scholarly journals In-silico investigation of antibacterial herbal compounds in order to find new antibiotic against Staphylococcus aureus and its resistant subtypes

2022 ◽  
pp. 100843
Author(s):  
Fatemeh Abedi Dorcheh ◽  
Negar Balmeh ◽  
Sahar Sanjari
Keyword(s):  
Staphylococcus Aureus ◽  
In Silico

scholarly journals Studi Interaksi Molekuler Aktivitas Antimikroba Peptida Bioaktif terhadap Staphylococcus aureus Secara In silico

2020 ◽  
Vol 7 (2) ◽  
pp. 93
Author(s):  
Taufik Muhammad Fakih ◽  
Mentari Luthfika Dewi
Keyword(s):  
Staphylococcus Aureus ◽  
In Silico ◽  
Binding Protein ◽  
Pelteobagrus Fulvidraco ◽  
Penicillin Binding Protein ◽  
Discovery Studio

Pendahuluan: Lendir kulit ikan lele kuning (Pelteobagrus fulvidraco), mengandung peptida bioaktif dan banyak dimanfaatkan dalam pengobatan berbagai penyakit karena memiliki aktivitas biologis, diantaranya sebagai antimikroba. Beberapa peptida bioaktif tersebut, antara lain pelteobagrin, myxinidin, pleurocidin, dan pardaxin-P1 dan telah terbukti mampu menghambat Penicillin-Binding Protein 3 (PBP3) dari Staphylococcus aureus. Tujuan: Penelitian ini bertujuan untuk mengidentifikasi aktivitas antimikroba molekul peptida bioaktif secara in silico terhadap makromolekul Penicillin-Binding Protein 3 (PBP3) dari Staphylococcus aureus dan interaksi peptida bioaktif tersebut yang terlibat dalam mekanisme aksi antimikroba. Metode: Sekuensing peptida bioaktif terlebih dahulu dilakukan pemodelan ke dalam bentuk konformasi 3D menggunakan software PEP-FOLD. Konformasi terbaik hasil pemodelan dipilih untuk kemudian dilakukan studi penambatan molekuler terhadap makromolekul dari Staphylococcus aureus menggunakan software PatchDock. Interaksi molekuler yang terbentuk selanjutnya diidentifikasi lebih lanjut menggunakan software BIOVIA Discovery Studio 2020. Hasil: Berdasarkan hasil penambatan molekuler menunjukkan bahwa peptida bioaktif myxinidin memiliki afinitas paling baik dengan ACE score −2497,26 kJ/mol. Kesimpulan: Peptida bioaktif lendir kulit ikan lele kuning (Pelteobagrus fulvidraco) dapat dipertimbangkan sebagai kandidat antimikroba alami.

scholarly journals Mutations in fusA Associated with Posttherapy Fusidic Acid Resistance in Clostridium difficile

2007 ◽  
Vol 51 (5) ◽  
pp. 1840-1843 ◽  
Author(s):  
T. Norén ◽  
T. Åkerlund ◽  
M. Wullt ◽  
L. G. Burman ◽  
M. Unemo
Keyword(s):  
Staphylococcus Aureus ◽  
Clostridium Difficile ◽  
Fusidic Acid ◽  
In Silico ◽  
Acid Resistance ◽  
Nonsynonymous Substitutions ◽  
Resistant Mutants

ABSTRACT In silico, we identified fusA (2,067 bp) in Clostridium difficile 630. Sequencing of fusA in posttherapy fusidic acid-resistant C. difficile isolates from 12 patients with C. difficile-associated diarrhea (CDAD) identified fusA mutations, one or two nonsynonymous substitutions, or in one case a deletion of one codon associated with resistance. Five of these mutations have previously been described in fusA of fusidic acid-resistant Staphylococcus aureus, but seven were novel fusA mutations. Fusidic acid monotherapy for CDAD seemed to rapidly select conserved resistant mutants.

scholarly journals In silico designing and molecular docking of a potent analog against Staphylococcus aureus porphobilinogen synthase

2014 ◽  
Vol 6 (3) ◽  
pp. 158 ◽  
Author(s):  
Potukuchi VenkataGurunatha Krishna Sarma ◽  
Gopal Sowjenya ◽  
Lokanathan Srikanth ◽  
Vimjam Swarupa ◽  
Katari Venkatesh ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Molecular Docking ◽  
In Silico ◽  
Porphobilinogen Synthase

scholarly journals Inhibition and Biochemical Characterization of Methicillin-Resistant Staphylococcus aureus Shikimate Dehydrogenase: An in Silico and Kinetic Study

