The new AlphaFold model demonstrates substantially improved accuracy over many previous specialized tools: far greater accuracy for protein–ligand interactions compared with state-of-the-art docking tools, much higher accuracy for protein–nucleic acid interactions compared with nucleic-acid-specific predictors and substantially higher antibody–antigen prediction accuracy.
In the past two years, significant updates were made to PubChem, including the co-occurrence data underlying the literature knowledge panel, enabling users to exploit semantic web technologies to explore entity relationships based on the co-occurrences in the scientific literature.
Amber is a molecular dynamics software package first conceived by Peter Kollman, his lab and collaborators to simulate biomolecular systems and recently added capabilities are described in this Application Note.
Current studies on curcumin’s chemical, bioactive, and pharmacological properties are reviewed, indicating the need for future research to elucidate curcumin’s mechanism of action, safety, efficacy, and therapeutic potential for treating various human and animal diseases.
Condensates possess tunable emergent properties such as interfaces, interfacial tension, viscoelasticity, network structure, dielectric permittivity, and sometimes interphase pH gradients and electric potentials.
A comprehensive understanding of cytokine-mediated inflammatory pathways and the interplay with antioxidants is paramount for developing natural therapeutic agents targeting inflammation-related disorders and helping to improve clinical outcomes and enhance the quality of life for patients.
By mining the metagenomic ‘dark matter’ (unclassified DNA with unknown function) of a microbial community specialized in lignocellulose degradation, a metalloenzyme is discovered that oxidatively cleaves cellulose and enables the conversion of agro-industrial residues into value-added bioproducts, thereby contributing to the transition to a sustainable and bio-based economy.
The proteomic mechanisms by which AgNPs exert their antimicrobial effects are investigated, with a special focus on their activity against planktonic bacteria and in biofilms and the issue of resistance to antibiotics is addressed.
The narrow-window data-independent acquisition (nDIA) strategy consisting of high-resolution MS1 scans with parallel tandem MS/MS scans of ~200 Hz using 2-Th isolation windows is presented, dissolving the differences between data-dependent and -independent methods.
Tethered macrocyclic peptide antibiotics with potent antibacterial activity against carbapenem-resistant Acinetobacter baumannii are identified and optimization of tethered macrocyclic peptide (MCP) antibiotics with potent antibacterial activity against CRAB are reported.
A comprehensive overview of the fundamental strategies underlying competitive LFAs is presented, the mathematical models that quantify assay performance are explored, and the critical parameters involved in their design and optimization are outlined.
This review aims to provide a comprehensive overview of cisplatin toxicity, encompassing its underlying mechanisms, risk factors, and emerging therapeutic strategies, and highlights the emerging therapeutic strategies that could be applied to minimize cisplatin-induced toxicities.
An editorial review of key points from the 2020 British Journal of Pharmacology practical guide, which outlines standards for natural products research reports, is highlighted and papers published in BJP between years 2020 to 2023 that demonstrate adherence to these guidelines are provided.
These findings identify an unusual mechanism of lipid transport inhibition, reveal a druggable conformation of the Lpt transporter and provide the foundation for extending this class of antibiotics to other Gram-negative pathogens.
A comprehensive review of the applications of LC MS/MS methods for the analysis of mRNA identity, 5′ capping efficiency and poly(A) tail length and heterogeneity is provided.
The mechanisms by which complex polyphenols act as antioxidative, anti-inflammatory, and anticancer agents have been discussed and their role in food enrichment is discussed.
How microfluidics offers a superior alternative to conventional physical, chemical, and biological synthesis methods for NP synthesis is explored, and the potential of integrating microfluidics with machine learning algorithms to develop "intelligent microfluidics" for NP synthesis is examined.
In this paper, several new extensions of the DFTB method have been developed and implemented in the DFTB+ program package in order to improve the accuracy and generality of the available simulation results.
This review highlights the latest advancements in the green synthesis of ZnO NPs and their biomedical applications, showcasing their potential to revolutionize the field with eco-friendly and cost-effective solutions.
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