-browsers for nearest neighbor searches, and the MQN- and SMIfp-Mapplet application for exploring color-coded principal component maps of GDB and other large databases. Proof-of-concept applications of GDB for drug discovery were realized by combining virtual screening with chemical synthesis and activity testing for neurotransmitter receptor and transporter ligands. One surprising lesson from using GDB for drug analog searches is the incredible depth of chemical space, that is, the fact that millions of very close analogs of any molecule can be readily identified by nearest-neighbor searches in the MQN-space of the various GDBs. The chemical space project has opened an unprecedented door on chemical diversity. Ongoing and yet unmet challenges concern enumerating molecules beyond 17 atoms and synthesizing GDB molecules with innovative scaffolds and pharmacophores.

Mechanistic insights into tRNA translocation on the ribosome

The ribosome is a highly conserved cellular complex and constitutes the center of protein biosynthesis. As the ribosome consists to about 2/3 of ribosomal RNA (rRNA), the rRNA is involved in most steps of translation. In order to investigate the role of some defined rRNA residues in different aspects of translation we use the atomic mutagenesis approach. This method allows the site-specific incorporation of unnatural nucleosides into the rRNA in the context of the complete 70S from Thermus aquaticus, and thereby exceeds the possibilities of conventional mutagenesis. We first studied ribosome-stimulated EF-G GTP hydrolysis. Here, we could show that the non-bridging phosphate oxygen of A2662, which is part of the Sarcin-Ricin-Loop, is required for EF-G GTPase activation by the ribosome. EF-G GTPase is a crucial step for tRNA translocation from the A- to the P-site, and from the P- to the E-site, respectively. We furthermore used the atomic mutagenesis approach to more precisely characterize the 23S rRNA functional groups involved in E-site tRNA binding. While the ribosomal A- and P-sites have been functionally well characterized in the past, the contribution of the E-site to protein biosynthesis is still poorly understood in molecular terms. Our data disclose the importance of the highly conserved E-site base pair G2421-C2395 for effective translation. Ribosomes with a disrupted G2421-C2395 base pair are defective in tRNA binding to the E-site. This results in an impaired translation of genuine mRNAs, while homo-polymeric templates are not affected. Cumulatively our data emphasize the importance of E-site tRNA occupancy and in particular the intactness of the 23S rRNA base pair G2421-C2395 for productive protein biosynthesis.

Materials properties from electron density distributions: Molecular magnetism and linear optical properties

The general goal of this thesis is correlating observable properties of organic and metal-organic materials with their ground-state electron density distribution. In a long-term view, we expect to develop empirical or semi-empirical approaches to predict materials properties from the electron density of their building blocks, thus allowing to rationally engineering molecular materials from their constituent subunits, such as their functional groups. In particular, we have focused on linear optical properties of naturally occurring amino acids and their organic and metal-organic derivatives, and on magnetic properties of metal-organic frameworks. For analysing the optical properties and the magnetic behaviour of the molecular or sub-molecular building blocks in materials, we mostly used the more traditional QTAIM partitioning scheme of the molecular or crystalline electron densities, however, we have also investigated a new approach, namely, X-ray Constrained Extremely Localized Molecular Orbitals (XC-ELMO), that can be used in future to extracted the electron densities of crystal subunits. With the purpose of rationally engineering linear optical materials, we have calculated atomic and functional group polarizabilities of amino acid molecules, their hydrogen-bonded aggregates and their metal-organic frameworks. This has enabled the identification of the most efficient functional groups, able to build-up larger electric susceptibilities in crystals, as well as the quantification of the role played by intermolecular interactions and coordinative bonds on modifying the polarizability of the isolated building blocks. Furthermore, we analysed the dependence of the polarizabilities on the one-electron basis set and the many-electron Hamiltonian. This is useful for selecting the most efficient level of theory to estimate susceptibilities of molecular-based materials. With the purpose of rationally design molecular magnetic materials, we have investigated the electron density distributions and the magnetism of two copper(II) pyrazine nitrate metal-organic polymers. High-resolution X-ray diffraction and DFT calculations were used to characterize the magnetic exchange pathways and to establish relationships between the electron densities and the exchange-coupling constants. Moreover, molecular orbital and spin-density analyses were employed to understand the role of different magnetic exchange mechanisms in determining the bulk magnetic behaviour of these materials. As anticipated, we have finally investigated a modified version of the X-ray constrained wavefunction technique, XC-ELMOs, that is not only a useful tool for determination and analysis of experimental electron densities, but also enables one to derive transferable molecular orbitals strictly localized on atoms, bonds or functional groups. In future, we expect to use XC-ELMOs to predict materials properties of large systems, currently challenging to calculate from first-principles, such as macromolecules or polymers. Here, we point out advantages, needs and pitfalls of the technique. This work fulfils, at least partially, the prerequisites to understand materials properties of organic and metal-organic materials from the perspective of the electron density distribution of their building blocks. Empirical or semi-empirical evaluation of optical or magnetic properties from a preconceived assembling of building blocks could be extremely important for rationally design new materials, a field where accurate but expensive first-principles calculations are generally not used. This research could impact the community in the fields of crystal engineering, supramolecular chemistry and, of course, electron density analysis.

