Lipidomics as a Tool in the Diagnosis and Clinical Therapy

The lipids are essential compounds of cells, with biochemical and structural properties. Lipids are classified according to their chain length or saturation levels and biogenesis. Lipidomics is a spectroscopic and spectrometric technique, like Mass Spectrometry and Nuclear Magnetic Resonance, as well as bioinformatics to quantify and characterize the lipid profile. Lipidomics enables the fundamental understanding of lipid biology, the identification of drug targets for therapy, and the discovery of lipid biomarkers of disease cohorts. Therefore, lipidomics allows knowing the diagnosis and clinical follow-up in medical therapy towards any disease. In this way, the lipid profile allows us to monitor the administration of a clinical treatment and assertively diagnose human diseases

Lipoproteomics: Methodologies and Analysis of Lipoprotein-Associated Proteins along with the Drug Intervention

Lipoproteins are specialized particles involved in the transport and distribution of hydrophobic lipids, as cholesterol and triglycerides, throughout the body. The lipoproteins exhibit a basic spherical shape as complexes of lipids and proteins, and these latter are known as apolipoproteins. Initially, the proteins associated with lipoproteins were recognized as integral or peripheral proteins that only maintain the dynamics and metabolism of lipoproteins. However, there exist many studies on different lipoproteins evidencing that the quantity and type of apolipoproteins and lipoprotein-associated proteins are diverse and could be associated with different lipoprotein function outcomes. Here, we summarized recent processes in the determination of apolipoproteins and lipoprotein-associated proteins profiles through a proteomic approach, analyzing the major methods available and are used to achieve this. We also discuss the relevance of these lipoproteomic analyses on the human disease outcomes

Ultraviolet Radiation and Its Effects on Plants

Ultraviolet radiation is a portion of the electromagnetic spectrum ranging from 10 to 400 nm, classified into three main categories: UV-A (320–400 nm), UV-B (280–320 nm), and UV-C (100–280 nm). The UV radiation from the sun that crosses the atmosphere and reaches the earth’s surface is composed largely of UV-A radiation (95%) and, to a lesser extent, UV-B (5%), which is normally filtered by stratospheric ozone. With the thinning of the ozone layer, UV-B radiation penetrates deeper into the earth’s surface, where it becomes dangerous due to its high energy content that acts at the molecular level, affecting the cycles of carbon, nitrogen, and other elements, thus, having a direct impact on global warming. On the other hand, UV radiation alters numerous essential organic compounds for living organisms. Since its discovery, it has been established that e UV-B causes alterations in plant development and metabolism, both primary and secondary. In this chapter, we summarize the current knowledge about the effects of UV radiation on the morphological, biochemical, and genetic processes in plants

Data-Driven Approaches Used for Compound Library Design for the Treatment of Parkinson’s Disease

Parkinson’s disease (PD) is the second most common neurodegenerative disease in older individuals worldwide. Pharmacological treatment for such a disease consists of drugs such as monoamine oxidase B (MAO-B) inhibitors to increase dopamine concentration in the brain. However, such drugs have adverse reactions that limit their use for extended periods; thus, the design of less toxic and more efficient compounds may be explored. In this context, cheminformatics and computational chemistry have recently contributed to developing new drugs and the search for new therapeutic targets. Therefore, through a data-driven approach, we used cheminformatic tools to find and optimize novel compounds with pharmacological activity against MAO-B for treating PD. First, we retrieved from the literature 3316 original articles published between 2015–2021 that experimentally tested 215 natural compounds against PD. From such compounds, we built a pharmacological network that showed rosmarinic acid, chrysin, naringenin, and cordycepin as the most connected nodes of the network. From such compounds, we performed fingerprinting analysis and developed evolutionary libraries to obtain novel derived structures. We filtered these compounds through a docking test against MAO-B and obtained five derived compounds with higher affinity and lead likeness potential. Then we evaluated its antioxidant and pharmacokinetic potential through a docking analysis (NADPH oxidase and CYP450) and physiologically-based pharmacokinetic (PBPK modeling). Interestingly, only one compound showed dual activity (antioxidant and MAO-B inhibitors) and pharmacokinetic potential to be considered a possible candidate for PD treatment and further experimental analysis