Discovery of promising FtsZ inhibitors by E-pharmacophore, 3D-QSAR,molecular docking study,and molecular dynamics simulation

Filamentous temperature-sensitive protein Z (FtsZ), playing a key role in bacterial cell division, is regarded as a promising target for the design of antimicrobial agent. This study is looking for potential high-efficiency FtsZ inhibitors. Ligand-based pharmacophore and E-pharmacophore, virtual screening and molecular docking were used to detect promising FtsZ inhibitors, and molecular dynamics simulation was used to study the stability of protein-ligand complexes in this paper. Sixty-three inhibitors from published literatures with pIC₅₀ ranging from 2.483 to 5.678 were collected to develop ligand-based pharmacophore model. 4DXD bound with 9PC was selected to develop the E-pharmacophore model. The pharmacophore models validated by test set method and decoy set were employed for virtual screening to exclude inactive compounds against ZINC database. After molecular docking, ADME analysis, IFD docking and MM-GBSA, 8 hits were identified as potent FtsZ inhibitors. A 50?ns molecular dynamics simulation was implemented on the compounds to assess the stability between potent inhibitors and FtsZ. The results indicated that the candidate compounds had a high docking score and were strongly combined with FtsZ by forming hydrogen bonding interactions with key amino acid residues, and van der Waals forces and hydrophobic interactions had significant contribution to the stability of the binding. Molecular dynamics simulation results showed that the protein-ligand compounds performed well in both the stability and flexibility of the simulation process.     

N-(thiazol-2-yl)-2-thiophene carboxamide derivatives as Abl inhibitors identified by a pharmacophore-based database screening of commercially available compounds

Suggestions derived from a previous ligand-based ligand design approach and docking calculations aimed at finding compound with affinity toward Abl and molecular scaffolds previously untested as Abl inhibitors, led to the identification of commercially available N-(thiazol-2-yl)-2-thiophene carboxamide derivatives with affinity in a cell-free assay up to low nanomolar concentrations, significantly enhanced with respect to that of their parent compounds previously reported. In particular, among compounds of the Asinex database, molecular docking simulations guided the choice of high-affinity ligands, predicting their binding mode and their interaction pattern with the Abl catalytic binding site. Moreover, affinity of the new compounds was also rationalized in terms of their interactions with the enzyme.     

Molecular docking studies on DMDP derivatives as human DHFR inhibitors

Molecular docking is routinely used for understanding drug‐receptor interaction in modern drug design. Here, we describe the docking of 2, 4-diamino-5-methyl-5-deazapteridine (DMDP) derivatives as inhibitors to human dihydrofolate reductase (DHFR). We docked 78 DMDP derivates collected from literature to DHFR and studied their specific interactions with DHFR. A new shape-based method, LigandFit, was used for docking DMDP derivatives into DHFR active sites. The result indicates that the molecular docking approach is reliable and produces a good correlation coefficient (r² = 0.499) for the 73 compounds between docking score and IC₅₀ values (Inhibitory Activity). The chloro substituted naphthyl ring of compound 63 makes significant hydrophobic contact with Leu 22, Phe 31 and Pro 61 of the DHFR active site leading to enhanced inhibition of the enzyme. The docked complexes provide better insights to design more potent DHFR inhibitors prior to their synthesis.     

Automatic identification and representation of protein binding sites for molecular docking.

Molecular docking is a popular way to screen for novel drug compounds. The method involves aligning small molecules to a protein structure and estimating their binding affinity. To do this rapidly for tens of thousands of molecules requires an effective representation of the binding region of the target protein. This paper presents an algorithm for representing a protein's binding site in a way that is specifically suited to molecular docking applications. Initially the protein's surface is coated with a collection of molecular fragments that could potentially interact with the protein. Each fragment, or probe, serves as a potential alignment point for atoms in a ligand, and is scored to represent that probe's affinity for the protein. Probes are then clustered by accumulating their affinities, where high affinity clusters are identified as being the "stickiest" portions of the protein surface. The stickiest cluster is used as a computational binding "pocket" for docking. This method of site identification was tested on a number of ligand-protein complexes; in each case the pocket constructed by the algorithm coincided with the known ligand binding site. Successful docking experiments demonstrated the effectiveness of the probe representation.     

