Furanone derivatives as new inhibitors of CDC7 kinase: development of structure activity relationship model using 3D QSAR,molecular docking,and in silico ADMET

Cell division cycle 7 (CDC7) is a serine/threonine kinase, which plays a vital role in the replication initiation of DNA synthesis. Overexpression of the CDC7 in various tumor growths and in cell proliferation makes it a promising target for treatment of cancers. To investigate the binding between the CDC7 and furanone inhibitors, and in order to design highly potent inhibitors, a three-dimensional quantitative structure activity relationship (3D-QSAR) with molecular docking was performed. The optimum CoMSIA model showed significant statistical quality on all validation methods with a determination coefficient (R²?=?0.945), bootstrapping R² mean (BS-R²?=?0.960), and leave-one-out cross-validation (Q²) coefficient of 0.545. The predictability of this model was evaluated by external validation using a test set of nine compounds with a predicted determination coefficient R²_test of 0.96, besides the mean absolute error (MAE) of the test set was 0.258 log units. The extracted contour maps were used to identify the important regions, where the modification was necessary to design a new molecule with improved activity. Furthermore, a good consistency between the molecular docking and contour maps strongly demonstrates that the molecular modeling is reliable. Based on those obtained results, we designed several new potent CDC7 inhibitors, and their inhibitory activities were validated by the molecular models. Additionally, those newly designed inhibitors showed promising results in the preliminary in silico ADMET evaluations.     

Pharmacophore generation,atom-based 3D-QSAR and molecular dynamics simulation analyses of pyridine-3-carboxamide-6-yl-urea analogues as potential gyrase B inhibitors

DNA gyrase subunit B (GyrB) is an attractive drug target for the development of antibacterial agents with therapeutic potential. In the present study, computational studies based on pharmacophore modelling, atom-based QSAR, molecular docking, free binding energy calculation and dynamics simulation were performed on a series of pyridine-3-carboxamide-6-yl-urea derivatives. A pharmacophore model using 49 molecules revealed structural and chemical features necessary for these molecules to inhibit GyrB. The best fitted model AADDR.13 was generated with a coefficient of determination (r²) of 0.918. This model was validated using test set molecules and had a good r² of 0.78. 3D contour maps generated by the 3D atom-based QSAR revealed the key structural features responsible for the GyrB inhibitory activity. Extra precision molecular docking showed hydrogen bond interactions with key amino acid residues of ATP-binding pocket, important for inhibitor binding. Further, binding free energy was calculated by the MM-GBSA rescoring approach to validate the binding affinity. A 10 ns MD simulation of inhibitor #47 showed the stability of the predicted binding conformations. We identified 10 virtual hits by in silico high-throughput screening. A few new molecules were also designed as potent GyrB inhibitors. The information obtained from these methodologies may be helpful to design novel inhibitors of GyrB.     

Aldehyde and phosphinate analogs of glutathione and glutathionylspermidine: potent,selective binding inhibitors of the E. coli bifunctional glutathionylspermidine synthetase/amidase

Introduction: The tripeptide glutathione is converted to glutathionylspermidine (Gsp) in Escherichia coli and in trypanosomatid parasites by an ATP-cleaving Gsp synthetase activity. In parasites, an additional glutathionylation forms bis-(glutathionyl)-spermidine, trypanothione, believed to be the major surveillance thiol involved in oxidant defense mechanisms in trypanosomatid parasites. In E. coli, the Gsp synthetase is part of a bifunctional enzyme opposed by the hydrolytic Gsp amidase.Results: Gsp amidase and Gsp synthetase activities of the bifunctional E. coli enzyme can be separately targeted by potent, selective slow-binding inhibitors that induce time-dependent inhibition. The inhibitor γ-Glu-Ala-Gly-CHO most probably captures Cys59 and accumulates as the tetrahedral adduct in the amidase active site. Inhibitory Gsp phosphinate analogs are phosphorylated by ATP to yield phosphinophosphate analogs in the synthetase active site. Binding of phosphinophosphate in the Gsp synthetase active site potentiates the inhibition affinity for the aldehyde at the Gsp amidase active site by two orders of magnitude.Conclusions: Time-dependent inhibition of the Gsp amidase activity by the aldehyde substrate analog supports previous work that suggests glutathionyl acyl-enzyme intermediate formation in the Gsp amidase reaction mechanism. Use of potent selective inhibitors against Gsp amidase (aldehyde) and Gsp synthetase (phosphinate) activities provides further evidence of interdomain communication in the bifunctional enzyme from E. coli.     

