Quantifying the shifts in physicochemical property space introduced by the metabolism of small organic molecules

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The re-emergence of natural products for drug discovery in the genomics era

Natural products have been a rich source of compounds for drug discovery. However, their use has diminished in the past two decades, in part because of technical barriers to screening natural products in high-throughput assays against molecular targets. Here, we review strategies for natural product screening that harness the recent technical advances that have reduced these barriers. We also assess the use of genomic and metabolomic approaches to augment traditional methods of studying natural products, and highlight recent examples of natural products in antimicrobial drug discovery and as inhibitors of protein-protein interactions. The growing appreciation of functional assays and phenotypic screens may further contribute to a revival of interest in natural products for drug discovery

Bacterial biogeography of the rare Charitable Research Reserve

Soil microbial communities play a dominant role in global biogeochemical cycles, with profound effects on agriculture, ecosystem stability, human health, and global climate. As a result, assessing their biogeographic patterns can help to further reveal mechanisms shaping their diversity and function in the environment. Furthermore, due to extensive spatial heterogeneity and environmental gradients, there is potential for overlooking key biogeographical patterns, critical metabolic processes, and novel bacterial taxa existing within deeper soil horizons that can be highly dependent on changes in land-usage. Additionally, an active area of research in soil microbial biogeography is assessing the extent to which current environmental or past historical factors constrain microbial community assemblages. The objectives of this study were to examine and characterize depth-dependent bacterial community characteristics across multiple land-use types to explore subsurface biogeographical patterns. I collected soil samples across seven distinct land-use types to depths of 45 cm, including old-growth and mature forests, decommissioned, and active agricultural fields from the rare Charitable Research Reserve (Cambridge, Ontario). Bacterial communities were characterized by sequencing of bacterial 16S rRNA gene amplicons coupled with multivariate statistical analyses from 376 soil samples. In addition, to explore functional and metabolic characteristics of collected soils, the PICRUSt algorithm was used to predict metagenomes of uncharacterized taxa. Soil bacterial communities across all sites were strongly influenced by depth. Upper soils (0–15 cm) and open field sites maintained higher bacterial alpha-diversity than deeper soils and forested sites. The magnitude of soil depth effects appeared to differ across environment types highlighting that land-use type also plays a significant role in shaping communities; bacterial communities across the field sites (i.e., grasslands and agricultural sites) were shown to be more strongly affected than forested sites. Soil pH, which exhibited a large gradient across samples, appeared to be largely responsible for differential shifts in communities with depth across land-use types especially considering that C, NH4+, NO3‾, moisture, and texture showed generally consistent trends with depth across all sites. This observation was further corroborated by NPMANOVA and CCA, which highlighted that pH was among the top explanatory variable explaining >15% of the variation in the dataset. This finding further emphasizes that pH is a strong predictor of bacterial community composition, not only across surface soils, but also within the soil subsurface. Overall, the impact of pH on soil bacterial community composition exceeded that of depth. The effect of land-use type on subsurface bacterial communities was found to be largely attributed to differences in dominant plant communities. Field sites were characterized by tall grasses whereas forest sites were characterized by woody tree species. Considering that plant inputs (i.e., root exudates, litter) are translocated through soils over time and affect the physicochemical environment, these findings further enforce that plants play important roles in structuring soil bacterial communities across environment types. In addition, contrary to evidence from the aboveground plant communities and site histories, there was no direct evidence of bacterial community succession throughout soils across the field sites sampled in this investigation. Instead, edaphic factors including soil texture, particularly sand, silt, clay, and moisture, appeared to govern changes in overall community composition across the field sites, highlighting the importance of the immediate physicochemical environment in shaping soil bacterial communities. Soils across all sites and depths were dominated by members of the Proteobacteria (33.2%), Actinobacteria (27.8%), Acidobacteria (14.9%), Chloroflexi (6.6%), Gemmatimonadetes (4.7%), Bacteroidetes (3.0%), Nitrospirae (2.1%), Firmicutes (2.3%), Verrucomicrobia (1.7%), and Latescibacteria (formerly WS3; 1.2%). In addition to observing trends in specific phyla with depth (e.g., Proteobacteria and Bacteroidetes), data also highlighted consistent depth-specific changes in OTU relative abundances. Although the majority of significant correlations were negative (indicating a decrease in abundance with increasing depth), Spearman’s correlation analysis found evidence for consistent positively correlated OTUs with depth. Notably, all positively depth-correlated OTUs were affiliated with uncultivated bacteria, further highlighting that subsurface environments are poorly studied. Correlation analyses were also conducted for pH. Nitrospirae and Chloroflexi members were among the top strongly and positively correlated taxa with pH, consistent with previous studies. Acidomicrobiia and Solibacteres classes, members of the Acidobacteria phylum, were found to be strongly and negatively correlated with pH, which is also consistent with previous research. These results further demonstrate the importance of pH in shaping soil bacterial communities considering that many taxa are adapted to narrow and specific growth and pH ranges. The PICRUSt results reflected observations noted in the taxonomy-based analysis. “Transporter” associated genes appeared to show differential abundances across land-use type. Forest sites, in particular site CA, a mature forest environment, had the lowest abundance of “transporter” associated genes. This result may further highlight pH effects on soil bacterial communities, considering that site CA had samples with the lowest pH and, consequently, the lowest species diversity. Overall, this research has set up baseline observations of bacterial community dynamics at the rare Charitable Research Reserve expanding on the few studies that have included soil depth as an environmental gradient and paving the way for future investigations. In addition, this study exemplifies important global environmental gradients including depth, land-usage, and soil biogeochemistry operating at smaller geographical scales across consistent underlying geology. Furthermore, this work has added insight concerning the interplay of the immediate physicochemical environment and past historical legacies in shaping soil microbial communities. Future research with the dataset generated will further explore bacterial taxa that vary in relation to pH and depth, in addition to phylogenetically novel taxa existing at low relative abundance, providing additional insight into the unexplored biodiversity of soil microbial communities

