Volume 4, Issue 11 -

Ceramics are among the most studied findings, one of the best markers for providing technological and functional information in archaeological contexts. Their chemical-mineralogical characterization allows to answer a large number of historical-archaeological questions about classification, provenance, production technologies, trade routes, economic exchange, etc. The best methodological approach not only integrates morphological-stylistic studies to the archaeometric ones, but also includes a synergic instrumental strategy aimed both to take advantage of each different analytical technique to the best of its potentiality and to over step the problems connected to the preciousness and uniqueness of the objects. As far as the mineralogical and petrographical composition of preindustrial ceramics is concerned, its determination is crucial to answer provenance and technological issues like raw materials procurement and the production processes in this respect, equivalent firing temperature, redox atmosphere during firing are important factors that help in understanding the relevant mineralogical and micro-structural transformations. In this paper, we illustrate how an integrated approach of analytical techniques, tested on different classes of ceramics – pottery with spathic calcite, Apulian red figure pottery and technical ceramics – can provide answers to archaeological questions.

Our previous work was focused on the fundamental physical and chemical concepts behind “drug-likeness” and “natural product (NP)-likeness”. Herein, we discuss further details on the concepts of “drug-likeness”, “lead-likeness” and “NP-likeness”. The discussion will first focus on NPs as drugs, then a discussion of previous studies in which the complexities of the scaffolds and chemical space of naturally occurring compounds have been compared with synthetic, semisynthetic compounds and the Food and Drug Administration-approved drugs. This is followed by guiding principles for designing “drug-like” natural product libraries for lead compound discovery purposes. In addition, we present a tool for measuring “NP-likeness” of compounds and a brief presentation of machine-learning approaches. A binary quantitative structure–activity relationship for classifying drugs from nondrugs and natural compounds from nonnatural ones is also described. While the studies add to the plethora of recently published works on the “drug-likeness” of NPs, it no doubt increases our understanding of the physicochemical properties that make NPs fall within the ranges associated with “drug-like” molecules.

Green Chemistry principles can be applied while following approved Environmental Protection Agency methods at an accredited lab. The decision-making process involved in selecting a method for the analysis of dioxins in solid matrices while considering green chemistry, method performance and overall cost are presented.

The relevance of FT-IR spectroscopy in heritage science has experienced a constant grow in the last two decades owing to analytical peculiarities that make it an extremely useful tool to answer the questions posed by the study and conservation of art-historical and archaeological materials. High versatility, sensitivity and molecular specificity are, in fact, all requirements that FT-IR spectroscopy fulfils allowing for the investigation of the chemical properties of heritage materials spanning from the micro- to the macro-scale and offering a variety of approaches to minimize sample manipulation and maximize extracted information. Molecular identification and localisation at high lateral resolution of organic and inorganic components in micro-samples was, over recently, the mostly exploited use of FT-IR in heritage science; however, benefiting from technological progress and advances in optical materials and components achieved in the last decade, it now stands out also for non-invasive surface analysis of artworks by fully portable instrumentation.

Technological advances have contributed to the evolution of the natural product chemistry and drug discovery programs. Recently, computational methods for nuclear magnetic resonance (NMR) and mass spectrometry (MS) have speeded up and facilitated the process of structural elucidation even in high complex biological samples. In this chapter, the current computational tools related to NMR and MS databases and spectral similarity networks, as well as their applications on dereplication and determination of biological biomarkers, are addressed.

The prediction of toxicological endpoints has gained broad acceptance; it is widely applied in early stages of drug discovery as well as for impurities obtained in the production of generic or equivalent products. In this work, we describe methodologies for the prediction of toxicological endpoints compounds, with a particular focus on secondary metabolites. Case studies include toxicity prediction of natural compound databases with anti-diabetic, anti-malaria and anti-HIV properties.