3D-QSAR,docking, molecular dynamics simulation and free energy calculation studies of some pyrimidine derivatives as novel JAK3 inhibitors

Janus kinase 3 (JAK3) is a promising drug target for the treatment of inflammatory diseases, autoimmune disorders, organ transplant rejection and various cancers. In the present study, 3D-QSAR, docking, MD simulation and MM/PBSA studies were performed on a series of pyrimidine-based JAK3 inhibitors. A reliable COMSIA (q² = 0.717 and r² = 0.986) model was developed and validated using external validation test set, bootstrapping, progressive scrambling and r_m² metrics analyses. Structural requirements identified through contour maps of the model were strategically utilized to computationally design 170 novel JAK3 inhibitors with improved potency. Docking studies were performed on the selected data set and newly designed compounds to show their binding mode and to identify important interacting residues inside the active site of JAK3. In addition, docking results of the selected designed compounds inside the active sites of JAK1, JAK2 and TYK2 indicated their JAK3 selectivity. MD simulation (100 ns) on the docked complex of compound 28 (one of highly active compounds of the data set) assisted in the further exploration of the binding interactions. Some crucial residues like Lys830 (glycine-rich loop), Val836, Ala853, Leu905 (hinge region), Cys909, Asn954, Leu956 and Ala966 were identified. Hydrogen bond interactions with hinge residue Leu905 were critical for the binding of JAK3 inhibitors. Additionally, MM/PBSA calculation provided the binding free energy of the compound 28. Newly designed molecules showed promising results in the preliminary in silico ADMET evaluations. Outcomes of the study can further be exploited to develop potent JAK3 inhibitors.     

Extra precision docking,free energy calculation and molecular dynamics studies on glutamic acid derivatives as MurD inhibitors

The binding modes of well known MurD inhibitors have been studied using molecular docking and molecular dynamics (MD) simulations. The docking results of inhibitors 1-30 revealed similar mode of interaction with Escherichia coli-MurD. Further, residues Thr36, Arg37, His183, Lys319, Lys348, Thr321, Ser415 and Phe422 are found to be important for inhibitors and E. coli-MurD interactions. Our docking procedure precisely predicted crystallographic bound inhibitor 7 as evident from root mean square deviation (0.96 Å). In addition inhibitors 2 and 3 have been successfully cross-docked within the MurD active site, which was pre-organized for the inhibitor 7. Induced fit best docked poses of 2, 3, 7 and 15/2Y1O complexes were subjected to 10 ns MD simulations to determine the stability of the predicted binding conformations. Induce fit derived docked complexes were found to be in a state of near equilibrium as evident by the low root mean square deviations between the starting complex structure and the energy minimized final average MD complex structures. The results of molecular docking and MD simulations described in this study will be useful for the development of new MurD inhibitors with high potency.     