Investigating the chemical space and metabolic bioactivation of natural products and cross-reactivity of chemical inhibitors in CYP450 phenotyping

Includes bibliographical references.Natural products have been exploited by humans as the most consistently reliable source of medicines for hundreds of years. Owing to the great diversity in chemical scaffolds they encompass, these compounds provide an almost limitless starting point for the discovery and development of novel semi-synthetic or wholly synthetic drugs. In Africa, and many other parts of the world, natural products in the form of herbal remedies are still used as primary therapeutic interventions by populations far removed from conventional healthcare facilities. However, unlike conventional drugs that typically undergo extensive safety studies during development, traditional remedies are often not subjected to similar evaluation and could therefore harbour unforeseen risks alongside their established efficacy. A comparison of the ‘drug-like properties’ of 335 natural products from medicinal plants reported in the African Herbal Pharmacopoeia with those of 608 compounds from the British Pharmacopoeia 2009 was performed using in silico tools. The data obtained showed that the natural products differed significantly from conventional drugs with regard to molecular weight, rotatable bonds and H-bond donor distributions but not with regard to lipophilicity (cLogP) and H-bond acceptor distributions. In general, the natural products were found to exhibit a higher degree of deviation from Lipinski’s ‘Rule-of-Five’. Additionally, these compounds possessed a slightly greater number of structural alerts per molecule compared to conventional drugs, suggesting a higher likelihood of undergoing metabolic bioactivation

Mathematics and biology: a Kantian view on the history of pattern formation theory

Driesch’s statement, made around 1900, that the physics and chemistry of his day were unable to explain self-regulation during embryogenesis was correct and could be extended until the year 1972. The emergence of theories of self-organisation required progress in several areas including chemistry, physics, computing and cybernetics. Two parallel lines of development can be distinguished which both culminated in the early 1970s. Firstly, physicochemical theories of self-organisation arose from theoretical (Lotka 1910–1920) and experimental work (Bray 1920; Belousov 1951) on chemical oscillations. However, this research area gained broader acceptance only after thermodynamics was extended to systems far from equilibrium (1922–1967) and the mechanism of the prime example for a chemical oscillator, the Belousov–Zhabotinski reaction, was deciphered in the early 1970s. Secondly, biological theories of self-organisation were rooted in the intellectual environment of artificial intelligence and cybernetics. Turing wrote his The chemical basis of morphogenesis (1952) after working on the construction of one of the first electronic computers. Likewise, Gierer and Meinhardt’s theory of local activation and lateral inhibition (1972) was influenced by ideas from cybernetics. The Gierer–Meinhardt theory provided an explanation for the first time of both spontaneous formation of spatial order and of self-regulation that proved to be extremely successful in elucidating a wide range of patterning processes. With the advent of developmental genetics in the 1980s, detailed molecular and functional data became available for complex developmental processes, allowing a new generation of data-driven theoretical approaches. Three examples of such approaches will be discussed. The successes and limitations of mathematical pattern formation theory throughout its history suggest a picture of the organism, which has structural similarity to views of the organic world held by the philosopher Immanuel Kant at the end of the eighteenth century

Toward Rational Design of Graphene Nanomaterials: Manipulating Chemical Composition to Identify Governing Properties for Electrochemical and Biological Activities