Structural insights of Staphylococcus aureus FtsZ inhibitors through molecular docking, 3D-QSAR and molecular dynamics simulations

Filamentous temperature-sensitive protein Z (FtsZ) is a protein encoded by the FtsZ gene that assembles into a Z-ring at the future site of the septum of bacterial cell division. Structurally, FtsZ is a homolog of eukaryotic tubulin but has low sequence similarity; this makes it possible to obtain FtsZ inhibitors without affecting the eukaryotic cell division. Computational studies were performed on a series of substituted 3-arylalkoxybenzamide derivatives reported as inhibitors of FtsZ activity in Staphylococcus aureus. Quantitative structure-activity relationship models (QSAR) models generated showed good statistical reliability, which is evident from r²_ncv and r²_loo values. The predictive ability of these models was determined and an acceptable predictive correlation (r²_Pred) values were obtained. Finally, we performed molecular dynamics simulations in order to examine the stability of protein-ligand interactions. This facilitated us to compare free binding energies of cocrystal ligand and newly designed molecule B1. The good concordance between the docking results and comparative molecular field analysis (CoMFA)/comparative molecular similarity indices analysis (CoMSIA) contour maps afforded obliging clues for the rational modification of molecules to design more potent FtsZ inhibitors.     

Identification of type I and type II inhibitors of c-Yes kinase using in silico and experimental techniques

c-Yes kinase is considered as one of the attractive targets for anti-cancer drug design. The DFG (Asp-Phe-Gly) motif present in most of the kinases will adopt active and inactive conformations, known as DFG-in and DFG-out and their inhibitors are classified into type I and type II, respectively. In the present study, two screening protocols were followed for identification of c-Yes kinase inhibitors. (i) Structure-based virtual screening (SBVS) and (ii) Structure-based (SB) and Pharmacophore-based (PB) tandem screening. In SBVS, the c-Yes kinase structure was obtained from homology modeling and seven ensembles with different active site scaffolds through molecular dynamics (MD) simulations. For SB-PB tandem screening, we modeled ligand bound active and inactive conformations. Physicochemical properties of inhibitors of Src kinase family and c-Yes kinase were used to prepare target focused libraries for screenings. Our screening procedure along with docking showed 520 probable hits in SBVS and tandem screening (120 and 400, respectively). Out of 5000 compounds identified from different computational methods, 2410 were examined using kinase inhibition assays. It includes 266 compounds (5.32%) identified from our method. We observed that 14 compounds (12%) are identified by the present method out of 168 that showed > 30% inhibition. Among them, three compounds are novel, unique, and showed good inhibition. Further, we have studied the binding of these compounds at the DFG-in and DFG-out conformations and reported the probable class (type I or type II). Hence, we suggest that these compounds could be novel drug leads for regulation of colorectal cancer.     

Probing voltage sensing domain of KCNQ2 channel as a potential target to combat epilepsy: a comparative study

Multidrug resistance along with side-effects of available anti-epileptic drugs and unavailability of potent and effective agents in submicromolar quantities presents the biggest therapeutic challenges in anti-epileptic drug discovery. The molecular modeling techniques allow us to identify agents with novel structures to match the continuous urge for its discovery. KCNQ2 channel represents one of the validated targets for its therapy. The present study involves identification of newer anti-epileptic agents by means of a computer-aided drug design adaptive protocol involving both structure-based virtual screening of Asinex library using homology model of KCNQ2 and 3D-QSAR based virtual screening with docking analysis, followed by dG bind and ligand efficiency calculations with ADMET studies, of which 20 hits qualified all the criterions. The best ligands of both screenings with least potential for toxicity predicted computationally were then taken for molecular dynamic simulations. All the crucial amino acid interactions were observed in hits of both screenings such as Glu130, Arg207, Arg210 and Phe137. Robustness of docking protocol was analyzed through Receiver operating characteristic (ROC) curve values 0.88 (Area under curve AUC?=?0.87) in Standard Precision and 0.84 (AUC?=?0.82) in Extra Precision modes. Novelty analysis indicates that these compounds have not been reported previously as anti-epileptic agents.     

Ligand‐based pharmacophore modelling and screening of DNA minor groove binders targeting Staphylococcus aureus

The recognition of DNA by small molecules is of special importance in the design of new drugs. Many natural and synthetic compounds have the ability to interact with the minor groove of DNA. In the present study, identification of minor groove binding compounds was attained by the combined approach of pharmacophore modelling, virtual screening and molecular dynamics approach. Experimentally reported 32 minor groove binding compounds were used to develop the pharmacophore model. Based on the fitness score, best three pharmacophore hypotheses were selected and used as template for screening the compounds from drug bank database. This pharmacophore‐based screening provides many compounds with the same pharmacological properties. All these compounds were subjected to four phases of docking protocols with combined Glide‐quantum‐polarized ligand docking approach. Molecular dynamics results indicated that selected compounds are more active and showed good interaction in the binding site of DNA. Based on the scoring parameters and energy values, the best compounds were selected, and antibacterial activity of these compounds was identified using in vitro antimicrobial techniques. Copyright © 2014 John Wiley & Sons, Ltd.     

