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Antibiotics

Overview of attention for book
Cover of 'Antibiotics'

Table of Contents

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    Book Overview
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    Chapter 1 Antibiotics: Precious Goods in Changing Times
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    Chapter 2 Mining Bacterial Genomes for Secondary Metabolite Gene Clusters
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    Chapter 3 Production of Antimicrobial Compounds by Fermentation
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    Chapter 4 Structure Elucidation of Antibiotics by NMR Spectroscopy
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    Chapter 5 Computer-Aided Drug Design Methods
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    Chapter 6 Cytotoxicity Assays as Predictors of the Safety and Efficacy of Antimicrobial Agents
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    Chapter 7 Application of a Bacillus subtilis Whole-Cell Biosensor (PliaI-lux) for the Identification of Cell Wall Active Antibacterial Compounds
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    Chapter 8 Determination of Bacterial Membrane Impairment by Antimicrobial Agents
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    Chapter 9 Mass-Sensitive Biosensor Systems to Determine the Membrane Interaction of Analytes
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    Chapter 10 Measurement of Cell Membrane Fluidity by Laurdan GP: Fluorescence Spectroscopy and Microscopy
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    Chapter 11 In Vitro Assays to Identify Antibiotics Targeting DNA Metabolism
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    Chapter 12 Fluorescence-Based Real-Time Activity Assays to Identify RNase P Inhibitors
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    Chapter 13 Reporter Gene-Based Screening for TPP Riboswitch Activators
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    Chapter 14 Cell-Based Fluorescent Screen to Identify Inhibitors of Bacterial Translation Initiation
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    Chapter 15 Bacterial Histidine Kinases: Overexpression, Purification, and Inhibitor Screen
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    Chapter 16 Expression Profiling of Antibiotic-Resistant Bacteria Obtained by Laboratory Evolution
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    Chapter 17 Sample Preparation for Mass-Spectrometry Based Absolute Protein Quantification in Antibiotic Stress Research
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    Chapter 18 Label-Free Quantitation of Ribosomal Proteins from Bacillus subtilis for Antibiotic Research
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    Chapter 19 Functional Metagenomics to Study Antibiotic Resistance
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    Chapter 20 Epidemiological Surveillance and Typing Methods to Track Antibiotic Resistant Strains Using High Throughput Sequencing
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    Chapter 21 Erratum
Attention for Chapter 5: Computer-Aided Drug Design Methods
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

Mentioned by

blogs
1 blog
patent
2 patents
facebook
1 Facebook page
googleplus
1 Google+ user

Citations

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19 Dimensions

Readers on

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788 Mendeley
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Chapter title
Computer-Aided Drug Design Methods
Chapter number 5
Book title
Antibiotics
Published in
Methods in molecular biology, January 2017
DOI 10.1007/978-1-4939-6634-9_5
Pubmed ID
Book ISBNs
978-1-4939-6632-5, 978-1-4939-6634-9
Authors

Wenbo Yu, Alexander D. MacKerell Jr., Alexander D. MacKerellJr., Alexander D. MacKerell, Jr., Alexander D. MacKerell, Yu, Wenbo, MacKerell, Alexander D.

Editors

Peter Sass

Abstract

Computational approaches are useful tools to interpret and guide experiments to expedite the antibiotic drug design process. Structure-based drug design (SBDD) and ligand-based drug design (LBDD) are the two general types of computer-aided drug design (CADD) approaches in existence. SBDD methods analyze macromolecular target 3-dimensional structural information, typically of proteins or RNA, to identify key sites and interactions that are important for their respective biological functions. Such information can then be utilized to design antibiotic drugs that can compete with essential interactions involving the target and thus interrupt the biological pathways essential for survival of the microorganism(s). LBDD methods focus on known antibiotic ligands for a target to establish a relationship between their physiochemical properties and antibiotic activities, referred to as a structure-activity relationship (SAR), information that can be used for optimization of known drugs or guide the design of new drugs with improved activity. In this chapter, standard CADD protocols for both SBDD and LBDD will be presented with a special focus on methodologies and targets routinely studied in our laboratory for antibiotic drug discoveries.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 788 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 788 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 110 14%
Student > Master 101 13%
Student > Ph. D. Student 80 10%
Researcher 57 7%
Student > Doctoral Student 28 4%
Other 95 12%
Unknown 317 40%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 140 18%
Chemistry 113 14%
Pharmacology, Toxicology and Pharmaceutical Science 88 11%
Agricultural and Biological Sciences 27 3%
Engineering 16 2%
Other 73 9%
Unknown 331 42%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 14. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 September 2022.
All research outputs
#2,668,526
of 25,837,817 outputs
Outputs from Methods in molecular biology
#451
of 14,425 outputs
Outputs of similar age
#51,202
of 425,363 outputs
Outputs of similar age from Methods in molecular biology
#66
of 1,089 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 14,425 research outputs from this source. They receive a mean Attention Score of 3.5. This one has done particularly well, scoring higher than 96% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 425,363 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 1,089 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.