Homologs of the vancomycin resistance d-Ala-d-Ala dipeptidase VanX in Streptomyces toyocaensis,Escherichia coli and Synechocystis: attributes of catalytic efficiency,stereoselectivity and regulation with implications for function

Background: Vancomycin-resistant enterococci are pathogenic bacteria that have altered cell-wall peptidoglycan termini (d-alanyl-d-lactate [d-Ala-d-lactate] instead of d-alanyl-d-alanine [d-Ala-d-Ala]), which results in a 1000-fold decreased affinity for binding vancomycin. The metallodipeptidase VanX (EntVanX) is a key enzyme in antibiotic resistance as it reduces the cellular pool of the d-Ala-d-Ala dipeptide.Results: A bacterial genome search revealed vanX homologs in Streptomyces toyocaensis (StoVanX), Escherichia coli (EcoVanX), and Synechocystis sp. strain PCC6803 (SynVanX). Here, the d,d-dipeptidase catalytic activity of all three VanX homologs is validated, and the catalytic efficiencies and diastereoselectivity ratios for dipeptide cleavage are reported. The ecovanX gene is shown to have an RpoS (σ^s)-dependent promoter typical of genes turned on in stationary phase. Expression of ecovanX and an associated cluster of dipeptide permease genes permitted growth of E. coli using d-Ala-d-Ala as the sole carbon source.Conclusions: The key residues of the EntVanX active site are strongly conserved in the VanX homologs, suggesting their active-site topologies are similar. StoVanX is a highly efficient d-Ala-d-Ala dipeptidase; its gene is located in a vanHAX operon, consistent with a vancomycin-immunity function. StoVanX is a potential source for the VanX found in gram-positive enterococci. The catalytic efficiencies of d-Ala-d-Ala hydrolysis for EcoVanX and SynVanX are 25-fold lower than for EntVanX, suggesting they have a role in cell-wall turnover. Clustered with the ecovanX gene is a putative dipeptide permease system that imports d-Ala-d-Ala into the cell. The combined action of EcoVanX and the permease could permit the use of d-Ala-d-Ala as a bacterial energy source under starvation conditions.     

Identification of novel Plasmodium falciparum PI4KB inhibitors as potential anti-malarial drugs: Homology modeling,molecular docking and molecular dynamics simulations

The current study was set to discover selective Plasmodium falciparum phosphatidylinositol-4-OH kinase type III beta (pfPI4KB) inhibitors as potential antimalarial agents using combined structure-based and ligand-based drug discovery approach. A comparative model of pfPI4KB was first constructed and validated using molecular docking techniques. Performance of Autodock4.2 and Vina4 software in predicting the inhibitor-PI4KB binding mode and energy was assessed based on two Test Sets: Test Set I contained five ligands with resolved crystal structures with PI4KB, while Test Set II considered eleven compounds with known IC50 value towards PI4KB. The outperformance of Autodock as compared to Vina was reported, giving a correlation coefficient (R²) value of 0.87 and 0.90 for Test Set I and Test Set II, respectively. Pharmacophore-based screening was then conducted to identify drug-like molecules from ZINC database with physicochemical similarity to two potent pfPI4KB inhibitors –namely cpa and cpb. For each query inhibitor, the best 1000 hits in terms of TanimotoCombo scores were selected and subjected to molecular docking and molecular dynamics (MD) calculations. Binding energy was then estimated using molecular mechanics–generalized Born surface area (MM-GBSA) approach over 50 ns MD simulations of the inhibitor-pfPI4KB complexes. According to the calculated MM-GBSA binding energies, ZINC78988474 and ZINC20564116 were identified as potent pfPI4KB inhibitors with binding energies better than those of cpa and cpb, with ΔG_binding ≥ −34.56 kcal/mol. The inhibitor-pfPI4KB interaction and stability were examined over 50 ns MD simulation; as well the selectivity of the identified inhibitors towards pfPI4KB over PI4KB was reported.     