Plant diversity moderates drought stress in grasslands: Implications from a large real-world study on 13C natural abundances

Land-use change and intensification play a key role in the current biodiversity crisis. The resulting species loss can have severe effects on ecosystem functions and services, thereby increasing ecosystem vulnerability to climate change. We explored whether land-use intensification (i.e. fertilization intensity), plant diversity and other potentially confounding environmental factors may be significantly related to water use (i.e. drought stress) of grassland plants. Drought stress was assessed using δ13C abundances in aboveground plant biomass of 150 grassland plots across a gradient of land-use intensity. Under water shortage, plants are forced to increasingly take up the heavier 13C due to closing stomata leading to an enrichment of 13C in biomass. Plants were sampled at the community level and for single species, which belong to three different functional groups (one grass, one herb, two legumes). Results show that plant diversity was significantly related to the δ13C signal in community, grass and legume biomass indicating that drought stress was lower under higher diversity, although this relation was not significant for the herb species under study. Fertilization, in turn, mostly increased drought stress as indicated by more positive δ13C values. This effect was mostly indirect by decreasing plant diversity. In line with these results, we found similar patterns in the δ13C signal of the organic matter in the topsoil, indicating a long history of these processes. Our study provided strong indication for a positive biodiversity-ecosystem functioning relationship with reduced drought stress at higher plant diversity. However, it also underlined a negative reinforcing situation: as land-use intensification decreases plant diversity in grasslands, this might subsequently increases drought sensitivity. Vice-versa, enhancing plant diversity in species-poor agricultural grasslands may moderate negative effects of future climate change.

Aboveground community and species-specific plant biomass from the Jena Experiment (Main Experiment, year 2004)

This data set contains aboveground community biomass (Sown plant community, Weed plant community, Dead plant material, and Unidentified plant material; all measured in biomass as dry weight) and species-specific biomass from the sown species of the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. Aboveground community biomass was harvested twice in 2004 just prior to mowing (during peak standing biomass in late May and in late August) on all experimental plots of the main experiment. This was done by clipping the vegetation at 3 cm above ground in four rectangles of 0.2 x 0.5 m per large plot. The location of these rectangles was assigned prior to each harvest by random selection of coordinates within the core area of the plots (i.e. the central 10 x 15 m). The positions of the rectangles within plots were identical for all plots. The harvested biomass was sorted into categories: individual species for the sown plant species, weed plant species (species not sown at the particular plot), detached dead plant material (i.e., dead plant material in the data file), and remaining plant material that could not be assigned to any category (i.e., unidentified plant material in the data file). All biomass was dried to constant weight (70°C, >= 48 h) and weighed. Sown plant community biomass was calculated as the sum of the biomass of the individual sown species. The data for individual samples and the mean over samples for the biomass measures on the community level are given. Overall, analyses of the community biomass data have identified species richness as well as functional group composition as important drivers of a positive biodiversity-productivity relationship.

Aboveground community and species-specific plant biomass from the Jena Experiment (Main Experiment, year 2007)

This data set contains aboveground community biomass (Sown plant community, Weed plant community, Dead plant material, and Unidentified plant material; all measured in biomass as dry weight) and species-specific biomass from the sown species of the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. Aboveground community biomass was harvested twice in 2007 just prior to mowing (during peak standing biomass in early June and in late August) on all experimental plots of the main experiment. This was done by clipping the vegetation at 3 cm above ground in four (May) or three (August) rectangles of 0.2 x 0.5 m per large plot. The location of these rectangles was assigned prior to each harvest by random selection of coordinates within the core area of the plots (i.e. the central 10 x 15 m). The positions of the rectangles within plots were identical for all plots. The harvested biomass was sorted into categories: individual species for the sown plant species, weed plant species (species not sown at the particular plot), detached dead plant material (i.e., dead plant material in the data file), and remaining plant material that could not be assigned to any category (i.e., unidentified plant material in the data file). All biomass was dried to constant weight (70°C, >= 48 h) and weighed. Sown plant community biomass was calculated as the sum of the biomass of the individual sown species. The data for individual samples and the mean over samples for the biomass measures on the community level are given. Overall, analyses of the community biomass data have identified species richness as well as functional group composition as important drivers of a positive biodiversity-productivity relationship.

