Molecular Docking Scores Research Articles

Hypolipidemic Activity of Prosopis cineraria L (Druce) Fruit Extract and Molecular Modeling Study with Farnesoid X Receptor (FXR)

Purpose: To investigate the hypolipidemic potential of the 70 % ethanol fruit extract of Prosopis cineraria (Fabaceae) (Et. PCF) in triton-induced hyperlipidemia in rats.Methods: Et-PCF was obtained by pulverizing whole dried fruits and extracting with 70 % ethanol. Adult Sprague Dawley rats were divided into six groups of six rats each. The groups were namely normal control, hyperlipidaemic control, standard drug-treated (simvastatin 4 mg/kg), and three Et-PCF (200, 400 and 600 mg/kg, respectively)-treated groups. Apart from normal control, all other groups received a single dose of triton (200 mg/kg, i.p.) exactly 30 min after a dose of the standard drug and Et-PCF for the induction of hyperlipidemia. Twenty four hours after trito injection, hyperlipidemia was confirmed by collecting blood samples from all the rats and testing for serum lipid profile. Antioxidant activity, in the form of inhibition of lipid peroxidation, was determined along with chromatographic analysis. Moreover, molecular docking study of â-sitosterol (active constitute of PCF) was performed with Farnesoid X receptor.Results: Triton-induced hyperlipidemia group showed significant increase in total cholesterol, low density lipoprotein cholesterol (LDL), very low density lipoprotein cholesterol (VLDL) , triglyceride, atherogenic index and decreased high density lipoprotein cholesterol (HDL), compared to normal control group. Et-PCF treated groups showed reduction in serum cholesterol, triglyceride, VLDL and LDL levels compared to triton treated control group. Extract at the dose of 200 mg/kg significantly reduce serum cholesterol (p < 0.01) and serum LDL (p < 0.01). At the dose level of 400 mg/kg and 600 mg/kg extract is effective to significantly reduce serum cholesterol (p < 0.05), triglyceride (p < 0.05), VLDL (p < 0.05), LDL (p < 0.05) and atherogenic index (p < 0.05) and these results are almost equivalent to those of standard drug simvastatin. Furthermore, antioxidant activity, i.e., IC50 of Et-PCF was 58.33 ±g/ml. Molecular docking score of â-sitosterol for Farnesoid X receptor was -8.32 kcal/mol, suggesting excellent binding conformation of Et-PCF to receptor molecules.Conclusion: The findings suggest that Prosopis cineraria may be beneficial for preventing hyperlipidaemic complications by its anti-hyperlipidemic and antioxidant activities.Keywords: Prosopis cineraria, Anti-hyperlipidemic activity, Simvastatin, Triton, Docking studies, Farnesoid X receptor

Molecular docking and multivariate analysis of xanthones as antimicrobial and antiviral agents.

Xanthones are secondary metabolites which have drawn considerable interest over the last decades due to their antimicrobial properties, among others. A great number of this kind of compounds has been therefore reported, but there is a limited amount of studies on screening for biological activity. Thus, as part of our research on antimicrobial agents of natural origin, a set of 272 xanthones were submitted to molecular docking (MD) calculations with a group of seven fungal and two viral enzymes. The results indicated that prenylated xanthones are important hits for inhibition of the analyzed enzymes. The MD scores were also analyzed by multivariate statistics. Important structural details were found to be crucial for the inhibition of the tested enzymes by the xanthones. In addition, the classification of active xanthones can be achieved by statistical analysis on molecular docking scores by an affinity-antifungal activity relationship approach. The obtained results therefore are a suitable starting point for the development of antifungal and antiviral agents based on xanthones.

Kinetic and in silico studies of hydroxy-based inhibitors of carbonic anhydrase isoforms I and II

A series of hydroxy and phenolic compounds have been assayed for the inhibition of two physiologically relevant carbonic anhydrase (CA, EC 4.2.1.1) isozymes, the cytosolic human isozymes I and II. The investigated molecules showed inhibition constants in the range of 1.07–4003 and 0.09–31.5 μM at the hCA I and hCA II enzymes, respectively. In order to investigate the binding mechanisms of these inhibitors, in silico studies were also applied. Molecular docking scores of the studied compounds are compared using three different scoring algorithms, namely Glide/SP, Glide/XP and Glide/IFD. In addition, different ADME (absorption, distribution, metabolism and excretion) analysis was performed. All the examined compounds were found within the acceptable range of pharmacokinetic profiles.