Deciphering the Interactions of Bioactive Compounds in Selected Traditional Medicinal Plants against Alzheimer’s Diseases via Pharmacophore Modeling,Auto-QSAR,and Molecular Docking Approaches

Neurodegenerative diseases, for example Alzheimer’s, are perceived as driven by hereditary, cellular, and multifaceted biochemical actions. Numerous plant products, for example flavonoids, are documented in studies for having the ability to pass the blood-brain barrier and moderate the development of such illnesses. Computer-aided drug design (CADD) has achieved importance in the drug discovery world; innovative developments in the aspects of structure identification and characterization, bio-computational science, and molecular biology have added to the preparation of new medications towards these ailments. In this study we evaluated nine flavonoid compounds identified from three medicinal plants, namely T. diversifolia, B. sapida, and I. gabonensis for their inhibitory role on acetylcholinesterase (AChE), butyrylcholinesterase (BChE) and monoamine oxidase (MAO) activity, using pharmacophore modeling, auto-QSAR prediction, and molecular studies, in comparison with standard drugs. The results indicated that the pharmacophore models produced from structures of AChE, BChE and MAO could identify the active compounds, with a recuperation rate of the actives found near 100% in the complete ranked decoy database. Moreso, the robustness of the virtual screening method was accessed by well-established methods including enrichment factor (EF), receiver operating characteristic curve (ROC), Boltzmann-enhanced discrimination of receiver operating characteristic (BEDROC), and area under accumulation curve (AUAC). Most notably, the compounds’ pIC₅₀ values were predicted by a machine learning-based model generated by the AutoQSAR algorithm. The generated model was validated to affirm its predictive model. The best models achieved for AChE, BChE and MAO were models kpls_radial_17 (R² = 0.86 and Q² = 0.73), pls_38 (R² = 0.77 and Q² = 0.72), kpls_desc_44 (R² = 0.81 and Q² = 0.81) and these externally validated models were utilized to predict the bioactivities of the lead compounds. The binding affinity results of the ligands against the three selected targets revealed that luteolin displayed the highest affinity score of −9.60 kcal/mol, closely followed by apigenin and ellagic acid with docking scores of −9.60 and −9.53 kcal/mol, respectively. The least binding affinity was attained by gallic acid (−6.30 kcal/mol). The docking scores of our standards were −10.40 and −7.93 kcal/mol for donepezil and galanthamine, respectively. The toxicity prediction revealed that none of the flavonoids presented toxicity and they all had good absorption parameters for the analyzed targets. Hence, these compounds can be considered as likely leads for drug improvement against the same.     

Molecular description of pyrimidine-based inhibitors with activity against FAK combining 3D-QSAR analysis,molecular docking and molecular dynamics

Focal adhesion kinase (FAK) is a promising target for developing more effective anticancer drugs. To better understand the structure-activity relationships and mechanism of actions of FAK inhibitors, a molecular modeling study using 3D-QSAR, molecular docking, molecular dynamics simulations, and binding free energy analysis were conducted. Two types of satisfactory 3D-QSAR models were generated, comprising the CoMFA model (R²_cv = 0.528, R²_pred = 0.7557) and CoMSIA model (R²_cv = 0.757, R²_pred = 0.8362), for predicting the inhibitory activities of novel inhibitors. The derived contour maps indicate structural characteristics for substituents on the template. Molecular docking, molecular dynamic simulations and binding free energy calculations further reveal that the binding of inhibitors to FAK is mainly contributed from hydrophobic, electrostatic and hydrogen bonding interactions. In addition, some key residues (Arg14, Glu88, Cys90, Arg138, Asn139, Leu141, and Leu155) responsible for ligand-receptor binding are highlighted. All structural information obtained from 3D-QSAR models and molecular dynamics is consist with the available experimental activities. All the results will facilitate the optimization of this series of FAK inhibitors with higher inhibitory activities.     

