981 resultados para molecular docking
Resumo:
Background: HLA-DPs are class II MHC proteins mediating immune responses to many diseases. Peptides bind MHC class II proteins in the acidic environment within endosomes. Acidic pH markedly elevates association rate constants but dissociation rates are almost unchanged in the pH range 5.0 - 7.0. This pH-driven effect can be explained by the protonation/deprotonation states of Histidine, whose imidazole has a pKa of 6.0. At pH 5.0, imidazole ring is protonated, making Histidine positively charged and very hydrophilic, while at pH 7.0 imidazole is unprotonated, making Histidine less hydrophilic. We develop here a method to predict peptide binding to the four most frequent HLA-DP proteins: DP1, DP41, DP42 and DP5, using a molecular docking protocol. Dockings to virtual combinatorial peptide libraries were performed at pH 5.0 and pH 7.0. Results: The X-ray structure of the peptide - HLA-DP2 protein complex was used as a starting template to model by homology the structure of the four DP proteins. The resulting models were used to produce virtual combinatorial peptide libraries constructed using the single amino acid substitution (SAAS) principle. Peptides were docked into the DP binding site using AutoDock at pH 5.0 and pH 7.0. The resulting scores were normalized and used to generate Docking Score-based Quantitative Matrices (DS-QMs). The predictive ability of these QMs was tested using an external test set of 484 known DP binders. They were also compared to existing servers for DP binding prediction. The models derived at pH 5.0 predict better than those derived at pH 7.0 and showed significantly improved predictions for three of the four DP proteins, when compared to the existing servers. They are able to recognize 50% of the known binders in the top 5% of predicted peptides. Conclusions: The higher predictive ability of DS-QMs derived at pH 5.0 may be rationalised by the additional hydrogen bond formed between the backbone carbonyl oxygen belonging to the peptide position before p1 (p-1) and the protonated ε-nitrogen of His 79β. Additionally, protonated His residues are well accepted at most of the peptide binding core positions which is in a good agreement with the overall negatively charged peptide binding site of most MHC proteins. © 2012 Patronov et al.; licensee BioMed Central Ltd.
Resumo:
Proteins of the Major Histocompatibility Complex (MHC) bind self and nonself peptide antigens or epitopes within the cell and present them at the cell surface for recognition by T cells. All T-cell epitopes are MHC binders but not all MCH binders are T-cell epitopes. The MHC class II proteins are extremely polymorphic. Polymorphic residues cluster in the peptide-binding region and largely determine the MHC's peptide selectivity. The peptide binding site on MHC class II proteins consist of five binding pockets. Using molecular docking, we have modelled the interactions between peptide and MHC class II proteins from locus DRB1. A combinatorial peptide library was generated by mutation of residues at peptide positions which correspond to binding pockets (so called anchor positions). The binding affinities were assessed using different scoring functions. The normalized scoring functions for each amino acid at each anchor position were used to construct quantitative matrices (QM) for MHC class II binding prediction. Models were validated by external test sets comprising 4540 known binders. Eighty percent of the known binders are identified in the best predicted 15% of all overlapping peptides, originating from one protein. © 2011 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Resumo:
Veterinary medicines (VMs) from agricultural industry can enter the environment in a number of ways. This includes direct exposure through aquaculture, accidental spillage and disposal, and indirect entry by leaching from manure or runoff after treatment. Many compounds used in animal treatments have ecotoxic properties that may have chronic or sometimes lethal effects when they come into contact with non-target organisms. VMs enter the environment in mixtures, potentially having additive effects. Traditional ecotoxicology tests are used to determine the lethal and sometimes reproductive effects on freshwater and terrestrial organisms. However, organisms used in ecotoxicology tests can be unrepresentative of the populations that are likely to be exposed to the compound in the environment. Most often the tests are on single compound toxicity but mixture effects may be significant and should be included in ecotoxicology testing. This work investigates the use, measured environmental concentrations (MECs) and potential impact of sea lice treatments on salmon farms in Scotland. Alternative methods for ecotoxicology testing including mixture toxicity, and the use of in silico techniques to predict the chronic impact of VMs on different species of aquatic organisms were also investigated. The Scottish Environmental Protection Agency (SEPA) provided information on the use of five sea lice treatments from 