Putative binding mode of Escherichia coli exopolyphosphatase and polyphosphates based on a hybrid in silico/biochemical approach

2016 ◽  
Vol 606 ◽  
pp. 64-72 ◽  
Author(s):  
Cristhian Boetsch ◽  
Daniel R. Aguayo-Villegas ◽  
Fernando D. Gonzalez-Nilo ◽  
Á. Teresita Lisa ◽  
Paola R. Beassoni
Keyword(s):  
Escherichia Coli ◽  
In Silico ◽  
Binding Mode ◽  
Biochemical Approach

scholarly journals In silico molecular docking and in vitro antimicrobial efficacy of phytochemicals against multi-drug-resistant enteroaggregative Escherichia coli and non-typhoidal Salmonella spp.

Gut Pathogens ◽  
2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Padikkamannil Abishad ◽  
Pollumahanti Niveditha ◽  
Varsha Unni ◽  
Jess Vergis ◽  
Nitin Vasantrao Kurkure ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Molecular Docking ◽  
In Silico ◽  
Docking Studies ◽  
Antimicrobial Efficacy ◽  
Drug Resistant ◽  
Protein Motifs ◽  
Phytochemical Compounds ◽  
In Silico Molecular Docking

Abstract Background In the wake of emergence of antimicrobial resistance, bioactive phytochemical compounds are proving to be important therapeutic agents. The present study envisaged in silico molecular docking as well as in vitro antimicrobial efficacy screening of identified phytochemical ligands to the dispersin (aap) and outer membrane osmoporin (OmpC) domains of enteroaggregative Escherichia coli (EAEC) and non-typhoidal Salmonella spp. (NTS), respectively. Materials and methods The evaluation of drug-likeness, molecular properties, and bioactivity of the identified phytocompounds (thymol, carvacrol, and cinnamaldehyde) was carried out using Swiss ADME, while Protox-II and StopTox servers were used to identify its toxicity. The in silico molecular docking of the phytochemical ligands with the protein motifs of dispersin (PDB ID: 2jvu) and outer membrane osmoporin (PDB ID: 3uu2) were carried out using AutoDock v.4.20. Further, the antimicrobial efficacy of these compounds against multi-drug resistant EAEC and NTS strains was determined by estimating the minimum inhibitory concentrations and minimum bactericidal concentrations. Subsequently, these phytochemicals were subjected to their safety (sheep and human erythrocytic haemolysis) as well as stability (cationic salts, and pH) assays. Results All the three identified phytochemicals ligands were found to be zero violators of Lipinski’s rule of five and exhibited drug-likeness. The compounds tested were categorized as toxicity class-4 by Protox-II and were found to be non- cardiotoxic by StopTox. The docking studies employing 3D model of dispersin and ompC motifs with the identified phytochemical ligands exhibited good binding affinity. The identified phytochemical compounds were observed to be comparatively stable at different conditions (cationic salts, and pH); however, a concentration-dependent increase in the haemolytic assay was observed against sheep as well as human erythrocytes. Conclusions In silico molecular docking studies provided useful insights to understand the interaction of phytochemical ligands with protein motifs of pathogen and should be used routinely before the wet screening of any phytochemicals for their antibacterial, stability, and safety aspects.

scholarly journals Exploring aromatic cage flexibility of the histone methyllysine reader protein Spindlin1 and its impact on binding mode prediction: an in silico study

2021 ◽  
Author(s):  
Chiara Luise ◽  
Dina Robaa ◽  
Wolfgang Sippl
Keyword(s):  
Molecular Dynamic ◽  
In Silico ◽  
Binding Pocket ◽  
Binding Mode ◽  
Molecular Dynamic Simulations ◽  
Flexible Docking ◽  
Dynamic Simulations ◽  
Binding Mode Prediction ◽  
Aromatic Cage ◽  
The Right

AbstractSome of the main challenges faced in drug discovery are pocket flexibility and binding mode prediction. In this work, we explored the aromatic cage flexibility of the histone methyllysine reader protein Spindlin1 and its impact on binding mode prediction by means of in silico approaches. We first investigated the Spindlin1 aromatic cage plasticity by analyzing the available crystal structures and through molecular dynamic simulations. Then we assessed the ability of rigid docking and flexible docking to rightly reproduce the binding mode of a known ligand into Spindlin1, as an example of a reader protein displaying flexibility in the binding pocket. The ability of induced fit docking was further probed to test if the right ligand binding mode could be obtained through flexible docking regardless of the initial protein conformation. Finally, the stability of generated docking poses was verified by molecular dynamic simulations. Accurate binding mode prediction was obtained showing that the herein reported approach is a highly promising combination of in silico methods able to rightly predict the binding mode of small molecule ligands in flexible binding pockets, such as those observed in some reader proteins.