155 3D QSAR and protein–protein interaction studies on neuraminidase against Clostridium perfringens: An approach toward target identification using structure-based drug designing

The rapid onset of resistance to new drugs and emergence of antibiotic resistant bacteria has led to resurgence in life-threatening bacterial infections. These problems have revitalized interest in antibiotics and lead to new research. To gain further insight between structural and biological activity of Clostridium perfringens, a gram-positive anaerobe responsible for food poisoning, mynecrosis in wound infections, and enterotoxemia in humans. We have considered various in silico approaches for developing new drug leads, based on small ligand structure. The importance of neuraminidases in the virulence of C. perfringens makes it a potent target for the studies of drug designing against this microbe. Natural products or their direct derivatives play crucial roles in many diseases. In the present study, 3D QSAR analysis using kNN-MFA method was performed on a series of pterocarpan derivatives as Clostridial neuraminidase inhibitors. Twenty-five compounds using random selection and sphere exclusion method for the division of dataset into training and test set were chosen. kNN-MFA methodology with stepwise, simulated annealing and genetic algorithm was used for model building and four predictive models have been generated. The most significant model has a high internal predictivity of 64.80% (q ²?=?0.6480) and an external predictivity of 95.46% (r ²?=?0.9546). Model showed that electrostatic and steric interactions play important role in determining neuraminidase inhibitory activity. The kNN-MFA plots provide further understanding of the relationship between structural features of substituted pterocarpan derivatives and their activities which were applied for designing new compounds as inhibitors. The drug likeliness of these compounds was checked through ADME property prediction and their interaction with the neuraminidase was checked by molecular docking studies. Moreover, analysis of protein–protein interaction network of NanI in C. perfringens was done.     

BEAR, a novel virtual screening methodology for drug discovery

BEAR (binding estimation after refinement) is a new virtual screening technology based on the conformational refinement of docking poses through molecular dynamics and prediction of binding free energies using accurate scoring functions. Here, the authors report the results of an extensive benchmark of the BEAR performance in identifying a smaller subset of known inhibitors seeded in a large (1.5 million) database of compounds. BEAR performance proved strikingly better if compared with standard docking screening methods. The validations performed so far showed that BEAR is a reliable tool for drug discovery. It is fast, modular, and automated, and it can be applied to virtual screenings against any biological target with known structure and any database of compounds.     

Antibacterial alkoxybenzamide inhibitors of the essential bacterial cell division protein FtsZ

3-Methoxybenzamide is a weak inhibitor of the essential bacterial cell division protein FtsZ. Exploration of the structure–activity relationships of 3-methoxybenzamide analogues led to the identification of potent anti-staphylococcal compounds.     

Insights into nucleotide recognition by cell division protein FtsZ from a mant-GTP competition assay and molecular dynamics

Essential cell division protein FtsZ forms the bacterial cytokinetic ring and is a target for new antibiotics. FtsZ monomers bind GTP and assemble into filaments. Hydrolysis to GDP at the association interface between monomers leads to filament disassembly. We have developed a homogeneous competition assay, employing the fluorescence anisotropy change of mant-GTP upon binding to nucleotide-free FtsZ, which detects compounds binding to the nucleotide site in FtsZ monomers and measures their affinities within the millimolar to 10 nM range. We have employed this method to determine the apparent contributions of the guanine, ribose, and the α-, β-, and γ-phosphates to the free energy change of nucleotide binding. Similar relative contributions have also been estimated through molecular dynamics and binding free energy calculations, employing the crystal structures of FtsZ-nucleotide complexes. We find an energetically dominant contribution of the β-phosphate, comparable to the whole guanosine moiety. GTP and GDP bind with similar observed affinity to FtsZ monomers. Loss of the regulatory γ-phosphate results in a predicted accommodation of GDP which has not been observed in the crystal structures. The binding affinities of a series of C8-substituted GTP analogues, known to inhibit FtsZ but not eukaryotic tubulin assembly, correlate with their inhibitory capacity on FtsZ polymerization. Our methods permit testing of FtsZ inhibitors targeting its nucleotide site, as well as compounds from virtual screening of large synthetic libraries. Our results give insight into the FtsZ-nucleotide interactions, which could be useful in the rational design of new inhibitors, especially GTP phosphate mimetics.     