The unique properties of graphene-based nanomaterials (GMs) have enabled various applications in the fields of electronics, energy, environment, and biotechnology. Yet, their potential inherent hazard poses risks to human health and the environment, which could be a barrier to the success of these applications. A critical underpinning of sustainable material development is rational design. This approach involves the ability to control material outcomes, requiring the establishment of property-function and property-hazard relationships. This dissertation aims to demonstrate an ability to rationally design GMs by manipulating chemical composition and establishing the relationships that correlate material properties to their electrochemical activity (function) and bioactivity (hazard). The electrochemical activity is represented by the material reactivity for important electrochemical reactions (oxygen reduction reaction, ORR and oxygen evolution reaction, OER). The bioactivity is represented as the material propensity to oxidize a cellular biomolecule (glutathione) and inactivate the bacteria (Escherichia coli). Material sets of graphene oxide (GO) and nitrogen-doped graphene (NG) are investigated using various complementary characterization techniques to determine the material properties that govern electrochemical and biological activities as chemical composition changes. The results suggest both activities are governed by synergistic effects from multiple properties, including specific oxygen and nitrogen sites and properties arising as a consequence of changing chemical composition. Enhanced aqueous dispersion and defect density are important for GO bioactivity. Additionally, coupled experimental and computational approaches elucidate the synergistic role of adjacent epoxide and hydroxyl groups on GO in directly oxidizing glutathione. As the surface of GO is reduced, the electrochemical and biological activities are governed by a balance of carbonyl groups and electrical conductivity. For NG, N-types control electrochemical reactions, ORR (graphitic-N) and OER (pyridinic-N). Further, the predominance of graphitic-N enhances oxidative stress-related bioactivity, which is an important contribution since very little is known surrounding NG bioactivity. Collectively, this dissertation supports the use of chemical composition manipulation to control material properties and in turn, function and hazard outcomes. The established property-function and property-hazard relationships provide rational design guidance for GMs. The holistic approach herein is applicable to other nanomaterials and thus, will continue to contribute to the advancement of sustainable nanotechnology

The compositional and evolutionary logic of metabolism

Metabolism displays striking and robust regularities in the forms of modularity and hierarchy, whose composition may be compactly described. This renders metabolic architecture comprehensible as a system, and suggests the order in which layers of that system emerged. Metabolism also serves as the foundation in other hierarchies, at least up to cellular integration including bioenergetics and molecular replication, and trophic ecology. The recapitulation of patterns first seen in metabolism, in these higher levels, suggests metabolism as a source of causation or constraint on many forms of organization in the biosphere. We identify as modules widely reused subsets of chemicals, reactions, or functions, each with a conserved internal structure. At the small molecule substrate level, module boundaries are generally associated with the most complex reaction mechanisms and the most conserved enzymes. Cofactors form a structurally and functionally distinctive control layer over the small-molecule substrate. Complex cofactors are often used at module boundaries of the substrate level, while simpler ones participate in widely used reactions. Cofactor functions thus act as "keys" that incorporate classes of organic reactions within biochemistry. The same modules that organize the compositional diversity of metabolism are argued to have governed long-term evolution. Early evolution of core metabolism, especially carbon-fixation, appears to have required few innovations among a small number of conserved modules, to produce adaptations to simple biogeochemical changes of environment. We demonstrate these features of metabolism at several levels of hierarchy, beginning with the small-molecule substrate and network architecture, continuing with cofactors and key conserved reactions, and culminating in the aggregation of multiple diverse physical and biochemical processes in cells.Comment: 56 pages, 28 figure

Energetics and inhibition of the KEAP1/NRF2 protein-protein interaction interface

Protein-protein interactions (PPI) represent a challenging target class in contemporary small molecule drug discovery. The difficulty arises because PPI sites are structurally and physicochemically different from conventional drug binding sites. Moreover, we currently lack a good understanding of the druggability of PPI targets: that is, how the structure and properties of a PPI interface site relates to the properties of small molecules that can bind to that site with high affinity. Efforts to achieve potent drug-like small molecule inhibitors of PPI interfaces, involving a wide range targets, historically have largely been unsuccessful, leading to the conclusion that new inhibitor chemotypes are needed to inhibit this class of target. In this thesis, I describe the application of two approaches to identify inhibitors of the PPI interface between Kelch-like ECH associated protein 1 (KEAP1) and Nuclear factor (erythroid-derived 2)-like 2 (Nrf2): (i) screening a library of synthetic macrocycles, and (ii) fragment-based lead discovery. I validate and characterize the hit compounds obtained. In the case of the fragment hits, I investigate what features of the compounds are required for binding to the target (Chapter Two). In parallel, I investigate the structure of the hot spot ensemble at the KEAP1/Nrf2 binding interface using three complementary methods: alanine scanning mutagenesis, fragment screening, and in silico probe mapping using the FTMap algorithm (Chapter Three). This analysis brings insight into the druggability of KEAP1, and advances our understanding of the utility and limitations of those three widely used methods for characterizing the hot spot ensembles at PPI interfaces (Chapter Three). Finally, to gain additional insight into the energetics of KEAP1/Nrf2 binding, I probe the additivity of combinations of alanine mutants (Chapter Four). I use the results to propose a quantitative approach to categorizing the various degrees of additivity that can be observed at PPI interfaces, and discuss the possible structural basis for these behaviors. The model potentially provides a more general framework for understanding the binding energetics at PPI interfaces using combinations of mutations