Complexity-to-Diversity and Pseudo-Natural Product Strategies as Powerful Platforms for Deciphering Next-Generation Therapeutics.

Stereochemical and skeletal complexity are particularly important vis-à-vis the cross-talks between a small molecule and a complementary active site of a biological target. This intricate harmony is known to increase selectivity, reduce toxicity, and increase the success rate in clinical trials. Therefore, the development of novel strategies for establishing underrepresented chemical space that is rich in stereochemical and skeletal diversity is an important milestone in a drug discovery campaign. In this review, we discuss the evolution of interdisciplinary synthetic methodologies utilized in chemical biology and drug discovery that has revolutionized the discovery of first-in-class molecules over the last decade with an emphasis on complexity-to-diversity and pseudo-natural product strategies as a remarkable toolbox for deciphering next-generation therapeutics. We also report how these approaches dramatically revolutionized the discovery of novel chemical probes that target underrepresented biological space. We also highlight selected applications and discuss key opportunities offered by these tools and important synthetic strategies used for the construction of chemical spaces that are rich in skeletal and stereochemical diversity. We also provide insight on how the integration of these protocols has the promise of changing the drug discovery landscape.

Evaluation of Two Simultaneous Metabolomic and Proteomic Extraction Protocols Assessed by Ultra-High-Performance Liquid Chromatography Tandem Mass Spectrometry.

Untargeted multi-omics analysis of plasma is an emerging tool for the identification of novel biomarkers for evaluating disease prognosis, and for developing a better understanding of molecular mechanisms underlying human disease. The successful application of metabolomic and proteomic approaches relies on reproducibly quantifying a wide range of metabolites and proteins. Herein, we report the results of untargeted metabolomic and proteomic analyses from blood plasma samples following analyte extraction by two frequently-used solvent systems: chloroform/methanol and methanol-only. Whole blood samples were collected from participants (n = 6) at University Hospital Sharjah (UHS) hospital, then plasma was separated and extracted by two methods: (i) methanol precipitation and (ii) 4:3 methanol:chloroform extraction. The coverage and reproducibility of the two methods were assessed by ultra-high-performance liquid chromatography-electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-ESI-QTOF-MS). The study revealed that metabolite extraction by methanol-only showed greater reproducibility for both metabolomic and proteomic quantifications than did methanol/chloroform, while yielding similar peptide coverage. However, coverage of extracted metabolites was higher with the methanol/chloroform precipitation.

Skin Cancer Metabolic Profile Assessed by Different Analytical Platforms.

Skin cancer, including malignant melanoma (MM) and keratinocyte carcinoma (KC), historically named non-melanoma skin cancers (NMSC), represents the most common type of cancer among the white skin population. Despite decades of clinical research, the incidence rate of melanoma is increasing globally. Therefore, a better understanding of disease pathogenesis and resistance mechanisms is considered vital to accomplish early diagnosis and satisfactory control. The "Omics" field has recently gained attention, as it can help in identifying and exploring metabolites and metabolic pathways that assist cancer cells in proliferation, which can be further utilized to improve the diagnosis and treatment of skin cancer. Although skin tissues contain diverse metabolic enzymes, it remains challenging to fully characterize these metabolites. Metabolomics is a powerful omics technique that allows us to measure and compare a vast array of metabolites in a biological sample. This technology enables us to study the dermal metabolic effects and get a clear explanation of the pathogenesis of skin diseases. The purpose of this literature review is to illustrate how metabolomics technology can be used to evaluate the metabolic profile of human skin cancer, using a variety of analytical platforms including gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), and nuclear magnetic resonance (NMR). Data collection has not been based on any analytical method.