Pharmacophore-based virtual screening approach for identification of potent natural modulatory compounds of human Toll-like receptor 7

Abstract

Toll-like receptor 7 (TLR7) is a transmembrane glycoprotein playing very crucial role in the signaling pathways involved in innate immunity and has been demonstrated to be useful in fighting against infectious disease by recognizing viral ssRNA & specific small molecule agonists. In order to find novel human TLR7 (hTLR7) modulators, computational ligand-based pharmacophore modeling approach was used to identify the molecular chemical features required for the modulation of hTLR7 protein. A training set of 20 TLR7 agonists with their known experimental activity was used to create pharmacophore model using 3D-QSAR pharmacophore generation (HypoGen algorithm) module in Discovery Studio. The best developed hypothesis consists of four pharmacophoric features namely, one hydrogen bond donor (HBD), one ring aromatic (RA), and two hydrophobic (HY) character. The developed hypothesis was then validated by different methods such as cost analysis, test set method, and Fischer’s test method for consistency. Hence, this validated model was further employed for screening of natural hit compounds from InterBioScreen Natural product database, consisting of more than 60,000 natural compounds and derivatives. The screened hit compounds were subsequently filtered by Lipinski’s rule of 5, ADME and toxicity parameters and molecular docking studies to remove the false positive rates. Finally, molecular docking analysis led to identification of the (3a′S,6a′R)-3′-(3,4-dihydroxybenzyl)-5′-(3,4-dimethoxyphenethyl)-5-ethyl-3′,3a′-dihydro-2′H-spiro[indoline-3,1′-pyrrolo[3,4-c]pyrrole]-2,4′,6′(5′H,6a′H)-trione (Compound ID: STOCK1N-65837) as potent hTLR7 modulator due to its better docking score and molecular interactions compared to other compounds. The result of virtual screening was further validated using molecular dynamics (MD) simulation analysis. Thus, a 30?ns MD simulation analysis revealed high stability and effective binding of STOCK1N-65837 within the binding site of hTLR7. Therefore, the present study provides confidence for the utility of the selected chemical feature based pharmacophore model to design novel TLR7 modulators with desired biological activity.     

Shape-based virtual screening,docking, and molecular dynamics simulations to identify Mtb-ASADH inhibitors

Aspartate β-semialdehyde dehydrogenase (ASADH) is a key enzyme for the biosynthesis of essential amino acids and several important metabolites in microbes. Inhibition of ASADH enzyme is a promising drug target strategy against Mycobacterium tuberculosis (Mtb). In this work, in silico approach was used to identify potent inhibitors of Mtb-ASADH. Aspartyl β-difluorophosphonate (β-AFP), a known lead compound, was used to understand the molecular recognition interactions (using molecular docking and molecular dynamics analysis). This analysis helped in validating the computational protocol and established the participation of Arg99, Glu224, Cys130, Arg249, and His256 amino acids as the key amino acids in stabilizing ligand–enzyme interactions for effective binding, an essential feature is H-bonding interactions with the two arginyl residues at the two ends of the ligand. Best binding conformation of β-AFP was selected as a template for shape-based virtual screening (ZINC and NCI databases) to identify compounds that competitively inhibit the Mtb-ASADH. The top rank hits were further subjected to ADME and toxicity filters. Final filter was based on molecular docking analysis. Each screened molecule carries the characteristics of the highly electronegative groups on both sides separated by an average distance of 6?Å. Finally, the best predicted 20 compounds exhibited minimum three H-bonding interactions with Arg99 and Arg249. These identified hits can be further used for designing the more potent inhibitors against ASADH family. MD simulations were also performed on two selected compounds (NSC4862 and ZINC02534243) for further validation. During the MD simulations, both compounds showed same H-bonding interactions and remained bound to key active residues of Mtb-ASADH.     

Docking small ligands to molecule of the plant FtsZ protein: Application of the CUDA technology for faster computations

The opportunities to apply the CUDA technology for faster computations in structural biology and bioinformatics are reviewed and analyzed. Using HEX 6.1 software, we performed a comparative analysis of the efficiency and the increase in quality after CUDA application. The work was conducted on the example of rigid docking of low-molecular-weight compounds of different classes on the surface of the Arabidopsis thaliana FtsZ. Several potential binding sites of benzimidazoles to the plant FtsZ were identified.     

