Introduction: There is an urgent need to discover novel antibiotics to overcome the growing problem of antibiotic resistance, which has become a serious concern in current medicine. Ketolides, the third generation of macrolide antibiotics, have shown promising effect against macrolide-resistant pathogens in respiratory diseases. Currently, a number of ketolide derivatives with excellent antibacterial activities have been reported, while their structure-activity relationships (SARs) were rarely explored systematically. Computer-aided drug design (CADD) such as 3D-QSAR and molecular docking are useful tools to study drug SARs in medicinal chemistry. Using these technologies, ketolide derivatives were systemically analyzed revealing important useful information about their SARs, providing useful information which can guide new drug design and optimization.
Areas Covered: The authors provide an overview of the currently reported 3D-QSAR models of ketolide derivatives. The authors present a comprehensive SAR model obtained from in-depth 3D-QSAR and molecular docking analysis for all kinds of ketolide derivatives.
Expert Opinion: 3D-QSAR has been shown to be a reliable tool that had successfully assisted the design of several new antibiotics with improved activity and reduced toxicity. By applying 3D-QSAR and molecular docking, a comprehensive and systematic SAR model for ketolide derivative discovery was formed, which is important to guide future drug design for the discovery of better ketolides with lower toxicity.
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http://dx.doi.org/10.1517/17460441.2013.774369 | DOI Listing |
SAR QSAR Environ Res
December 2024
College of Chemistry and Chemical Engineering, Qiqihar University, Qiqihar, P. R. China.
Bromodomain-containing protein 4 (BRD4) plays an important role in gene transcription in a variety of diseases, including inflammation and cancer. However, the mechanism by which the BRD4 inhibitors bind selectively to its bromodomain 1 (BRD4-BD1) and bromodomain 2 (BRD4-BD2) remains unclear. Studying the interaction mechanism between bromodomain of BRD4 and inhibitors will provide new ideas for drug development and disease treatment.
View Article and Find Full Text PDFSAR QSAR Environ Res
December 2024
Department of Biotechnology, RV College of Engineering, Bengaluru, India.
The Nipah virus (NiV) is an emerging pathogenic paramyxovirus that causes severe viral infection with a high mortality rate. This study aimed to model the effectual binding of marine sponge-derived natural compounds (MSdNCs) towards RNA-directed RNA polymerase (RdRp) of NiV. Based on the functional relevance, RdRp of NiV was selected as the prospective molecular target and 3D-structure, not available in its native form, was modelled.
View Article and Find Full Text PDFSAR QSAR Environ Res
December 2024
School of Computing and Data Sciences, FLAME University, Pune, India.
This study illustrates the use of chemical fingerprints with machine learning for blood-brain barrier (BBB) permeability prediction. Employing the Blood Brain Barrier Database (B3DB) dataset for BBB permeability prediction, we extracted nine different fingerprints. Support Vector Machine (SVM) and Extreme Gradient Boosting (XGBoost) algorithms were used to develop models for permeability prediction.
View Article and Find Full Text PDFSAR QSAR Environ Res
December 2024
Structural Biology and Biocomputing Lab, Department of Bioinformatics, Alagappa University, Karaikudi, India.
Diabetes mellitus (DM) affects over 77 million adults in India, with cases expected to reach 134 million by 2045. Current treatments, including sulfonylureas and thiazolidinediones, are inadequate, underscoring the need for novel therapeutic strategies. This study investigates marine natural products (MNPs) as alternative therapeutic agents targeting SIK2, a key enzyme involved in DM.
View Article and Find Full Text PDFOrg Biomol Chem
January 2025
Department of Chemistry, Indian Institute of Technology Kharagpur, Kharagpur 721 302, India.
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