2008-2011 on Scottish salmon farms. This information was combined with the recently available data on sediment MECs for the years 2009-2012 provided by SEPA using ArcGIS 10.1. In depth analysis of this data showed that from a total of 55 sites, 30 sites had a MEC higher than the maximum allowable concentration (MAC) as set out by SEPA for emamectin benzoate and 7 sites had a higher MEC than MAC for teflubenzuron. A number of sites that were up to 16 km away from the nearest salmon farm reported as using either emamectin benzoate or teflubenzuron measured positive for the two treatments. There was no relationship between current direction and the distribution of the sea lice treatments, nor was there any evidence for alternative sources of the compounds e.g. land treatments. The sites that had MECs higher than the MAC could pose a risk to non-target organisms and disrupt the species dynamics of the area. There was evidence that some marine protected sites might be at risk of exposure to these compounds. To complement this work, effects on acute mixture toxicity of the 5 sea lice treatments, plus one major metabolite 3-phenoxybenzoic acid (3PBA), were measured using an assay using the bioluminescent bacteria Aliivibrio fischeri. When exposed to the 5 sea lice treatments and 3PBA A. fischeri showed a response to 3PBA, emamectin benzoate and azamethiphos as well as combinations of the three. In order to establish any additive effect of the sea lice treatments, the efficacy of two mixture prediction equations, concentration addition (CA) and independent action ii(IA) were tested using the results from single compound dose response curves. In this instance IA was the more effective prediction method with a linear regression confidence interval of 82.6% compared with 22.6% of CA. In silico molecular docking was carried out to predict the chronic effects of 15 VMs (including the five used as sea lice control). Molecular docking has been proposed as an alternative screening method for the chronic effects of large animal treatments on non-target organisms. Oestrogen receptor alpha (ERα) of 7 non-target bony fish and the African clawed frog Xenopus laevis were modelled using SwissModel. These models were then ‘docked’ to oestradiol, the synthetic oestrogen ethinylestradiol, two known xenoestrogens dichlorodiphenyltrichloroethane (DDT) and bisphenol A (BPA), the antioestrogen breast cancer treatment tamoxifen and 15 VMs using Auto Dock 4. Based on the results of this work, four VMs were identified as being possible xenoestrogens or anti-oestrogens; these were cypermethrin, deltamethrin, fenbendazole and teflubenzuron. Further investigation, using in vitro assays, into these four VMs has been suggested as future work. A modified recombinant yeast oestrogen screen (YES) was attempted using the cDNA of the ERα of the zebrafish Danio rerio and the rainbow trout Oncorhynchus mykiss. Due to time and difficulties in cloning protocols this work was unable to be completed. Use of such in vitro assays would allow for further investigation of the highlighted VMs into their oestrogenic potential. In conclusion, VMs used as sea lice treatments, such as teflubenzuron and emamectin benzoate may be more persistent and have a wider range in the environment than previously thought. Mixtures of sea lice treatments have been found to persist together in the environment, and effects of these mixtures on the bacteria A. fischeri can be predicted using the IA equation. Finally, molecular docking may be a suitable tool to predict chronic endocrine disrupting effects and identify varying degrees of impact on the ERα of nine species of aquatic organisms.
Resumo:
Ligand-protein docking is an optimization problem based on predicting the position of a ligand with the lowest binding energy in the active site of the receptor. Molecular docking problems are traditionally tackled with single-objective, as well as with multi-objective approaches, to minimize the binding energy. In this paper, we propose a novel multi-objective formulation that considers: the Root Mean Square Deviation (RMSD) difference in the coordinates of ligands and the binding (intermolecular) energy, as two objectives to evaluate the quality of the ligand-protein interactions. To determine the kind of Pareto front approximations that can be obtained, we have selected a set of representative multi-objective algorithms such as NSGA-II, SMPSO, GDE3, and MOEA/D. Their performances have been assessed by applying two main quality indicators intended to measure convergence and diversity of the fronts. In addition, a comparison with LGA, a reference single-objective evolutionary algorithm for molecular docking (AutoDock) is carried out. In general, SMPSO shows the best overall results in terms of energy and RMSD (value lower than 2A for successful docking results). This new multi-objective approach shows an improvement over the ligand-protein docking predictions that could be promising in in silico docking studies to select new anticancer compounds for therapeutic targets that are multidrug resistant.