Aboveground community and species-specific plant biomass from the Jena Experiment (Main Experiment, year 2006)

This data set contains aboveground community biomass (Sown plant community, Weed plant community, Dead plant material, and Unidentified plant material; all measured in biomass as dry weight) and species-specific biomass from the sown species of the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. Aboveground community biomass was harvested twice in 2006 just prior to mowing (during peak standing biomass in early June and in late August) on all experimental plots of the main experiment. This was done by clipping the vegetation at 3 cm above ground in four rectangles of 0.2 x 0.5 m per large plot. The location of these rectangles was assigned prior to each harvest by random selection of coordinates within the core area of the plots (i.e. the central 10 x 15 m). The positions of the rectangles within plots were identical for all plots. The harvested biomass was sorted into categories: individual species for the sown plant species, weed plant species (species not sown at the particular plot), detached dead plant material (i.e., dead plant material in the data file), and remaining plant material that could not be assigned to any category (i.e., unidentified plant material in the data file). All biomass was dried to constant weight (70°C, >= 48 h) and weighed. Sown plant community biomass was calculated as the sum of the biomass of the individual sown species. The data for individual samples and the mean over samples for the biomass measures on the community level are given. Overall, analyses of the community biomass data have identified species richness as well as functional group composition as important drivers of a positive biodiversity-productivity relationship.

Collection of data on plant height along the plant diversity gradient in the Jena Experiment (Main Experiment, time series since 2002)

This data set contains a time series of plant height measurements (vegetative and reproductive) from the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In addition, data on species specific plant heights for the main experiment are available from 2002. In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. 1. Plant height was recorded, generally, twice a year just before biomass harvest (during peak standing biomass in late May and in late August). Methodologies of measuring height have varied somewhat over the years. In earlier year the streched plant height was measured, while in later years the standing height without streching the plant was measured. Vegetative height was measured either as the height of the highest leaf or as the length of the main axis of non-flowering plants. Regenerating height was measured either as the height of the highest flower on a plant or as the height of the main axis of flowering. Sampled plants were either randomly selected in the core area of plots or along transects in defined distances. For details refer to the description of individual years. Starting in 2006, also the plots of the management experiment, that altered mowing frequency and fertilized subplots (see further details in the general description of the Jena Experiment) were sampled. 2. Species specific plant height was recorded two times in 2002: in late July (vegetative height) and just before biomass harvest during peak standing biomass in late August (vegetative and regenerative height). For each plot and each sown species in the species pool, 3 plant individuals (if present) from the central area of the plots were randomly selected and used to measure vegetative height (non-flowering indviduals) and regenerative height (flowering individuals) as stretched height. Provided are the means over the three measuremnts per plant species per plot.

Collection of data on soil carbon (particulate and dissolved) in the Jena Experiment (Main Experiment, time series since 2002)

This data set contains three time series of measurements of soil carbon (particular and dissolved) from the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. 1. Particulate soil carbon: Stratified soil sampling was performed every two years since before sowing in April 2002 and was repeated in April 2004, 2006 and 2008 to a depth of 30 cm segmented to a depth resolution of 5 cm giving six depth subsamples per core. Total carbon concentration was analyzed on ball-milled subsamples by an elemental analyzer at 1150°C. Inorganic carbon concentration was measured by elemental analysis at 1150°C after removal of organic carbon for 16 h at 450°C in a muffle furnace. Organic carbon concentration was calculated as the difference between both measurements of total and inorganic carbon. 2. Particulate soil carbon (high intensity sampling): In one block of the Jena Experiment soil samples were taken to a depth of 1 m (segmented to a depth resolution of 5 cm giving 20 depth subsamples per core) with three replicates per block ever 5 years starting before sowing in April 2002. Samples were processed as for the more frequent sampling. 3. Dissolved organic carbon: Suction plates installed on the field site in 10, 20, 30 and 60 cm depth were used to sample soil pore water. Cumulative soil solution was sampled biweekly and analyzed for dissolved organic carbon concentration by a high TOC elemental analyzer. Annual mean values of DOC are provided.

