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() infections pose a global health challenge demanding innovative therapeutic strategies by which to eradicate them. Urease, a key virulence factor hydrolyzes urea, facilitating bacterial survival in the acidic gastric environment. In this study, a multi-methodological approach combining pharmacophore- and structure-based virtual screening, molecular dynamics simulations, and MM-GBSA calculations was employed to identify novel inhibitors for urease (U). A refined dataset of 8,271,505 small molecules from the ZINC15 database underwent pharmacokinetic and physicochemical filtering, resulting in 16% of compounds for pharmacophore-based virtual screening. Molecular docking simulations were performed in successive stages, utilizing HTVS, SP, and XP algorithms. Subsequent energetic re-scoring with MM-GBSA identified promising candidates interacting with distinct urease variants. Lys219, a residue critical for urea catalysis at the urease binding site, can manifest in two forms, neutral (LYN) or carbamylated (KCX). Notably, the evaluated molecules demonstrated different interaction and energetic patterns in both protein variants. Further evaluation through ADMET predictions highlighted compounds with favorable pharmacological profiles, leading to the identification of 15 candidates. Molecular dynamics simulations revealed comparable structural stability to the control DJM, with candidates 5, 8 and 12 (CA5, CA8, and CA12, respectively) exhibiting the lowest binding free energies. These inhibitors suggest a chelating capacity that is crucial for urease inhibition. The analysis underscores the potential of CA5, CA8, and CA12 as novel U inhibitors. Finally, we compare our candidates with the chemical space of urease inhibitors finding physicochemical similarities with potent agents such as thiourea.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10888695 | PMC |
http://dx.doi.org/10.3390/ijms25041968 | DOI Listing |
JMIR Form Res
December 2024
School of Journalism and Communication, Beijing Normal University, Beijing, China.
Background: The proliferation of generative artificial intelligence (AI), such as ChatGPT, has added complexity and richness to the virtual environment by increasing the presence of AI-generated content (AIGC). Although social media platforms such as TikTok have begun labeling AIGC to facilitate the ability for users to distinguish it from human-generated content, little research has been performed to examine the effect of these AIGC labels.
Objective: This study investigated the impact of AIGC labels on perceived accuracy, message credibility, and sharing intention for misinformation through a web-based experimental design, aiming to refine the strategic application of AIGC labels.
Biomed Khim
December 2024
Chumakov Federal Scientific Center for Research and Development of Immune-and-Biological Products of Russian Academy of Sciences (Institute of Poliomyelitis), Moscow, Russia; Institute of Translational Medicine and Biotechnology, Sechenov First Moscow State Medical University, Moscow, Russia.
The orthoflavivirus NS1 protein is a relatively understudied target for the design of broad-spectrum anti-orthoflaviviral drugs. Currently, the NS1 protein structures of tick-borne orthoflaviviruses have not been published yet, but these structures can be modelled by homology, thus generating a large amount of structural data. We performed homology modelling of the NS1 protein structures of epidemiologically significant orthoflaviviruses and analysed the possibility of using these models in ensemble docking-based virtual screening.
View Article and Find Full Text PDFBiomed Khim
December 2024
Chemoinformatics Group - NEQUIM, Departamento de Quimica, Instituto de Ciências Exatas, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil.
Traditional testing methods in pharmaceutical development can be time-consuming and costly, but in silico evaluation tools can offer a solution. Our in-house Active-IT system, a Ligand-Based Virtual Screening (LBVS) tool, was developed to predict the biological and pharmacological activities of small organic molecules. It includes four independent modules for generating molecular descriptors (3D-Pharma), machine learning modeling (ExCVBA), a database of bioactivity models, and a prediction module.
View Article and Find Full Text PDFFront Neurol
December 2024
Students Research Committee, Ardabil University of Medical Sciences, Ardabil, Iran.
Background And Aim: Neurodegenerative disorders (e.g., Alzheimer's, Parkinson's) lead to neuronal loss; neurocognitive disorders (e.
View Article and Find Full Text PDFAdv Med Educ Pract
December 2024
Queen Charlotte's and Chelsea Hospital, Imperial College, London, UK.
Purpose: To determine the level of uptake of telemedicine among postgraduate obstetrics and gynaecology (O&G) trainees in London, and how they perceive its impact on their training.
Methods: A mixed-methods survey aimed at exploring trainee perspectives of telemedicine use in clinical practice and its implications for training. Study participants were O&G specialist doctors on the London (UK) training programme.
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