Poly(ADP-ribose) polymerase (PARP)-based pharmacophore model development and its application in designing antitumor inhibitors

In this study, we suggest a workflow for the identification of potential leads targeted against poly(ADP-ribose) polymerase (PARP). To clarify the essential structure–activity relationship for the PARP inhibitors as well as identify potent leads against PARP, a qualitative pharmacophore model were established using a structure-based approach. The compounds in the Specs database were progressively filtered by the pharmacophore mapping, the rule of five, the molecular docking scores and the interactions with the critical active-site residues. The generated pharmacophore model consists of one hydrogen-bond acceptor feature, two hydrophobic features and the excluded volumes. It was validated using an internal database with a goodness of hit score of 0.87, and then utilized to screen the Specs database. Finally, nine structurally diverse compounds that showed better docking scores and the stronger interactions with the key amino acids were selected for further in vitro cytotoxicity assays. Biological evaluation indicated that all hits were found to be active with different degrees of inhibition at 40μmol/L compound concentration. Compounds 2 (an IC50 value of 22μM) and 4 (an IC50 value of 16μM) exhibited moderate antiproliferative activities against MDA-MB-231 cancer cell line.

Repurposing of Kinase Inhibitors to Target c-Abl as Potential Therapeutics for Alzheimer’s Disease

Alzheimer’s disease (AD) represents a major public health concern and has been considered as a research priority. Recently, the tyrosine kinase c-Abl has been shown as a new and potential target of AD therapy. In the current study, sophisticated molecular docking and empirical scoring functions were integrated to develop a bioinformatics predictor based on 52 kinase–inhibitor complexes with solved crystal structures and known biological activities. The predictor was then used to identify those potential c-Abl binders from a commercially available kinase inhibitor library. A total of 18 promising candidates with top scores were raised; their intermolecular interactions with c-Abl were further examined in detail by using molecular dynamics simulations and binding energy analysis. Seven out of the 18 candidates were selected and tested in vitro for their inhibitory activities against c-Abl, and, consequently, two compounds, namely S2882 and TAE684, were identified as high-activity agents (IC50 = 28 ± 5 and 12 ± 3 nM, respectively). The two compounds possess long-chain structures with multiple rings that are structurally similar to the FDA-approved drugs imatinib and nilotinib. Visual examination of molded complex structures revealed that the S2882 and TAE684 can be readily bound within the active cleft of c-Abl kinase domain, exhibiting an extended conformation. In addition, an intensive network of nonbonded interactions across the complex interfaces of c-Abl with S2882 and TAE684 was also highlighted, which confers substantial stability and specificity for the complex systems.

Antibacterial potential of selected 4-phenyl hydroxycoumarins: integrated in vitro and molecular docking studies

The antibacterial activity (minimal inhibitory concentration—MIC) of selected 4-phenyl hydroxycoumarins was evaluated using Micro-well Dilution Assay against 20 laboratory bacterial control strains (ATCC). The highest antibacterial activity was found for 5,7-dihydroxy-4-phenyl coumarin and the lowest for 7-hydroxy-4-phenyl coumarin. All tested compounds had an inhibitory effect at concentrations of 0.01–10.0 mg/mL with the exception against Pseudomonas aeruginosa and Proteus mirabilis strains, which did not react even at the highest tested concentration of 10 mg/mL. In general, compounds showed better activity against Gram (+) bacteria (MIC = 0.01–2.50 mg/mL) compared to Gram (−) bacteria (MIC = 0.16–10.00 mg/mL). Molecular docking simulations against Staphylococcus aureus tyrosyl-tRNA synthetase and Escherichia coli topoisomerase II DNA gyrase B were performed. Correlation between the observed inhibitory activity and the in silico molecular docking scores of the compounds were observed through hydrogen-bonding interactions and calculated docking scores. These findings suggest that 4-phenyl hydroxycoumarins may be considered as good molecular templates for potential antibacterial agents.