Resumo:
A library of isoquinolinone and azepanone derivatives were screened for both acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE) activity. The strategy adopted included (a) in vitro biological assays, against eel AChE (EeAChE) and equine serum BuChE (EqBuChE) in order to determine the compounds IC50 and their dose-response activity, consolidated by (b) molecular docking studies to evaluate the docking poses and interatomic interactions in the case of the hit compounds, validated by STD-NMR studies. Compound (1f) was identified as one of these hits with an IC50 of 89.5 mu M for EeAChE and 153.8 mu M for EqBuChE, (2a) was identified as a second hit with an IC50 of 108.4 mu M (EeAChE) and 277.8 mu M (EqBuChE). In order to gain insights into the binding mode and principle active site interactions of these molecules, (R)-(1f) along with 3 other analogues (also as the R-enantiomer) were docked into both RhAChE and hBuChE models. Galantamine was used as the benchmark. The docking study was validated by performing an STD-NMR study of (1f) with EeAChE using galantamine as the benchmark.
Resumo:
Rivastigmine is a very important drug prescribed for the treatment of Alzheimer's disease (AD) symptoms. It is a dual inhibitor, in that it inhibits both acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE). For our screening program on the discovery of new rivastigmine analogue hits for human butyrylcholinesterase (hBuChE) inhibition, we investigated the interaction of this inhibitor with BuChE using the complimentary approach of the biophysical method, saturation transfer difference (STD)-NMR and molecular docking. This allowed us to obtain essential information on the key binding interactions between the inhibitor and the enzyme to be used for screening of hit compounds. The main conclusions obtained from this integrated study was that the most dominant interactions were (a) H-bonding between the carbamate carbonyl of the inhibitor and the NH group of the imidazole unit of H434, (b) stacking of the aromatic unit of the inhibitor and the W82 aromatic unit in the choline binding pocket via pi-pi interactions and (c) possible CH/pi interactions between the benzylic methyl group and the N-methyl groups of the inhibitor and W82 of the enzyme.
Resumo:
Phenolic marine natural product is a kind of new potential aldose reductase inhibitors (ARIs). In order to investigate the binding mode and inhibition mechanism, molecular docking and dynamics studies were performed to explore the interactions of six phenolic inhibitors with human aldose reductase (hALR2). Considering physiological environment, all the neutral and other two ionized states of each phenolic inhibitor were adopted in the simulation. The calculations indicate that all the inhibitors are able to form stable hydrogen bonds with the hALR2 active pocket which is mainly constructed by residues TYR48, HIS110 and TRP111, and they impose the inhibition effect by occupying the active space. In all inhibitors, only La and its two ionized derivatives La_ion1 and La_ion2, in which neither of the ortho-hydrogens of 3-hydroxyl is substituted by Br, bind with hALR2 active residues using the terminal 3-hydroxyl. While, all the other inhibitors, at least one of whose ortho-sites of 3- and 6-hydroxyls are substituted by Br substituent which take much electron-withdrawing effect and steric hindrance, bind with hALR2 through the lactone group. This means that the Br substituent can effectively regulate the binding modes of phenolic inhibitors. Although the lactone bound inhibitors have relatively high RMSD values, our dynamics study shows that both binding modes are of high stability. For each inhibitor molecule, the ionization does not change its original binding mode, but it does gradually increase the binding free energy, which reveals that besides hydrogen bonds, the electrostatic effect is also important to the inhibitor–hALR2 interaction.
Resumo:
The DNA G-qadruplexes are one of the targets being actively explored for anti-cancer therapy by inhibiting them through small molecules. This computational study was conducted to predict the binding strengths and orientations of a set of novel dimethyl-amino-ethyl-acridine (DACA) analogues that are designed and synthesized in our laboratory, but did not diffract in Synchrotron light.Thecrystal structure of DNA G-Quadruplex(TGGGGT)4(PDB: 1O0K) was used as target for their binding properties in our studies.We used both the force field (FF) and QM/MM derived atomic charge schemes simultaneously for comparing the predictions of drug binding modes and their energetics. This study evaluates the comparative performance of fixed point charge based Glide XP docking and the quantum polarized ligand docking schemes. These results will provide insights on the effects of including or ignoring the drug-receptor interfacial polarization events in molecular docking simulations, which in turn, will aid the rational selection of computational methods at different levels of theory in future drug design programs. Plenty of molecular modelling tools and methods currently exist for modelling drug-receptor or protein-protein, or DNA-protein interactionssat different levels of complexities.Yet, the capasity of such tools to describevarious physico-chemical propertiesmore accuratelyis the next step ahead in currentresearch.Especially, the usage of most accurate methods in quantum mechanics(QM) is severely restricted by theirtedious nature. Though the usage of massively parallel super computing environments resulted in a tremendous improvement in molecular mechanics (MM) calculations like molecular dynamics,they are still capable of dealing with only a couple of tens to hundreds of atoms for QM methods. One such efficient strategy that utilizes thepowers of both MM and QM are the QM/MM hybrid methods. Lately, attempts have been directed towards the goal of deploying several different QM methods for betterment of force field based simulations, but with practical restrictions in place. One of such methods utilizes the inclusion of charge polarization events at the drug-receptor interface, that is not explicitly present in the MM FF.
