Leishmaniasis is one of the most neglected diseases worldwide and is considered a serious public health issue. The current therapeutic options have several disadvantages that make the search for new therapeutics urgent. Gold compounds are emerging as promising candidates based on encouraging in vitro and limited in vivo results for several Au and Au complexes. The antiparasitic mechanisms of these molecules remain only partially understood. However, a few studies have proposed the trypanothione redox system as a target, similar to the mammalian thioredoxin system, pointed out as the main target for several gold compounds with significant antitumor activity. In this review, we present the current status of the investigation and design of gold compounds directed at treating leishmaniasis. In addition, we explore potential targets in Leishmania parasites beyond the trypanothione system, taking into account previous studies and structure modulation performed for gold-based compounds.
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http://dx.doi.org/10.1002/cmdc.202100022 | DOI Listing |
Angew Chem Int Ed Engl
January 2025
Griffith University, Griffith School of Environment, Centre for Clean Environment and Energy, 4222, Brisbane, AUSTRALIA.
Converting biomass-derived molecules like 5-hydroxymethylfurfural (HMF) into value-added products alongside hydrogen production using renewable energy offers significant opportunities for sustainable chemical and energy production. Yet, HMF electrooxidation requires strong alkaline conditions and membranes for efficient conversion. These harsh conditions destabilize HMF, leading to humin formation and reduced product purity, meanwhile membranes increase costs.
View Article and Find Full Text PDFSci Rep
January 2025
University of Novi Sad, BioSense Institute, Dr Zorana Djindjica 1, Novi Sad, 21000, Serbia.
Although various sensors specifically developed for target analytes are available, affordable biosensing solutions with broad applicability are limited. In this study, a cost-effective biosensor for detecting human epidermal growth factor receptor 2 (HER2) was developed using custom-made gold leaf electrodes (GLEs). A novel strategy for antibody immobilization on a gold surface, for the first time mediated by protein L and HER2-specific antibody trastuzumab, was examined using commercial screen-printed gold electrodes and GLEs.
View Article and Find Full Text PDFPsychopharmacol Bull
January 2025
Frye, MD, Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA.
Bipolar disorder is a chronic disease that imposes a lifelong burden on those that suffer from it. Lithium is still considered both gold standard treatment and first-line maintenance treatment, and access to treatment with lithium is paramount to improving patient outcomes. However, access to adequate treatment is not only contingent on symptom recognition, accurate diagnosis, and individualization of treatment, but also affected by racial and ethnic disparities at each stage of patient experience.
View Article and Find Full Text PDFJ Cheminform
December 2024
Institute for Inorganic and Analytical Chemistry, Friedrich Schiller University Jena, Lessingstr. 8, 07743, Jena, Germany.
Naming chemical compounds systematically is a complex task governed by a set of rules established by the International Union of Pure and Applied Chemistry (IUPAC). These rules are universal and widely accepted by chemists worldwide, but their complexity makes it challenging for individuals to consistently apply them accurately. A translation method can be employed to address this challenge.
View Article and Find Full Text PDFNat Comput Sci
December 2024
Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
Machine learning plays an important role in quantum chemistry, providing fast-to-evaluate predictive models for various properties of molecules; however, most existing machine learning models for molecular electronic properties use density functional theory (DFT) databases as ground truth in training, and their prediction accuracy cannot surpass that of DFT. In this work we developed a unified machine learning method for electronic structures of organic molecules using the gold-standard CCSD(T) calculations as training data. Tested on hydrocarbon molecules, our model outperforms DFT with several widely used hybrid and double-hybrid functionals in terms of both computational cost and prediction accuracy of various quantum chemical properties.
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