With the aim of developing novel anti-SARS-CoV-2 drugs to address the ongoing evolution and emergence of drug-resistant strains, the reported SARS-CoV-2 M inhibitor was selected as a lead to find novel, highly potent, and broad-spectrum inhibitors. Using a fragment-based multilevel virtual screening strategy, 15 hit compounds were identified and subsequently synthesized. Among them, (IC = 1.05 μM), (IC = 1.08 μM), and (IC = 0.154 μM) demonstrated potent SARS-CoV-2 M inhibition comparable to or slightly weaker than . Antiviral activity evaluations revealed that compound exhibited the strongest antiviral activity with an EC value of 0.18 μM, quite comparable to the marketed drug Nirmatrelvir (EC = 0.123 μM) and inferior to (EC = 0.042 μM). Molecular dynamics simulations elucidated the key interactions between compounds , , , and the binding pocket of SARS-CoV-2 M, providing valuable insights into their mechanisms of action. These findings identify compound as a promising lead for anti-SARS-CoV-2 drug development.
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http://dx.doi.org/10.3390/ijms26020670 | DOI Listing |
Mol Divers
January 2025
Key Laboratory for Macromolecular Science of Shaanxi Province, School of Chemistry and Chemical Engineering, Shaanxi Normal University, Xi'an, 710119, People's Republic of China.
Molecular Property Prediction (MPP) is a fundamental task in important research fields such as chemistry, materials, biology, and medicine, where traditional computational chemistry methods based on quantum mechanics often consume substantial time and computing power. In recent years, machine learning has been increasingly used in computational chemistry, in which graph neural networks have shown good performance in molecular property prediction tasks, but they have some limitations in terms of generalizability, interpretability, and certainty. In order to address the above challenges, a Multiscale Molecular Structural Neural Network (MMSNet) is proposed in this paper, which obtains rich multiscale molecular representations through the information fusion between bonded and non-bonded "message passing" structures at the atomic scale and spatial feature information "encoder-decoder" structures at the molecular scale; a multi-level attention mechanism is introduced on the basis of theoretical analysis of molecular mechanics in order to enhance the model's interpretability; the prediction results of MMSNet are used as label values and clustered in the molecular library by the K-NN (K-Nearest Neighbors) algorithm to reverse match the spatial structure of the molecules, and the certainty of the model is quantified by comparing virtual screening results across different K-values.
View Article and Find Full Text PDFInt J Mol Sci
January 2025
Key Laboratory of Chemical Biology (Ministry of Education), Department of Medicinal Chemistry, School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, 44 West Culture Road, Jinan 250012, China.
With the aim of developing novel anti-SARS-CoV-2 drugs to address the ongoing evolution and emergence of drug-resistant strains, the reported SARS-CoV-2 M inhibitor was selected as a lead to find novel, highly potent, and broad-spectrum inhibitors. Using a fragment-based multilevel virtual screening strategy, 15 hit compounds were identified and subsequently synthesized. Among them, (IC = 1.
View Article and Find Full Text PDFSleep Med X
December 2025
Research Group 'Chronobiology, Nutrition and Health' of Federal University of Alagoas, Maceió, Alagoas, Brazil.
Objective: To examine the influence of latitude, longitude, sunrise, and daylight, in conjunction with individual and behavioral factors, on sleep duration, wake time, and bedtime in a country with the world's broadest latitude range, yet characterized by homogeneity in language, cultural traits, and consistent time zones.
Methods: Participants (n = 1440; 18-65y) were part of a virtual population-based survey (2021-22). Sleep patterns were spatially represented through maps using Multilevel B-spline Interpolation.
Arch Womens Ment Health
January 2025
Department of Psychology, University of Wisconsin-Madison, 1202 W. Johnson St, Madison, WI, 53706, USA.
Purpose: Given the lack of available and effective interventions to address the detrimental consequences of perinatal exposure to intimate partner violence (IPV) on maternal mental health, and reported very low access to IPV-related mental health services in Mexico, we examined the feasibility and efficacy of a culturally adapted, virtual, brief group psychosocial intervention designed to improve maternal mental and physical health and reduce IPV revictimization for pregnant women exposed to IPV. In this pilot randomized controlled trial, we evaluated maternal outcomes after participation in the Pregnant Moms' Empowerment Program (PMEP) in Mexico.
Methods: Women were recruited from social service agencies and health centers in the community, as well as social media advertisements that targeted pregnant women living in Mexico.
Cancer Epidemiol Biomarkers Prev
January 2025
University of Connecticut, Storrs, CT, United States.
Background: While community engagement has had a substantial presence in public health research, community input to inform geospatial and health analyses remains underutilized and novel. This manuscript reports on community engagement activities to solicit stakeholder perspectives on the role of neighborhood conditions in health and cancer. We discuss how this community input refined a priori conceptual model to be tested in the larger Families, Friends, and Neighborhoods (FFAN) Study.
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