Comprehensive investigation on synthesis, computational, antioxidant, antimicrobial, and bio-imaging studies of salicylaldehyde-based Schiff bases

IF 2.218 Q2 Chemistry Chemical Data Collections Pub Date : 2025-02-01 DOI:10.1016/j.cdc.2025.101184
Unnati P. Patel , Shweta P. Thakar , Krishna Desai , Ranjitsinh C. Dabhi , Suryajit L. Rathod , Pranav S. Shrivastav , Jayesh J. Maru
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引用次数: 0

Abstract

The escalating resistance to antimicrobial drugs has become a significant public health concern, presenting significant challenges to the treatment and control of bacterial infections, thereby calling for the development of novel antimicrobial agents. Previous studies have reported diverse biological applications of Schiff bases, including antimicrobial, antiviral, and antimalarial. In that regard, we synthesized a series of salicylaldehyde-based Schiff base derivatives and analyzed their chemical structures using IR spectroscopy, 1H NMR, 13C NMR, mass spectrometry, and elemental analysis. The synthesized compounds were evaluated for their antimicrobial and antioxidant activities. Further, computational molecular docking was used to assess the drug-likeness properties of seventeen newly synthesized Schiff bases. These compounds were tested against two bacterial protein targets, namely PDB ID: 3UDI and 4CJN. Additionally, molecular dynamics simulations of over 100 ns were performed to monitor the complex's behavior and assess its stability over time. The outcomes revealed that the simulated complex remained stable throughout the simulation period. Moreover, the compounds CF5 and CF15 were then employed for bio-imaging studies using nematodes as a model organism.
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Chemical Data Collections
Chemical Data Collections Chemistry-Chemistry (all)
CiteScore
6.10
自引率
0.00%
发文量
169
审稿时长
24 days
期刊介绍: Chemical Data Collections (CDC) provides a publication outlet for the increasing need to make research material and data easy to share and re-use. Publication of research data with CDC will allow scientists to: -Make their data easy to find and access -Benefit from the fast publication process -Contribute to proper data citation and attribution -Publish their intermediate and null/negative results -Receive recognition for the work that does not fit traditional article format. The research data will be published as ''data articles'' that support fast and easy submission and quick peer-review processes. Data articles introduced by CDC are short self-contained publications about research materials and data. They must provide the scientific context of the described work and contain the following elements: a title, list of authors (plus affiliations), abstract, keywords, graphical abstract, metadata table, main text and at least three references. The journal welcomes submissions focusing on (but not limited to) the following categories of research output: spectral data, syntheses, crystallographic data, computational simulations, molecular dynamics and models, physicochemical data, etc.
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