Molecules ◽  
2014 ◽  
Vol 19 (4) ◽  
pp. 4491-4509 ◽  
Author(s):  
Claudia Avitia-Domínguez ◽  
Erick Sierra-Campos ◽  
José Salas-Pacheco ◽  
Hugo Nájera ◽  
Arturo Rojo-Domínguez ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Kinetic Study ◽  
In Silico ◽  
Methicillin Resistant Staphylococcus Aureus ◽  
Biochemical Characterization ◽  
Shikimate Dehydrogenase ◽  
Methicillin Resistant

scholarly journals Comparative Genome-Scale Metabolic Reconstruction and Flux Balance Analysis of Multiple Staphylococcus aureus Genomes Identify Novel Antimicrobial Drug Targets

2009 ◽  
Vol 191 (12) ◽  
pp. 4015-4024 ◽  
Author(s):  
Deok-Sun Lee ◽  
Henry Burd ◽  
Jiangxia Liu ◽  
Eivind Almaas ◽  
Olaf Wiest ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Flux Balance Analysis ◽  
In Silico ◽  
Drug Targets ◽  
Gene Deletion ◽  
Multidrug Resistant ◽  
Antimicrobial Drug ◽  
Metabolic Reconstruction ◽  
Flux Balance ◽  
Balance Analysis

ABSTRACT Mortality due to multidrug-resistant Staphylococcus aureus infection is predicted to surpass that of human immunodeficiency virus/AIDS in the United States. Despite the various treatment options for S. aureus infections, it remains a major hospital- and community-acquired opportunistic pathogen. With the emergence of multidrug-resistant S. aureus strains, there is an urgent need for the discovery of new antimicrobial drug targets in the organism. To this end, we reconstructed the metabolic networks of multidrug-resistant S. aureus strains using genome annotation, functional-pathway analysis, and comparative genomic approaches, followed by flux balance analysis-based in silico single and double gene deletion experiments. We identified 70 single enzymes and 54 pairs of enzymes whose corresponding metabolic reactions are predicted to be unconditionally essential for growth. Of these, 44 single enzymes and 10 enzyme pairs proved to be common to all 13 S. aureus strains, including many that had not been previously identified as being essential for growth by gene deletion experiments in S. aureus. We thus conclude that metabolic reconstruction and in silico analyses of multiple strains of the same bacterial species provide a novel approach for potential antibiotic target identification.

scholarly journals Detecting Staphylococcus aureus Virulence and Resistance Genes: a Comparison of Whole-Genome Sequencing and DNA Microarray Technology

2016 ◽  
Vol 54 (4) ◽  
pp. 1008-1016 ◽  
Author(s):  
Lena Strauß ◽  
Ulla Ruffing ◽  
Salim Abdulla ◽  
Abraham Alabi ◽  
Ruslan Akulenko ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Dna Microarray ◽  
Resistance Genes ◽  
In Silico ◽  
Target Genes ◽  
Whole Genome ◽  
Microarray Hybridization ◽  
Content Type

Staphylococcus aureusis a major bacterial pathogen causing a variety of diseases ranging from wound infections to severe bacteremia or intoxications. Besides host factors, the course and severity of disease is also widely dependent on the genotype of the bacterium. Whole-genome sequencing (WGS), followed by bioinformatic sequence analysis, is currently the most extensive genotyping method available. To identify clinically relevant staphylococcal virulence and resistance genes in WGS data, we developed anin silicotyping scheme for the software SeqSphere+(Ridom GmbH, Münster, Germany). The implemented target genes (n= 182) correspond to those queried by the IdentibacS. aureusGenotyping DNA microarray (Alere Technologies, Jena, Germany). Thein silicoscheme was evaluated by comparing the typing results of microarray and of WGS for 154 humanS. aureusisolates. A total of 96.8% (n= 27,119) of all typing results were equally identified with microarray and WGS (40.6% present and 56.2% absent). Discrepancies (3.2% in total) were caused by WGS errors (1.7%), microarray hybridization failures (1.3%), wrong prediction of ambiguous microarray results (0.1%), or unknown causes (0.1%). Superior to the microarray, WGS enabled the distinction of allelic variants, which may be essential for the prediction of bacterial virulence and resistance phenotypes. Multilocus sequence typing clonal complexes and staphylococcal cassette chromosomemecelement types inferred from microarray hybridization patterns were equally determined by WGS. In conclusion, WGS may substitute array-based methods due to its universal methodology, open and expandable nature, and rapid parallel analysis capacity for different characteristics in once-generated sequences.

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