Natural products have a significant role in drug discovery. Natural products have distinctive chemical structures that have contributed to identifying and developing drugs for different therapeutic areas. Moreover, natural products are significant sources of inspiration or starting points to develop new therapeutic agents. Natural products such as peptides and macrocycles, and other compounds with unique features represent attractive sources to address complex diseases. Computational approaches that use chemoinformatics and molecular modeling methods contribute to speed up natural product-based drug discovery. Several research groups have recently used computational methodologies to organize data, interpret results, generate and test hypotheses, filter large chemical databases before the experimental screening, and design experiments. This review discusses a broad range of chemoinformatics applications to support natural product-based drug discovery. We emphasize profiling natural product data sets in terms of diversity; complexity; acid/base; absorption, distribution, metabolism, excretion, and toxicity (ADME/Tox) properties; and fragment analysis. Novel techniques for the visual representation of the chemical space are also discussed.
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http://dx.doi.org/10.3390/biom10111566 | DOI Listing |
Sci Rep
December 2024
Plum Island Animal Disease Center, Agricultural Research Service, USDA, Greenport, NY, 11944, USA.
For over a century African swine fever (ASF) has been causing outbreaks leading to devastating losses for the swine industry. The current pandemic of ASF has shown no signs of stopping and continues to spread causing outbreaks in additional countries. Currently control relies mostly on culling infected farms, and strict biosecurity procedures.
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December 2024
The University of Trans-Disciplinary Health Sciences and Technology (TDU), 74/2, Post Attur via Yelahanka, Jarakabande Kaval, Bengaluru, 560 064, India.
Triphala is a traditional Ayurvedic herbal formulation composed of three fruits: amla (Phyllanthus emblica), bibhitaki (Terminalia bellerica), and haritaki (Terminalia chebula). Triphala is a potent Ayurvedic remedy that promotes digestion, detoxification, and overall wellness, while also providing antioxidant benefits through its trio of nutrient-rich fruits. In order to elucidate the individual contributions of the three ingredients of Triphala from molecular perspective, the individual ingredients were used for the untargeted LCMS/MS analysis.
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December 2024
Shaanxi Key Laboratory of Natural Products & Chemical Biology, College of Chemistry & Pharmacy, Northwest A&F University, Yangling, Shaanxi, 712100, China.
Marine cyclopianes are a family of diterpenoid with novel carbon skeleton and diverse biological activities. Herein, we report our synthetic and chemical proteomics studies of cyclopiane diterpenes which culminate in the asymmetric total synthesis of conidiogenones C, K and 12β-hydroxy conidiogenone C, and identification of Immunity-related GTPase family M protein 1 (IRGM1) as a cellular target. Our asymmetric synthesis commences from Wieland-Miescher ketone and features a sequential intramolecular Pauson-Khand reaction and gold-catalyzed Nazarov cyclization to rapidly construct the 6-5-5-5 tetracyclic skeleton.
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December 2024
Division of Pulmonary, Allergy, Critical Care, and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
E-cigarette/vaping-associated lung injury (EVALI) is strongly associated with vitamin E acetate and often occurs with concomitant tetrahydrocannabinol (THC) use. To uncover pathways associated with EVALI, we examined cytokines, transcriptomic signatures, and lipidomic profiles in bronchoalveolar lavage fluid (BALF) from THC-EVALI patients. At a single center, we prospectively enrolled mechanically ventilated patients with EVALI from THC-containing products (N = 4) and patients with non-vaping acute lung injury and airway controls (N = 5).
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December 2024
State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau, China.
Lipid nanoparticles (LNPs) have proven effective in mRNA delivery, as evidenced by COVID-19 vaccines. Its key ingredient, ionizable lipids, is traditionally optimized by inefficient and costly experimental screening. This study leverages artificial intelligence (AI) and virtual screening to facilitate the rational design of ionizable lipids by predicting two key properties of LNPs, apparent pKa and mRNA delivery efficiency.
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