In Silico Approach to Inhibition of Tyrosinase by Ascorbic Acid Using Molecular Docking Simulations

Current evidence suggests that endogenous dopamine may act as a neurotoxin following its oxidation to an oquinone and reaction with cellular thiols, which are neutoxic, which may occur spontaneously or via reaction with tyrosinase or some other enzymes. Tyrosinase (E.C. 1.14.18.1) with two cupper ions coordinated by three histidines is a bifunctional enzyme that catalyses both the hydroxylation of tyrosine to L-DOPA and the consequent oxidation of the resulting catechol-containing species to an o-quinone. Therefore, tyrosinase may play a role in neuromelanin formation in the brain and could be central to dopamine neurotoxicity by contributing to the neurodegeneration associated with Parkinson's disease. In the present study, inhibitory effect of ascorbic acid against tyrosinase has been investigated and it has shown a remarkable inhibitory effect in in vitro assays. Then, the in silico-based experiments established through molecular docking calculations and scoring, docking search algorithm, and data plotting indicated that ascorbic acid is strong inhibitor of tyrosinase by interacting with four amino acid units (histidine 263, serine 282, phenylalanine 264, and valin 283) in the active site of the enzyme. The compound also had two long distant hydrogen bindings with Cu1 and Cu2 with distances of 3.57 and 3.41 A, respectively, through its O5 atom.

Computational Insights into the Competitive Inhibition of Acetyl Coenzyme A and Succinyl Coenzyme A of the First Step of Citric Acid Cycle

Citric acid cycle comprises a various chemical reactions and it is required by all aerobic organisms to generate ATP. The present investigation focuses on the competitive inhibition of citrate synthase- the first step of the citric acid cycle. The known natural substrate of citrate synthase is acetyl Coenzyme A. Initially, the first substrate oxaloacetate binds to the citrate synthase which then induces the enzyme to change its conformation thus creating a binding site for the acetyl Coenzyme A. There are also several reports of citrate synthase enzyme inhibited by succinyl Coenzyme A which resembles acetyl Coenzyme A and acts as a competitive inhibitor. Hence, the present investigation deals with the molecular docking simulation studies of the two substrates viz. acetyl Coenzyme A and succinyl Coenzyme A at the active site of the citrate synthase to understand the insights into the competitive inhibition of these two substrates. Lastly, we have also performed the density functional theory (DFT) analysis of acetyl Coenzyme A and succinyl Coenzyme A to understand the atomic charge that might contribute in the competitive inhibition. The molecular docking scores and interaction energy revealed acetyl Coenzyme A showing competitive inhibition with succinyl Coenzyme A with favourable energy. Also the DFT studies revealed the plausible caused of the competitive inhibition at the atomic level.

Design, Synthesis and Biological Evaluation of Some 2‐Azetidinone Derivatives as Potential Antihyperlipidemic Agents

In an effort to develop new molecules with improved antihyperlipidemic activity, eight new 2-azetidinone analogs (4a-4h) of ezetimibe were designed through in silico docking experiments with the crystal structure of the Niemann-Pick C1-like 1 protein (NPC1L1). Synthesis and further antihyperlipdemic evaluation of this series in the Triton WR 1339 induced hyperlipidemic rat model showed some of the molecules to exhibit significant lipid-lowering effects comparable to ezetimibe. Correlation between the observed biological activity and the in silico molecular docking scores of the compounds was observed.

Molecular Docking Studies Involving Transitional Metal Complexes (Zn(II), Co(II), Cu(II), Fe(II), Ni(II) with Cholic Acid (AC) as Ligand against Aurora A Kinase

Colorectal cancer is a malignant tumor, one of the main types of cancer which produces a large number of deaths each year in many countries around the world. The main objective of this work is to employ various bioinformatics tools to perform docking of the transitional metal complexes (Zn (II), Co (II), Cu (II), Fe (II), Ni (II)) with cholic acid (AC) as ligand against Aurora A Kinase (RCSB Protein Data Bank code: 2X6E). Molegro Virtual Docker (MVD) was used for the docking process. The molecular docking score and the values of the statistic parameter Root Mean Square Deviation (RMSD) are presented in Table 1. The results obtained in this study serve to design new complex combinations with potential action against Aurora A Kinase inhibitor.

Optimization of molecular docking scores with support vector rank regression

This work introduces the support vector rank regression (SVRR) algorithm for the optimization of molecular docking scores. Seven original docking scores reported by two docking software were integrated by the SVRR algorithm. The resulting SVRR scores showed an average of 12.1% improvement (59.5-66.7%) in binding conformation prediction tests to rank the correctly computed conformation in the first place, along with 16.7% RMSD improvement (2.5414 vs. 2.1162 Å) for the top ranked conformations. In compound library screening (LS) tests, an average of 46.3% improvement (18.2-26.6%) was also observed to rank the correct ligand in the first place. Furthermore, it was shown that SVRR scores trained with different example datasets, using different training strategies, all exhibited exceedingly consistent accuracies, suggesting that the SVRR algorithm is highly robust and generalizable. In contrast, using the same training datasets, traditional support vector classification and regression algorithms failed to improve comparably the accuracy of LS and conformation prediction. These results suggested that, with additional features to indicate the comparative fitness between computed binding conformations, the SVRR algorithm holds the potential to create a new category of more accurate integrative docking scores.

