Cluster-based molecular docking study for in silico identification of novel 6-fluoroquinolones as potential inhibitors against Mycobacterium tuberculosis

<p>A classical protein sequence alignment and homology modeling strategy were used for building three Mycobacterium tuberculosis-DNA gyrase protein models using the available topoII-DNA-6FQ crystal structure complexes originating from different organisms. The recently determined M. tuberculosis-DNA gyrase apoprotein structures and topoII-DNA-6FQ complexes were used for defining the 6-fluoroquinolones (6-FQs) binding pockets. The quality of the generated models was initially validated by docking of the cocrystallized ligands into their binding site, and subsequently by quantitative evaluation of their discriminatory performances (identification of active/inactive 6-FQs) for a set of 145 6-FQs with known biological activity values. The M. tuberculosis-DNA gyrase model with the highest estimated discriminatory power was selected and used afterwards in an additional molecular docking experiment on a mixed combinatorial set of 427 drug-like 6-FQ analogs for which the biological activity values were predicted using a prebuilt counter-propagation artificial neural network model. A novel three-level Boolean-based [T/F (true/false)] clustering algorithm was used to assess the generated binding poses: Level 1 (geometry properties assessment), Level 2 (score-based clustering and selection of the (T)-signed highly scored Level 1 poses), and Level 3 (activity-based clustering and selection of the most “active” (T)-signed Level 2 hits). The frequency analysis of occurrence of the fragments attached at R1 and R7 position of the (T)-signed 6-FQs selected in Level 3 revealed several novel attractive fragments and confirmed some previous findings. We believe that this methodology could be successfully used in establishing novel possible structure-activity relationship recommendations in the 6-FQs optimization, which could be of great importance in the current antimycobacterial hit-to-lead processes.</p

Cluster-based molecular docking study for in silico identification of novel 6-fluoroquinolones as potential inhibitors against Mycobacterium tuberculosis (Cover Page)

<p>The rapid development of drug resistance in microbes, the toxicity, and side effects of existing anti-infectious drugs are factors stimulating the effort directed toward a new generation of antibiotics. On page 790, Nikola Minovski, Andrej Perdih, Marjana Novic, and Tom Solmajer demonstrate how carefully validated in silico models using the recently determined structures of M. tuberculosis– DNA gyrase apoprotein and topoisomerase II-DNA-6-fluoroquinolones complexes are proficiently used for defining the drugs' binding pockets and the subsequent design of a series of novel inhibitors of DNA gyrase from the class of substituted 6-fluoroquinolones (shown on the cover).</p

Inhibitor Design Strategy Based on an Enzyme Structural Flexibility: A Case of Bacterial MurD Ligase

Increasing bacterial resistance to available antibiotics stimulated the discovery of novel efficacious antibacterial agents. The biosynthesis of the bacterial peptidoglycan, where the MurD enzyme is involved in the intracellular phase of the UDP-MurNAc-pentapeptide formation, represents a collection of highly selective targets for novel antibacterial drug design. In our previous computational studies, the C-terminal domain motion of the MurD ligase was investigated using Targeted Molecular Dynamic (TMD) simulation and the Off-Path Simulation (OPS) technique. In this study, we present a drug design strategy using multiple protein structures for the identification of novel MurD ligase inhibitors. Our main focus was the ATP-binding site of the MurD enzyme. In the first stage, three MurD protein conformations were selected based on the obtained OPS/TMD data as the initial criterion. Subsequently, a two-stage virtual screening approach was utilized combining derived structure-based pharmacophores with molecular docking calculations. Selected compounds were then assayed in the established enzyme binding assays, and compound <b>3</b> from the aminothiazole class was discovered to act as a dual MurC/MurD inhibitor in the micomolar range. A steady-state kinetic study was performed on the MurD enzyme to provide further information about the mechanistic aspects of its inhibition. In the final stage, all used conformations of the MurD enzyme with compound <b>3</b> were simulated in classical molecular dynamics (MD) simulations providing atomistic insights of the experimental results. Overall, the study depicts several challenges that need to be addressed when trying to hit a flexible moving target such as the presently studied bacterial MurD enzyme and show the possibilities of how computational tools can be proficiently used at all stages of the drug discovery process

Inhibitor Design Strategy Based on an Enzyme Structural Flexibility: A Case of Bacterial MurD Ligase