Estimation of the normal boiling point of organic compounds via group contributions

The normal boiling point is a fundamental thermo-physical property, which is important in describing the transition between the vapor and liquid phases. Reliable method which can predict it is of great importance, especially for compounds where there are no experimental data available. In this work, an improved group contribution method, which is second order method, for determination of the normal boiling point of organic compounds based on the Joback functional first order groups with some changes and added some other functional groups was developed by using experimental data for 632 organic components. It could distinguish most of structural isomerism and stereoisomerism, which including the structural, cis- and trans- isomers of organic compounds. First and second order contributions for hydrocarbons and hydrocarbon derivatives containing carbon, hydrogen, oxygen, nitrogen, sulfur, fluorine, chlorine and bromine atoms, are given. The fminsearch mathematical approach from MATLAB software is used in this study to select an optimal collection of functional groups (65 functional groups) and subsequently to develop the model. This is a direct search method that uses the simplex search method of Lagarias et al. The results of the new method are compared to the several currently used methods and are shown to be far more accurate and reliable. The average absolute deviation of normal boiling point predictions for 632 organic compounds is 4.4350 K; and the average absolute relative deviation is 1.1047 %, which is of adequate accuracy for many practical applications.

Structural group composition of low-polarity organic matter dissolved in waters of the Northwest Indian Ocean and the Red Sea

Data on amounts of various functional groups, i.e. aldehyde, acid, ester, alcohol, thiol and aromatic groups in several fractions of low-polarity dissolved organic matter are presented. An assumption that this organic matter is part of the lipid fraction is not confirmed. Amount of aromatic compounds in waters of the Northwest Indian Ocean is estimated to be about 1000 times higher than quantity of aromatic hydrocarbons discharged into the ocean each year in petroleum and petroleum products.

Soil carbon in the Jena Experiment (all blocks Main Experiment up to 30cm depth, year 2006)

This data set contains soil carbon measurements (Organic carbon, inorganic carbon, and total carbon; all measured in dried soil samples) from the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. Soil sampling and analysis: Stratified soil sampling was performed in April 2006 to a depth of 30 cm. Three samples per plot were taken using a split tube sampler with an inner diameter of 4.8 cm (Eijkelkamp Agrisearch Equipment, Giesbeek, the Netherlands). Sampling locations were less than 30 cm apart from sampling locations in 2002. Soil samples were segmented into 5 cm depth segments in the field (resulting in six depth layers) and made into composite samples per depth. Subsequently, samples were dried at 40°C. All soil samples were passed through a sieve with a mesh size of 2 mm. Because of much higher proportions of roots in the soil, samples in years after 2002 were further sieved to 1 mm according to common root removal methods. No additional mineral particles were removed by this procedure. Total carbon concentration was analyzed on ball-milled subsamples (time 4 min, frequency 30 s**-1) by an elemental analyzer at 1150°C (Elementaranalysator vario Max CN; Elementar Analysensysteme GmbH, Hanau, Germany). We measured inorganic carbon concentration by elemental analysis at 1150°C after removal of organic carbon for 16 h at 450°C in a muffle furnace. Organic carbon concentration was calculated as the difference between both measurements of total and inorganic carbon.

Plant height along the plant diversity gradient in the Jena Experiment (Main Experiment, year 2002)

This data set contains measurements of plant height: vegetative height (non-flowering indviduals) and regenerative height (flowering individuals) in 2002 from the Main Experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the Main Experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. In 2002, plant height was recorded twice a year: in late June and just before biomass harvest during peak standing biomass in late August. For 3 target plant individuals (if present) per sown species from the central area of the plots, vegetative height (non-flowering indviduals) and regenerative height (flowering individuals) were measured as stretched height. Provided are the indivdiual measurements and the mean over the measured plants per plot (in June) and the mean over the measured plants per plot (in August).

Dissolved organic carbon in soil solution of the Jena Experiment (Main Experiment, year 2002)

This data set contains measurements of dissolved organic carbon in samples of soil water collected from the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. In April 2002 glass suction plates with a diameter of 12 cm, 1 cm thickness and a pore size of 1-1.6 mm (UMS GmbH, Munich, Germany) were installed in depths of 10, 20, 30 and 60 cm to collect soil solution. The sampling bottles were continuously evacuated to a negative pressure between 50 and 350 mbar, such that the suction pressure was about 50 mbar above the actual soil water tension. Thus, only the soil leachate was collected. Cumulative soil solution was sampled biweekly and analyzed for dissolved organic carbon concentration by a high TOC elemental analyzer (Elementar Analysensysteme GmbH, Hanau, Germany). Samples were analyzed as soon as possible and stored at 4°C if necessary. Often in summer, no free soil solution was available for collection, especially in the upper soil layers. Annual mean values of measured biweekly concentrations of dissolved organic carbon are provided.