Human immunodeficiency virus (HIV) infection is a major problem for humanity because HIV is constantly changing and developing resistance to current drugs. This necessitates the development of new anti-HIV drugs that take new approaches to combat an ever-evolving virus. One of the promising alternatives to combination antiretroviral therapy (cART) is the molecular hybrid strategy, in which two or more pharmacophore units of bioactive scaffolds are combined into a single molecular structure. These hybrid structures have the potential to have higher efficacy and lower toxicity than their parent molecules. Given the potential advantages of the hybrid molecular approach, the development and synthesis of these compounds are of great importance in anti-HIV drug discovery. This review focuses on the recent development of hybrid compounds targeting integrase (IN), reverse transcriptase (RT), and protease (PR) proteins and provides a brief description of their chemical structures, structure-activity relationship, and binding mode.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9502546 | PMC |
http://dx.doi.org/10.3390/ph15091092 | DOI Listing |
J Phys Chem A
January 2025
Department of Chemistry and Biochemistry, The University of Alabama, Tuscaloosa, Alabama 35487-0336, United States.
The bonding and spectroscopic properties of LaX and AcX (X = O and F) diatomic molecules were studied by high-level ab initio CCSD(T) and SO-CASPT2 electronic structure calculations. Bond dissociation energies (BDEs) were calculated at the Feller-Peterson-Dixon (FPD) level. Potential energy curves and spectroscopic constants for the lowest-lying spin-orbit Ω states were obtained at the SO-CASPT2/aQ-DK level.
View Article and Find Full Text PDFJ Am Chem Soc
January 2025
School of Energy and Environment, Southeast University, Nanjing 210096, China.
The broad temperature adaptability associated with the desolvation process remains a formidable challenge for organic electrolytes in rechargeable metal batteries, especially under low-temperature (LT) conditions. Although a traditional approach involves utilizing electrolytes with a high degree of anion participation in the solvation structure, known as weakly solvation electrolytes (WSEs), the solvation structure of these electrolytes is highly susceptible to temperature fluctuations, potentially undermining their LT performance. To address this limitation, we have devised an innovative electrolyte that harnesses the interplay between solvent molecules, effectively blending strong and weak solvents while incorporating anion participation in a solvation structure that remains mostly unchanged by temperature variations.
View Article and Find Full Text PDFPLoS One
January 2025
Center for Computation and Integrative Biology, Rutgers, The State of New Jersey, Camden, NJ, United States of America.
Melatonin, a molecule with diverse biological functions, is ubiquitously present in living organisms. There is significant interest in understanding melatonin signal transduction pathways in humans, particularly due to its critical role in regulating the sleep-wake cycle. However, a knowledge gap remains in fully elucidating the mechanisms by which melatonin influences circadian regulation.
View Article and Find Full Text PDFPLoS One
January 2025
Special Infectious Agents Unit-BSL3, King Fahd Medical Research Center, King Abdulaziz University, Jeddah, Saudi Arabia.
The ongoing increase in the prevalence and mutation rate of the influenza virus remains a critical global health issue. A promising strategy for antiviral drug development involves targeting the RNA-dependent RNA polymerase, specifically the PB2-cap binding domain of Influenza A H5N1. This study employs an in-silico approach to inhibit this domain, crucial for viral replication, using potential inhibitors derived from marine bacterial compounds.
View Article and Find Full Text PDFJ Chem Inf Model
January 2025
Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States.
In the field of computational chemistry, predicting bond dissociation energies (BDEs) presents well-known challenges, particularly due to the multireference character of reactive systems. Many chemical reactions involve configurations where single-reference methods fall short, as the electronic structure can significantly change during bond breaking. As generating training data for partially broken bonds is a challenging task, even state-of-the-art reactive machine learning interatomic potentials (MLIPs) often fail to predict reliable BDEs and smooth dissociation curves.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!