Development of Novel Antibiotics for the Treatment of Acinetobacter and Related Pathogens

2012 ◽  
Author(s):  
Paul J. Hergenrother
Keyword(s):  
Novel Antibiotics

Investigation of interspecies interactions between marine micromonosporaceae for identification of novel antibiotics

Planta Medica ◽  
2015 ◽  
Vol 81 (11) ◽  
Author(s):  
N Adnani ◽  
E Vazquez-Rivera ◽  
S Adibhatla ◽  
GA Ellis ◽  
D Braun ◽  
...  
Keyword(s):  
Interspecies Interactions ◽  
Novel Antibiotics

Novel Antibiotics from Marine Sources

2011 ◽  
Vol 4 (3) ◽  
pp. 1446-1461 ◽  
Author(s):  
E.A. Martis ◽  
G M Doshi ◽  
G V Aggarwal ◽  
P P Shanbhag
Keyword(s):  
Pharmaceutical Industry ◽  
Resistant Bacteria ◽  
Drug Resistant ◽  
Drug Resistant Bacteria ◽  
Terrestrial Life ◽  
New Antibiotics ◽  
Antibiotic Compounds ◽  
New Generation ◽  
Novel Antibiotics ◽  
Untapped Resource

With the emergence of newer diseases, resistant forms of infectious diseases and multi-drug resistant bacteria, it has become essential to develop novel and more effective antibiotics. Current antibiotics are obtained from terrestrial life or made synthetically from intermediates. The ocean represents virtually untapped resource from which novel antibiotic compounds can be discovered. It is the marine world that will provide the pharmaceutical industry with the next generation of antibiotics. Marine antibiotics are antibiotics obtained from marine organisms. Scientists have reported the discovery of various antibiotics from marine bacteria (aplasmomycin, himalomycins, and pelagiomycins), sponges (Ara C, variabillin, strobilin, ircinin-1, aeroplysin, 3,5-dibromo-4-hydroxyphenylacetamide), coelenterates (asperidol and eunicin), mollusks (laurinterol and pachydictyol), tunicates (geranylhydroquinone and cystadytins), algae (cycloeudesmol, aeroplysinin-1(+), prepacifenol and tetrabromoheptanone), worms (tholepin and 3,5-dibromo-4-hydroxybezaldehyde), and actinomycetes (marinomycins C and D). This indicates that the marine environment, representing approximately half of the global diversity, is an enormous resource for new antibiotics and this source needs to be explored for the discovery of new generation antibiotics. The present article provides an overview of various antibiotics obtained from marine sources.

scholarly journals A novel chemical biology and computational approach to expedite the discovery of new-generation polymyxins against life-threatening Acinetobacter baumannii

2021 ◽  
Author(s):  
Xukai Jiang ◽  
Nitin A. Patil ◽  
Mohammad A. K. Azad ◽  
Hasini Wickremasinghe ◽  
Heidi Yu ◽  
...  
Keyword(s):  
Public Health ◽  
Chemical Biology ◽  
Multidrug Resistant ◽  
Computational Approach ◽  
Gram Negative Bacteria ◽  
Global Public Health ◽  
Gram Negative ◽  
Life Threatening ◽  
New Generation ◽  
Novel Antibiotics

Multidrug-resistant Gram-negative bacteria have been an urgent threat to global public health. Novel antibiotics are desperately needed to combat these 'superbugs'.

scholarly journals Synergizing the potential of bacterial genomics and metabolomics to find novel antibiotics

2021 ◽  
Author(s):  
Fabian Panter ◽  
Chantal D. Bader ◽  
Rolf Müller
Keyword(s):  
Natural Products ◽  
Antimicrobial Resistance ◽  
Public Concern ◽  
Bacterial Genomics ◽  
Technological Developments ◽  
Novel Antibiotics

Antimicrobial resistance is a major public concern and novel antibiotics are largely based on natural products. We summarize recent analytical and genome based technological developments that gain increasing importance in the natural products field.

scholarly journals Dynamicins O, P and Q: Novel antibiotics related to dynemicin a isolation, characterization and biological activity.

1991 ◽  
Vol 44 (10) ◽  
pp. 1037-1044 ◽  
Author(s):  
MEGUMI MIYOSHI-SAITOH ◽  
NAOKO MORISAKI ◽  
YOSHIYUKI TOKIWA ◽  
SHIGEO IWASAKI ◽  
MASATAKA KONISHI ◽  
...  
Keyword(s):  
Biological Activity ◽  
Novel Antibiotics

scholarly journals Diagnosis Confirmation Model: A Value-Based Pricing Model for Inpatient Novel Antibiotics

2018 ◽  
Vol 46 (S1) ◽  
pp. 66-74 ◽  
Author(s):  
Ka Lum ◽  
Taimur Bhatti ◽  
Silas Holland ◽  
Mark Guthrie ◽  
Stephanie Sassman
Keyword(s):  
High Risk ◽  
Financial Incentives ◽  
Drug Resistant ◽  
Pricing Model ◽  
Pricing Mechanism ◽  
A Value ◽  
Novel Antibiotics

The Diagnosis Confirmation Model (DCM) includes a dual-pricing mechanism designed to support value-based pricing of novel antibiotics while improving the alignment of financial incentives with their optimal use in patients at high risk of drug-resistant infections. DCM is a market-based model and complementary to delinked models. Policymakers interested in stimulating antibiotic innovation could consider tailoring the DCM to their reimbursement systems and incorporating it into the suite of incentives to improve the economics of antibiotics.

scholarly journals LSTrAP-Crowd: Prediction of novel components of bacterial ribosomes with crowd-sourced analysis of RNA sequencing data

2020 ◽  
Author(s):  
Benedict Hew ◽  
Qiao Wen Tan ◽  
William Goh ◽  
Jonathan Wei Xiong Ng ◽  
Kenny Koh ◽  
...  
Keyword(s):  
Gene Expression ◽  
Protein Synthesis ◽  
Rna Sequencing ◽  
Gene Expression Data ◽  
Large Scale ◽  
Bacterial Resistance ◽  
Expression Data ◽  
Sequencing Data ◽  
Novel Proteins ◽  
Novel Antibiotics

AbstractBacterial resistance to antibiotics is a growing problem that is projected to cause more deaths than cancer in 2050. Consequently, novel antibiotics are urgently needed. Since more than half of the available antibiotics target the bacterial ribosomes, proteins that are involved in protein synthesis are thus prime targets for the development of novel antibiotics. However, experimental identification of these potential antibiotic target proteins can be labor-intensive and challenging, as these proteins are likely to be poorly characterized and specific to few bacteria. In order to identify these novel proteins, we established a Large-Scale Transcriptomic Analysis Pipeline in Crowd (LSTrAP-Crowd), where 285 individuals processed 26 terabytes of RNA-sequencing data of the 17 most notorious bacterial pathogens. In total, the crowd processed 26,269 RNA-seq experiments and used the data to construct gene co-expression networks, which were used to identify more than a hundred uncharacterized genes that were transcriptionally associated with protein synthesis. We provide the identity of these genes together with the processed gene expression data. The data can be used to identify other vulnerabilities or bacteria, while our approach demonstrates how the processing of gene expression data can be easily crowdsourced.

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