Resumo:
The formation of telomeric G-quadruplexes has been shown to inhibit telomerase activity. Indeed, a number of small molecules capable of p-stacking with G-tetrads have shown the ability to inhibit telomerase activity through the stabilization of G-quadruplexes. Curcumin displays a wide spectrum of medicinal properties ranging from anti-bacterial, anti-viral, anti-protozoal, anti-fungal and anti-inflammatory to anti-cancer activity. We have investigated the interactions of curcumin and its structural analogues with the human telomeric sequence AG(3)(T(2)AG(3))(3) under molecular crowding conditions. Experimental studies indicated the existence of a AG(3)(T(2)AG(3))(3)/curcumin complex with binding affinity of 0.72 x 10(6) M-1 under molecular crowding conditions. The results from UV-visible absorption spectroscopy, a fluorescent TO displacement assay, circular dichroism and molecular docking studies, imply that curcumin and their analogues interact with G-quadruplex DNA via groove binding. While other analogs of curcumin studied here bind to G-quadruplexes in a qualitatively similar manner their affinities are relatively lower in comparison to curcumin. The Knoevenagel condensate, a methoxy-benzylidene derivative of curcumin, also exhibited significant binding to G-quadruplex DNA, although with two times decreased affinity. Our study establishes the potential of curcumin as a promising natural product for G-quadruplex specific ligands.
Resumo:
The formation of telomeric G-quadruplexes has been shown to inhibit telomerase activity. Indeed, a number of small molecules capable of p-stacking with G-tetrads have shown the ability to inhibit telomerase activity through the stabilization of G-quadruplexes. Curcumin displays a wide spectrum of medicinal properties ranging from anti-bacterial, anti-viral, anti-protozoal, anti-fungal and anti-inflammatory to anti-cancer activity. We have investigated the interactions of curcumin and its structural analogues with the human telomeric sequence AG(3)(T(2)AG(3))(3) under molecular crowding conditions. Experimental studies indicated the existence of a AG(3)(T(2)AG(3))(3)/curcumin complex with binding affinity of 0.72 x 10(6) M-1 under molecular crowding conditions. The results from UV-visible absorption spectroscopy, a fluorescent TO displacement assay, circular dichroism and molecular docking studies, imply that curcumin and their analogues interact with G-quadruplex DNA via groove binding. While other analogs of curcumin studied here bind to G-quadruplexes in a qualitatively similar manner their affinities are relatively lower in comparison to curcumin. The Knoevenagel condensate, a methoxy-benzylidene derivative of curcumin, also exhibited significant binding to G-quadruplex DNA, although with two times decreased affinity. Our study establishes the potential of curcumin as a promising natural product for G-quadruplex specific ligands.
Resumo:
Objectives: The ram locus, consisting of the romA–ramA genes, is repressed by the tetracycline-type regulator RamR, where regulation is abolished due to loss-of-function mutations within the protein or ligand interactions. The aim of this study was to determine whether the phenothiazines (chlorpromazine and thioridazine) directly interact with RamR to derepress ramA expression.
Methods: Quantitative real-time PCR analyses were performed to determine expression levels of the romA–ramA genes after exposure to the phenothiazines. Electrophoretic mobility shift assays (EMSAs) and in vitro transcription experiments were performed to show direct binding to and repression by RamR. Direct binding of the RamR protein to the phenothiazines was measured by fluorescence spectroscopy experiments and molecular docking models were generated using the RamR crystal structure.
Results: Exposure to either chlorpromazine or thioridazine resulted in the up-regulation of the romA–ramA genes. EMSAs and in vitro transcription experiments demonstrated that both agents reduce/abolish binding and enhance transcription of the target PI promoter upstream of the ramR–romA genes in Klebsiella pneumoniae compared with RamR alone. Fluorescence spectroscopy measurements demonstrated that RamR directly binds both chlorpromazine and thioridazine with micromolar affinity. Molecular docking analyses using the RamR crystal structure demonstrated that the phenothiazines interact with RamR protein through contacts described for other ligands, in addition to forming unique strong polar interactions at positions D152 and K63.