基于分子对接技术筛选中草药中潜在的H1N1病毒神经氨酸酶抑制剂

甲型H1N1流感病毒是一种高度接触性急性呼吸道传染病,给人类健康造成了极大威胁。作为一个已经被证明的抗流感药物靶点,神经氨酸酶在流感病毒复制和传播中发挥重要作用,并且其活性中心的氨基酸组成高度保守。本研究中,我们使用分子对接技术筛选从中草药小分子数据库中筛选神经氨酸酶潜在的抑制剂,结果得到4个亲和力高于奥司他韦(Osel-tamivir)的化合物,并确定了他们的中草药来源。为从草药中提取,设计以及实验合成新的神经氨酸酶抑制剂提供了一定的依据和指导。     

The FtsZ protein of Bacillus subtilis is localized at the division site and has GTPase activity that is dependent upon FtsZ concentration

The ftsZ gene is essential for cell division in both Escherichia coli and Bacillus subtilis. In E. coli FtsZ forms a cytokinetic ring at the division site whose formation is under cell-cycle control. In addition, the FtsZ from E. coli has a GTPase activity that shows an unusual lag in vitro. In this study we show that FtsZ in Bacillus subtilis forms a ring that is at the tip of the invaginating septum. The FtsZ ring is dynamic since it is formed as division is initiated, changes diameter during septation, and disperses upon completion of septation. In vitro the purified FtsZ from B. subtilis exhibits a GTPase activity without a demonstrable lag, but the GTPase activity is markedly dependent upon the FtsZ concentration, suggesting that the FtsZ protein must oligomerize to express the GTPase activity.     

Pharmacophore generation,atom-based 3D-QSAR,molecular docking and molecular dynamics simulation studies on benzamide analogues as FtsZ inhibitors

FtsZ is an appealing target for the design of antimicrobial agent that can be used to defeat the multidrug-resistant bacterial pathogens. Pharmacophore modelling, molecular docking and molecular dynamics (MD) simulation studies were performed on a series of three-substituted benzamide derivatives. In the present study a five-featured pharmacophore model with one hydrogen bond acceptors, one hydrogen bond donors, one hydrophobic and two aromatic rings was developed using 97 molecules having MIC values ranging from .07 to 957 μM. A statistically significant 3D-QSAR model was obtained using this pharmacophore hypothesis with a good correlation coefficient (R² = .8319), cross validated coefficient (Q² = .6213) and a high Fisher ratio (F = 103.9) with three component PLS factor. A good correlation between experimental and predicted activity of the training (R² = .83) and test set (R² = .67) molecules were displayed by ADHRR.1682 model. The generated model was further validated by enrichment studies using the decoy test and MAE-based criteria to measure the efficiency of the model. The docking studies of all selected inhibitors in the active site of FtsZ protein showed crucial hydrogen bond interactions with Val 207, Asn 263, Leu 209, Gly 205 and Asn-299 residues. The binding free energies of these inhibitors were calculated by the molecular mechanics/generalized born surface area VSGB 2.0 method. Finally, a 15 ns MD simulation was done to confirm the stability of the 4DXD–ligand complex. On a wider scope, the prospect of present work provides insight in designing molecules with better selective FtsZ inhibitory potential.     

The essential role of SepF in mycobacterial division

Mycobacteria lack several of the components that are essential in model systems as Escherichia coli or Bacillus subtilis for the formation of the divisome, a ring‐like structure assembling at the division site to initiate bacterial cytokinesis. Divisome assembly depends on the correct placement of the FtsZ protein into a structure called the Z ring. Notably, early division proteins that assist in the localisation of the Z ring to the cytoplasmic membrane and modulate its structure are missing in the so far known mycobacterial cell division machinery. To find mycobacterium‐relevant components of the divisome that might act at the level of FtsZ, a yeast two‐hybrid screening was performed with FtsZ from Mycobacterium tuberculosis. We identified the SepF homolog as a new interaction partner of mycobacterial FtsZ. Depending on the presence of FtsZ, SepF‐GFP fusions localised in ring‐like structures at potential division sites. Alteration of SepF levels in Mycobacterium smegmatis led to filamentous cells, indicating a division defect. Depletion of SepF resulted in a complete block of division. The sepF gene is highly conserved in the M. tuberculosis complex members. We therefore propose that SepF is an essential part of the core division machinery in the genus Mycobacterium.