Dataset Information

Identification of novel bacterial DNA gyrase inhibitors: An in silico study.

ABSTRACT: Owing to essential role in bacterial survival, DNA gyrase has been exploited as a validated drug target. However, rapidly emerging resistance to gyrase-targeted drugs such as widely utilized fluoroquinolones reveals the necessity to develop novel compounds with new mechanism of actions against this enzyme. Here, an attempt has been made to identify new drug-like molecules for Shigella flexneri DNA gyrase inhibition through in silico approaches. The structural similarity search was carried out using the natural product simocyclinone D8, a unique gyrase inhibitor, to virtually screen ZINC database. A total of 11830 retrieved hits were further screened for selection of high-affinity compounds by implementing molecular docking followed by investigation of druggability according to Lipinski's rule, biological activity and physiochemical properties. Among the hits initially identified, three molecules were then confirmed to have reasonable gyrase-binding affinity and to follow Lipinski's rule. Based on these in silico findings, three compounds with different chemical structures from previously identified gyrase inhibitors were proposed as potential candidates for the treatment of fluoroquinolone-resistant strains and deserve further investigations.

SUBMITTER: Rahimi H

PROVIDER: S-EPMC4962306 | biostudies-literature | 2016 May-Jun

REPOSITORIES: biostudies-literature

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Identification of novel bacterial DNA gyrase inhibitors: An in silico study.

Rahimi Hamzeh H Najafi Ali A Eslami Habib H Negahdari Babak B Moghaddam Mehrdad Moosazadeh MM

Research in pharmaceutical sciences 20160501 3

Owing to essential role in bacterial survival, DNA gyrase has been exploited as a validated drug target. However, rapidly emerging resistance to gyrase-targeted drugs such as widely utilized fluoroquinolones reveals the necessity to develop novel compounds with new mechanism of actions against this enzyme. Here, an attempt has been made to identify new drug-like molecules for Shigella flexneri DNA gyrase inhibition through in silico approaches. The structural similarity search was carried out us ...[more]

PMID: 27499795

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Project description:Type II topoisomerases like DNA gyrase initiate ATP-dependent negative supercoils in bacterial DNA. It is critical in all of the bacteria but is missing from eukaryotes, making it a striking target for antibacterials. Ciprofloxacin is a clinically approved drug, but its clinical effectiveness is affected by the emergence of resistance in both Gram-positive and Gram-negative bacteria. Thus, it is vital to identify novel compounds that can efficiently inhibit DNA gyrase, and quantitative structure-activity relationship (QSAR) modeling is a quick and economical means to do so. A QSAR-based virtual screening approach was applied to identify new gyrase inhibitors using an in-house-generated combinatorial library of 29828 compounds from seven ciprofloxacin scaffold structures. QSAR was built using a data set of 271 compounds, which were identified as positive and negative inhibitors from existing data reported in in vitro studies. The best QSAR model was developed using the 5-fold cross-validation Neural Network in Orange, and it was based on five PaDEL descriptors with an accuracy and sensitivity of 83%. As a result of screening of an in-house-built combinatorial library with the best-developed QSAR model, 675 compounds were identified as potential inhibitors of DNA gyrase. These inhibitors were further docked with DNA gyrase using AutoDock to compare the binding mode and score of the selected/screened compounds, and 615 compounds exhibited a docking score comparable to or lower than that of ciprofloxacin. Out of these, the top five analogues 902b, 9699f, 4419f, 5538f, and 898b reported in our study have binding scores of -13.81, -12.95, -12.52, -12.43, and -12.41 kcal/mol, respectively. The MD simulations of these five analogues for 100 ns supported the interaction stability of analogues with Escherichia coli DNA gyrase. Ninety-one per cent of the analogues screened by the QSAR model displayed better binding energy than ciprofloxacin, demonstrating the efficacy of the generated model. The NN-QSAR model proposed in this manuscript can be downloaded from https://github.com/ritu225/NN-QSAR_model.git.

Dataset Information

Identification of novel bacterial DNA gyrase inhibitors: An in silico study.

Publications

Identification of novel bacterial DNA gyrase inhibitors: An in silico study.

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