scholarly journals Metabolic Engineering of Escherichia coli for Enhanced Production of Succinic Acid, Based on Genome Comparison and In Silico Gene Knockout Simulation

2005 ◽  
Vol 71 (12) ◽  
pp. 7880-7887 ◽  
Author(s):  
Sang Jun Lee ◽  
Dong-Yup Lee ◽  
Tae Yong Kim ◽  
Byung Hun Kim ◽  
Jinwon Lee ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Succinic Acid ◽  
In Silico ◽  
Acid Production ◽  
Gene Knockout ◽  
Fermentation Products ◽  
E Coli ◽  
Metabolic Analysis ◽  
Enhanced Production ◽  
Succinic Acid Production

ABSTRACT Comparative analysis of the genomes of mixed-acid-fermenting Escherichia coli and succinic acid-overproducing Mannheimia succiniciproducens was carried out to identify candidate genes to be manipulated for overproducing succinic acid in E. coli. This resulted in the identification of five genes or operons, including ptsG, pykF, sdhA, mqo, and aceBA, which may drive metabolic fluxes away from succinic acid formation in the central metabolic pathway of E. coli. However, combinatorial disruption of these rationally selected genes did not allow enhanced succinic acid production in E. coli. Therefore, in silico metabolic analysis based on linear programming was carried out to evaluate the correlation between the maximum biomass and succinic acid production for various combinatorial knockout strains. This in silico analysis predicted that disrupting the genes for three pyruvate forming enzymes, ptsG, pykF, and pykA, allows enhanced succinic acid production. Indeed, this triple mutation increased the succinic acid production by more than sevenfold and the ratio of succinic acid to fermentation products by ninefold. It could be concluded that reducing the metabolic flux to pyruvate is crucial to achieve efficient succinic acid production in E. coli. These results suggest that the comparative genome analysis combined with in silico metabolic analysis can be an efficient way of developing strategies for strain improvement.

scholarly journals In silico profiling of Escherichia coli and Saccharomyces cerevisiae as terpenoid factories

2013 ◽  
Vol 12 (1) ◽  
pp. 84 ◽  
Author(s):  
Evamaria Gruchattka ◽  
Oliver Hädicke ◽  
Steffen Klamt ◽  
Verena Schütz ◽  
Oliver Kayser
Keyword(s):  
Escherichia Coli ◽  
Saccharomyces Cerevisiae ◽  
In Silico

scholarly journals Binding Mode Knowledge of New Possible Anti-Hypertensive Compounds Designed In Silico Using Neutral Endopeptidase (NEP) as a Target

2020 ◽  
Author(s):  
Emilio Lamazares ◽  
Yudith Cañizares-Carmenate ◽  
Juan A. Castillo-Garit ◽  
Karel Mena-Ulecia
Keyword(s):  
Arterial Hypertension ◽  
In Silico ◽  
Neutral Endopeptidase ◽  
Binding Mode ◽  
Dynamics Simulation ◽  
Energy Decomposition ◽  
Simulation Tools ◽  
Free Energy Decomposition ◽  
Key Enzyme ◽  
New Compounds

Arterial hypertension is a health problem that affects millions of people around the world. Particularly in Chile, according to the last health survey in 2019, 28.7% of the population had this condition, and arterial hypertension complications cause one in three deaths per year. In this work, we have used molecular simulation tools to evaluate new compounds designed in silico by our group as possible anti-hypertensive agents, taking Neutral Endopeptidase (NEP) as a target, a key enzyme in the arterial hypertension regulation at the level kidney. We use docking experiments, molecular dynamics simulation, free energy decomposition calculations (by MM-PBSA method), and ligand efficiency analysis to identify the best anti-hypertensive agent pharmacokinetic and toxicological predictions (ADME-Tox). The energetic components that contribute to the complexes stability are the electrostatic and Van der Waals components; however, when the ADME-Tox properties were analyzed, we conclude that the best anti-hypertensive candidate agents are Lig783 and Lig3444, taking Neutra Endopeptidase as a target.

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