Combined 2D and 3D-QSAR,molecular modelling and docking studies of pyrazolodiazepinones as novel phosphodiesterase 2 inhibitors

Selective inhibition of phosphodiesterase 2 (PDE2) in cells where it is located elevates cyclic guanosine monophosphate (cGMP) and acts as novel analgesic with antinociceptive activity. Three-dimensional quantitative structure–activity relationship (QSAR) studies for pyrazolodiazepinone inhibitors exhibiting PDE2 inhibition were performed using comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA) and Topomer CoMFA, and two-dimensional QSAR study was performed using a Hologram QSAR (HQSAR) method. QSAR models were generated using training set of 23 compounds and were validated using test set of nine compounds. The optimum partial least squares (PLS) for CoMFA-Focusing, CoMSIA-SDH, Topomer CoMFA and HQSAR models exhibited good ‘leave-one-out’ cross validated correlation coefficient (q²) of 0.790, 0.769, 0.840 and 0.787, coefficient of determination (r²) of 0.999, 0.964, 0.979 and 0.980, and high predictive power (r²_pred) of 0.796, 0.833, 0.820 and 0.803 respectively. Docking studies revealed that those inhibitors able to bind to amino acid Gln859 by cGMP binding orientation called ‘glutamine-switch’, and also bind to the hydrophobic clamp of PDE2 isoform, could possess high selectivity for PDE2. From the results of all the studies, structure–activity relationships and structural requirements for binding to active site of PDE2 were established which provide useful guidance for the design and future synthesis of potent PDE2 inhibitors.     

Investigation of indirubin derivatives: a combination of 3D-QSAR,molecular docking,and ADMET towards the design of new DRAK2 inhibitors

Kinase-related apoptosis-inducing kinase 2 (DRAK2) is a serine/threonine kinase and belongs to the death-associated protein kinase DPAK family, which is responsible for induction of apoptosis in many cell types. Thus, DRAK2 is regarded as a promising target for treatment of autoimmune diseases. To investigate the binding between DRAK2 and indirubin inhibitors and design potent inhibitors, a three-dimensional quantitative structure-activity relationship (3D-QSAR) and molecular docking were performed. Comparative Molecular Similarity Indices Analysis (CoMSIA) was developed using 33 molecules having pIC₅₀ ranging from 8.523 to 5.000 (IC₅₀ in nM). The best CoMSIA model gave a significant coefficient of determination (R²?=?0.93), as well as a (leave-one-out cross-validation coefficient Q² of 0.81. The predictive ability of this model was evaluated by external validation using a test set of eight compounds and yielded a predicted coefficient of determination R²_test of 0.94. The contour maps could provide structural features to improve inhibitory activity. Good consistency between contour maps and molecular docking strongly suggests that the molecular modeling is reliable. Based on these satisfactory results, we designed several new DRAK2 inhibitors and their inhibitory activities were predicted using different models, which are developed on different training and test sets. Additionally, these newly designed inhibitors showed promising results in the preliminary in silico ADMET evaluations compared to the best inhibitor from the studied dataset. This study could be useful in lead identification and optimization for early drug discovery of DRAK2 inhibitors.     

Identification of novel nt-MGAM inhibitors for potential treatment of type 2 diabetes: Virtual screening,atom based 3D-QSAR model,docking analysis and ADME study

In this study, a virtual screening procedure was applied to identify new potential nt-MGAM inhibitors as a possible medication for type 2 diabetes. To this aim, a series of salacinol analogues were first investigated by docking analysis for their binding to the X-ray structure of the biological target nt-MGAM. Key interactions for ligand binding into the receptor active site were identified which shared common features to those found for other known inhibitors, which strengthen the results of this study. 3D QSAR model was then built and showed to be statistically significant and with a good predictive power for the training (R² = 0.99, SD = 0.17, F = 555.3 and N = 27) and test set (Q² = 0.81, Pearson(r) = 0.92, RMSE = 0.52, N = 08). The model was then used to virtually screen the ZINC database with the aim of identifying novel chemical scaffolds as potential nt-MGAM inhibitors. Further, in silico predicted ADME properties were investigated for the most promising molecules. The outcome of this investigation sheds light on the molecular characteristics of the binding of salacinol analogues to nt-MGAM enzyme and identifies new possible inhibitors which have the potential to be developed into drugs, thus significantly contributing to the design and optimization of therapeutic strategies against type 2 diabetes.     

