Over the past decade, molecular dynamics (MD) simulations have become particularly powerful to rationalize drug insertion and partitioning in lipid bilayers. MD simulations efficiently support experimental evidences, with a comprehensive understanding of molecular interactions driving insertion and crossing. Prediction of drug partitioning is discussed with respect to drug families (anesthetics; β-blockers; non-steroidal anti-inflammatory drugs; antioxidants; antiviral drugs; antimicrobial peptides). To accurately evaluate passive permeation coefficients turned out to be a complex theoretical challenge; however the recent methodological developments based on biased MD simulations are particularly promising. Particular attention is paid to membrane composition (e.g., presence of cholesterol), which influences drug partitioning and permeation. Recent studies concerning in silico models of membrane proteins involved in drug transport (influx and efflux) are also reported here. These studies have allowed gaining insight in drug efflux by, e.g., ABC transporters at an atomic resolution, explicitly accounting for the mandatory forces induced by the surrounded lipid bilayer. Large-scale conformational changes were thoroughly analyzed.
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http://dx.doi.org/10.1016/j.phrs.2016.06.030 | DOI Listing |
Molecules
January 2025
Department of Medical Biosciences, Faculty of Life Sciences, Ritsumeikan University, Kusatsu 525-8577, Shiga, Japan.
Traditional Japanese medicines, i.e., Kampo medicines, consist of crude drugs (mostly plants) that have empirical pharmacological functions ('' in Japanese), such as clearing heat.
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January 2025
College of Science & Engineering and Centre for Tropical Environmental and Sustainability Science, James Cook University of North Queensland, Cairns, Queensland, Australia.
Ozone (O), a major air pollutant, can negatively impact plant growth and yield. While O impacts have been widely documented in crops such as wheat and soybean, few studies have looked at the effects of O on sorghum, a C plant and the fifth most important cereal crop worldwide. We exposed grain sorghum ( cv.
View Article and Find Full Text PDFBMC Complement Med Ther
January 2025
Laser Research Centre, Faculty of Health Sciences, Doornfontein Campus, University of Johannesburg, Johannesburg, 2028, South Africa.
Background: Amongst all neoplastic diseases, breast cancer represents a major cause of death among the female population in developed and developing countries. Since alkaloid drugs are commonly used in chemotherapy to manage this disease, this study investigated the anti-proliferative effectiveness of alkaloid-rich fractions of Senna didymobotrya leaves only and with laser irradiation against MCF-7 breast cancer cells.
Method And Materials: A powdered sample of the plant leaves was extracted with 50% ethanol, filtered and their pH was adjusted with acid and base solution followed by partitioning with chloroform and ethyl acetate solvents.
Swiss Med Wkly
January 2025
Cancer Center und Research Center, Cantonal Hospital Graubünden, Chur, Switzerland.
Background And Objective: Because of the lack of effective targeted treatment options, docetaxel has long been the standard second-line therapy for patients with advanced non-small cell lung cancer, including the Kirsten rat sarcoma virus (KRAS) G12C mutation. The CodeBreak 200 trial demonstrated that sotorasib, a new drug targeting the G12C-mutated KRAS protein, modestly improved progression-free survival compared with docetaxel in patients whose cancer had progressed after receiving platinum chemotherapy and programmed cell death protein 1 (PD-1) / programmed death ligand 1 (PD-L1) inhibitors as first-line treatment. Consequently, sotorasib received temporary approval in Switzerland.
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January 2025
Department of Mathematical Sciences, Faculty of Science, Somali National University, Mogadishu Campus, Mogadishu, Somalia.
In recent years, machine learning has gained substantial attention for its ability to predict complex chemical and biological properties, including those of pharmaceutical compounds. This study proposes a machine learning-based quantitative structure-property relationship (QSPR) model for predicting the physicochemical properties of anti-arrhythmia drugs using topological descriptors. Anti-arrhythmic drug development is challenging due to the complex relationship between chemical structure and drug efficacy.
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