Increasing bacterial resistance to available antibiotics stimulated the discovery of novel efficacious antibacterial agents. The biosynthesis of the bacterial peptidoglycan, where the MurD enzyme is involved in the intracellular phase of the UDP-MurNAc-pentapeptide formation, represents a collection of highly selective targets for novel antibacterial drug design. In our previous computational studies, the C-terminal domain motion of the MurD ligase was investigated using Targeted Molecular Dynamic (TMD) simulation and the Off-Path Simulation (OPS) technique. In this study, we present a drug design strategy using multiple protein structures for the identification of novel MurD ligase inhibitors. Our main focus was the ATP-binding site of the MurD enzyme. In the first stage, three MurD protein conformations were selected based on the obtained OPS/TMD data as the initial criterion. Subsequently, a two-stage virtual screening approach was utilized combining derived structure-based pharmacophores with molecular docking calculations. Selected compounds were then assayed in the established enzyme binding assays, and compound <b>3</b> from the aminothiazole class was discovered to act as a dual MurC/MurD inhibitor in the micomolar range. A steady-state kinetic study was performed on the MurD enzyme to provide further information about the mechanistic aspects of its inhibition. In the final stage, all used conformations of the MurD enzyme with compound <b>3</b> were simulated in classical molecular dynamics (MD) simulations providing atomistic insights of the experimental results. Overall, the study depicts several challenges that need to be addressed when trying to hit a flexible moving target such as the presently studied bacterial MurD enzyme and show the possibilities of how computational tools can be proficiently used at all stages of the drug discovery process

Inhibitor Design Strategy Based on an Enzyme Structural Flexibility: A Case of Bacterial MurD Ligase

Increasing bacterial resistance to available antibiotics stimulated the discovery of novel efficacious antibacterial agents. The biosynthesis of the bacterial peptidoglycan, where the MurD enzyme is involved in the intracellular phase of the UDP-MurNAc-pentapeptide formation, represents a collection of highly selective targets for novel antibacterial drug design. In our previous computational studies, the C-terminal domain motion of the MurD ligase was investigated using Targeted Molecular Dynamic (TMD) simulation and the Off-Path Simulation (OPS) technique. In this study, we present a drug design strategy using multiple protein structures for the identification of novel MurD ligase inhibitors. Our main focus was the ATP-binding site of the MurD enzyme. In the first stage, three MurD protein conformations were selected based on the obtained OPS/TMD data as the initial criterion. Subsequently, a two-stage virtual screening approach was utilized combining derived structure-based pharmacophores with molecular docking calculations. Selected compounds were then assayed in the established enzyme binding assays, and compound <b>3</b> from the aminothiazole class was discovered to act as a dual MurC/MurD inhibitor in the micomolar range. A steady-state kinetic study was performed on the MurD enzyme to provide further information about the mechanistic aspects of its inhibition. In the final stage, all used conformations of the MurD enzyme with compound <b>3</b> were simulated in classical molecular dynamics (MD) simulations providing atomistic insights of the experimental results. Overall, the study depicts several challenges that need to be addressed when trying to hit a flexible moving target such as the presently studied bacterial MurD enzyme and show the possibilities of how computational tools can be proficiently used at all stages of the drug discovery process

Schematic representation of the computational and experimental investigations of the BTL transmembrane region.

<p>Schematic representation of the computational and experimental investigations of the BTL transmembrane region.</p

2D ¹H-¹⁵N HSQC spectrum.

<p>It is acquired on Varian VNMRS 800 NMR spectrometer at 298 K on natural abundance of ¹⁵N isotope. The sequence-specific assignments of main conformation of GSVQCAGLISLPIAIEFTKKKK peptide are presented. The resonance signals coming from side chain NH₂ group for Gln4 are also shown.</p

Radial distribution function (RDF) plots.

<p>RDF of hydrophobic (black), hydrophilic (red) parts of SDS micelle and water molecules (green) and the heavy atoms in side chains for all residues with the exception of Gly220 and Gly226.</p

3D Ramachandran histograms for the backbone torsion angles φ and ψ (A) andtwo dimensional plots of the secondary structure analysis (B).

<p>In <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0038967#pone-0038967-g005" target="_blank">Fig 5A</a> the analysis was performed for the residues that were predicted to from the transmembrane helix: 221–238 for the TM 3 helix and 220–238 for the TM 3A helix. Each exported conformation of the peptide in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0038967#pone-0038967-g005" target="_blank">Fig 5B</a>, generated by the 20 ns MD simulation was analyzed for is the secondary structure. Purple colour depicts the alpha helix structure, green indicates the turn structure and blue depicts the 3–10 helical structure. Selected residue numbers on the y-axis corresponds to the residues numbers of the BTL sequence.</p

The initial configuration (A) and representative snapshots (B) of the alpha-helices TM 3 and TM 3A.

<p> In Fig. 3A the initial configuration of the alpha-helices TM 3 and TM 3A are inserted into the DPPC membrane. The helices are surrounded above and below by a layer of water molecules. In <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0038967#pone-0038967-g003" target="_blank">Fig.3B</a> representative snapshots of the alpha helices TM 3 and TM 3A are from the MD simulation. The approximate borders of the alpha helical structures residue are also depicted. The BTL Pro231 residue, where the alpha helix kink is located is highlighted with a line model.</p