Organotellurium(IV) complexes of N-methylisatin-o-aminothiophenol Schiff base: Preparation,characterization, DFT,molecular docking studies,antimicrobial and antioxidant activity

The reactions of organotellurium(IV) chlorides (RTeCl₃ and R₂TeCl₂) with Schiff base(NMeIATP) derived by condensation of N-methylisatin with 2-aminothiophenol results in the formation of new organotellurium(IV) complexes (4a-4f) of type RTeCl₂.NMeIATP and R₂TeCl.NMeIATP (where R = 4-Methoxyaryl, 4-Hydroxyaryl and 3-Methy-4-hydroxyaryl; aryl = phenyl). These complexes were characterized by different experimental and spectroscopic techniques like elemental analyses, molar conductance, SEM analysis, FT-IR, DFT calculations, powder X-ray diffraction, mass spectrometry, ¹H NMR, ¹³C NMR, UV–Vis and Thermogravimetric analysis. These spectroscopic studies revealed that ligand acted as monobasic tridentate ligand coordinated with tellurium metal through Carbonyl oxygen, azomethine nitrogen and sulphur atom from the 2-aminothiophenol ring. The molecular geometries of NMeIATP and its organotellurium(IV) complexes(4a-4f) were optimized and quantum mechanical parameters were calculated by using DFT/B3LYP basis sets in Guassian09 program. Based on the spectral results, suitable geometries of the complexes are purposed. Molecular docking studies were carried out to determine the binding energy between NMeIATP and complexes with receptor proteins: S. aureus (3ty7), B. subtilis (5h67) and E. coli (3t88). Antioxidant activity of NMeIATP and organotellurium(IV) complexes were evaluated by DPPH assay. The radical scavenging activity(IC₅₀ value) of complex 4a (IC₅₀ = 59.08 μg/ml) was found to be greater than other compounds. NMeIATP and organotellurium(IV) complexes were tested against different bacteria and fungi. MIC values show that complexes possess better antimicrobial activity than Schiff base (NMeIATP).     

Design of (quinolin-4-ylthio)carboxylic acids as new Escherichia coli DNA gyrase B inhibitors: machine learning studies,molecular docking,synthesis and biological testing

Spread of multidrug‐resistant Escherichia coli clinical isolates is a main problem in the treatment of infectious diseases. Therefore, the modern scientific approaches in decision this problem require not only a prevention strategy, but also the development of new effective inhibitory compounds with selective molecular mechanism of action and low toxicity. The goal of this work is to identify more potent molecules active against E. coli strains by using machine learning, docking studies, synthesis and biological evaluation. A set of predictive QSAR models was built with two publicly available structurally diverse data sets, including recent data deposited in PubChem. The predictive ability of these models tested by a 5-fold cross-validation, resulted in balanced accuracies (BA) of 59–98% for the binary classifiers. Test sets validation showed that the models could be instrumental in predicting the antimicrobial activity with an accuracy (with BA = 60–99 %) within the applicability domain. The models were applied to screen a virtual chemical library, which was designed to have activity against resistant E. coli strains. The eight most promising compounds were identified, synthesized and tested. All of them showed the different levels of anti-E. coli activity and acute toxicity. The docking results have shown that all studied compounds are potential DNA gyrase inhibitors through the estimated interactions with amino acid residues and magnesium ion in the enzyme active center The synthesized compounds could be used as an interesting starting point for further development of drugs with low toxicity and selective molecular action mechanism against resistant E. coli strains. The developed QSAR models are freely available online at OCHEM http://ochem.eu/article/112525 and can be used to virtual screening of potential compounds with anti-E. coli activity.     