Conclusions: These data demonstrate that phenothiazines can modulate loci linked to the microbe–drug response where RamR is an intracellular target for the phenothiazines, thus resulting in a transient non-mutational derepression of ramA concentrations.
Resumo:
A series of novel naphthyridine derivatives 3 and 4 was prepared from substituted pyridine 2 and ketones using ZnCl2 as catalyst under microwave irradiation conditions. All the compounds were evaluated for AChE inhibitory activity and promising compounds 3d, 3e, 4b, and 4g was identified. Representative compounds 3d and 3e were found to show insignificant THLE-2 liver cell viability/toxicity. The binding mode between X-ray crystal structure of human AChE and compounds was studied using molecular docking method and fitness scores were found to be in good correlation with the activity data.
Resumo:
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Resumo:
Background: This paper addresses the prediction of the free energy of binding of a drug candidate with enzyme InhA associated with Mycobacterium tuberculosis. This problem is found within rational drug design, where interactions between drug candidates and target proteins are verified through molecular docking simulations. In this application, it is important not only to correctly predict the free energy of binding, but also to provide a comprehensible model that could be validated by a domain specialist. Decision-tree induction algorithms have been successfully used in drug-design related applications, specially considering that decision trees are simple to understand, interpret, and validate. There are several decision-tree induction algorithms available for general-use, but each one has a bias that makes it more suitable for a particular data distribution. In this article, we propose and investigate the automatic design of decision-tree induction algorithms tailored to particular drug-enzyme binding data sets. We investigate the performance of our new method for evaluating binding conformations of different drug candidates to InhA, and we analyze our findings with respect to decision tree accuracy, comprehensibility, and biological relevance. Results: The empirical analysis indicates that our method is capable of automatically generating decision-tree induction algorithms that significantly outperform the traditional C4.5 algorithm with respect to both accuracy and comprehensibility. In addition, we provide the biological interpretation of the rules generated by our approach, reinforcing the importance of comprehensible predictive models in this particular bioinformatics application. Conclusions: We conclude that automatically designing a decision-tree algorithm tailored to molecular docking data is a promising alternative for the prediction of the free energy from the binding of a drug candidate with a flexible-receptor.
Resumo:
The identification of molecular processes involved in cancer development and prognosis opened avenues for targeted therapies, which made treatment more tumor-specific and less toxic than conventional therapies. One important example is the epidermal growth factor receptor (EGFR) and EGFR-specific inhibitors (i.e. erlotinib). However, challenges such as drug resistance still remain in targeted therapies. Therefore, novel candidate compounds and new strategies are needed for improvement of therapy efficacy. Shikonin and its derivatives are cytotoxic constituents in traditional Chinese herbal medicine Zicao (Lithospermum erythrorhizin). In this study, we investigated the molecular mechanisms underlying the anti-cancer effects of shikonin and its derivatives in glioblastoma cells and leukemia cells. Most of shikonin derivatives showed strong cytotoxicity towards erlotinib-resistant glioblastoma cells, especially U87MG.ΔEGFR cells which overexpressed a deletion-activated EGFR (ΔEGFR). Moreover, shikonin and some derivatives worked synergistically with erlotinib in killing EGFR-overexpressing cells. Combination treatment with shikonin and erlotinib overcame the drug resistance of these cells to erlotinib. Western blotting analysis revealed that shikonin inhibited ΔEGFR phosphorylation and led to corresponding decreases in phosphorylation of EGFR downstream molecules. By means of Loewe additivity and Bliss independence drug interaction models, we found erlotinb and shikonin or its derivatives corporately suppressed ΔEGFR phosphorylation. We believed this to be a main mechanism responsible for their synergism in U87MG.ΔEGFR cells. In leukemia cells, which did not express EGFR, shikonin and its derivatives exhibited even greater cytotoxicity, suggesting the existence of other mechanisms. Microarray-based gene expression analysis uncovered the transcription factor c-MYC as the commonly deregulated molecule by shikonin and its derivatives. As validated by Western blotting analysis, DNA-binding assays and molecular docking, shikonin and its derivatives bound and inhibited c-MYC. Furthermore, the deregulation of ERK, JNK MAPK and AKT activity was closely associated with the reduction of c-MYC, indicating the involvement of these signaling molecules in shikonin-triggered c-MYC inactivation. In conclusion, the inhibition of EGFR signaling, synergism with erlotinib and targeting of c-MYC illustrate the multi-targeted feature of natural naphthoquinones such as shikonin and derivatives. This may open attractive possibilities for their use in a molecular targeted cancer therapy.