Combined Theoretical and Experimental Study of the Complexation of a Hexaarylbenzene-Based Receptor with the Potassium Cation

In this study, non-covalent binding interactions of the hexaarylbenzene-based receptor (R) with the potassium cation have been investigated. Employing quantum mechanical density functional theory calculations, the most probable structure of the KR ⁺ complex species was predicted. In this complex, the K⁺ cation synergistically interacts with the polar ethereal oxygen fence and with the central hydrophobic benzene bottom via cation?C?? interaction. The strength of the KR ⁺ complex was evaluated experimentally by affinity capillary electrophoresis. From the dependence of the effective electrophoretic mobility of the receptor R on the concentration of the potassium ion in the background electrolyte, the thermodynamic binding (stability, association) constant (K _KR) of the KR ⁺ complex in methanol was evaluated as log₁₀?K _KR?=?3.20?±?0.22.     

Pharmacophore interactions analysis and prediction of inhibitory activity of 1,7-diazacarbazoles as checkpoint kinase 1 inhibitors: application of molecular docking, 3D-QSAR and RBF neural network

In the present study, we mainly focused on new synthesized 1,7-diazacarbazole derivatives (44 active molecules) as Chk1 inhibitors to build 3D-QSAR model. Comparative molecular field analysis (CoMFA) model with three principal components was developed. The relative contributions in building of CoMFA model were 64.41 % for steric field and 35.59 % for electrostatic field. R ² values for training and test sets of CoMFA model were 0.8724 and 0.7818, respectively, and squared correlation coefficient for leave-one-out cross-validation test (q ²) was 0.6753. To improve the predictive power, a new 3D-QSAR model was developed by using radial basis function network (RBFN) and score of CoMFA interactions energy values as input variables. Scores 1, 2 and 3 were used as input variables, and a RBFN model with seven centers and spread value equal to 95 was developed to create a nonlinear 3D-QSAR model. R ² values for training and test sets were 0.9613 and 0.8564, and q ² for leave-one-out cross-validation test was 0.9258. Docking of all molecules to 3DX ligand binding site of Chk1 receptor indicated six interactions as pharmacological interactions between compounds and binding site of receptors. These pharmacological interactions were hydrogen bonding with LEU-15 and GLU-85 in main chain and four van der Waals interactions with LEU-15, VAL-23, TYR-86 and LEU-137 in side chain. CoMFA contour plots were used to design new inhibitors, and inhibitory activity of each compound was predicted by using CoMFA and RBFN models.     

Pharmacophore modeling, 3D-QSAR,docking, and molecular dynamics simulation on topoisomerase IV inhibitors of wild type Staphylococcus aureus

Staphylococcus aureus is a gram-positive bacterium. It is a foremost cause of skin and respiratory infections, endocarditis, osteomyelitis, Ritter’s disease, and bacteraemia. Topoisomerase enzyme is involved in preventing or correcting topological problems of overwinding or underwinding occurring in DNA before replication process. An exhaustive molecular modeling studies that includes pharmacophore modeling, ligand-based three-dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking, molecular dynamics simulation, and ADME calculations were performed on isothiazoloquinolones derivatives which are reported as effective inhibitors against topoisomerase IV of wild type S. aureus. In pharmacophore modeling by using pharmacophore alignment and scoring engine (PHASE) a five-point model (AHHRR.3) was generated with existing compounds having statistical significant as correlation coefficient (R ² = 0.954), cross-validation coefficient (Q ² = 0.650), and F value of 130.5. Ligand-based 3D-QSAR study was applied using comparative molecular field analysis (CoMFA) with Q ² = 0.616, R ² = 0.989, and comparative molecular similarity indices analysis (CoMSIA) with Q ² = 0.510, R ² = 0.995. The predictive ability of this model was determined using a test set of molecules that gave acceptable predictive correlation (R ² Pred) values 0.55 and 0.56 for CoMFA and CoMSIA, respectively. Docking and molecular dynamic simulations were employed to position the inhibitors into protein active site to find out the most probable binding mode and most reliable conformations. Developed pharmacophore models and docking methods provide guidance to design enhanced activity molecules.