A Drug-Target Network-Based Approach to Evaluate the Efficacy of Medicinal Plants for Type II Diabetes Mellitus.

The use of plants as natural medicines in the treatment of type II diabetes mellitus (T2DM) has long been of special interest. In this work, we developed a docking score-weighted prediction model based on drug-target network to evaluate the efficacy of medicinal plants for T2DM. High throughput virtual screening from chemical library of natural products was adopted to calculate the binding affinity between natural products contained in medicinal plants and 33 T2DM-related proteins. The drug-target network was constructed according to the strength of the binding affinity if the molecular docking score satisfied the threshold. By linking the medicinal plant with T2DM through drug-target network, the model can predict the efficacy of natural products and medicinal plant for T2DM. Eighteen thousand nine hundred ninety-nine natural products and 1669 medicinal plants were predicted to be potentially bioactive.

A Network-Based Multi-Target Computational Estimation Scheme for Anticoagulant Activities of Compounds

BackgroundTraditional virtual screening method pays more attention on predicted binding affinity between drug molecule and target related to a certain disease instead of phenotypic data of drug molecule against disease system, as is often less effective on discovery of the drug which is used to treat many types of complex diseases. Virtual screening against a complex disease by general network estimation has become feasible with the development of network biology and system biology. More effective methods of computational estimation for the whole efficacy of a compound in a complex disease system are needed, given the distinct weightiness of the different target in a biological process and the standpoint that partial inhibition of several targets can be more efficient than the complete inhibition of a single target.MethodologyWe developed a novel approach by integrating the affinity predictions from multi-target docking studies with biological network efficiency analysis to estimate the anticoagulant activities of compounds. From results of network efficiency calculation for human clotting cascade, factor Xa and thrombin were identified as the two most fragile enzymes, while the catalytic reaction mediated by complex IXa:VIIIa and the formation of the complex VIIIa:IXa were recognized as the two most fragile biological matter in the human clotting cascade system. Furthermore, the method which combined network efficiency with molecular docking scores was applied to estimate the anticoagulant activities of a serial of argatroban intermediates and eight natural products respectively. The better correlation (r = 0.671) between the experimental data and the decrease of the network deficiency suggests that the approach could be a promising computational systems biology tool to aid identification of anticoagulant activities of compounds in drug discovery.ConclusionsThis article proposes a network-based multi-target computational estimation method for anticoagulant activities of compounds by combining network efficiency analysis with scoring function from molecular docking.

Whole blood viscosity extrapolation formula: Note on appropriateness of units

Background:A series has recently been done on whole blood viscosity. The first on the series proposed extrapolation chart with conventional reference range. Since the publication, two concerns have been received in personal communications. The first expressed concern over the use of serum proteins values in ‘g/L’ instead of ‘g/dL’ that was contained in the referenced material. The second enquired on suitability of the formula for determination of blood viscosity at low shear rate.Aim:This work sets out to compare different units-converted-modifications of the extrapolation with a view to develop a statement of comparison and suitability of units.Materials and Methods:The values of haematocrit and serum proteins were used in different unit-conversions on the mathematical formula to derive four modifications, which were compared. Five clinical cases that were specifically tested for whole blood viscosity, and had results for haematocrit and serum proteins were evaluated. The appropriateness of modifications for determination of viscosity at low shear rate was reviewed.Results:Except as modified and used in the series, determination of whole blood viscosity at low shear rate using other unit conversions on the formula yields negative values for all five cases.Conclusion:Given that it is unexpected for blood viscosity level to be zero let alone less, it is logical that negative values are invalid. A formula that gives the least invalid results may be most appropriate. Therefore, extrapolation modification used in the series is most appropriate.

Drug efficiency indices for improvement of molecular docking scoring functions

A dataset of protein-drug complexes with experimental binding energy and crystal structure were analyzed and the performance of different docking engines and scoring functions (as well as components of these) for predicting the free energy of binding and several ligand efficiency indices were compared. The aim was not to evaluate the best docking method, but to determine the effect of different efficiency indices on the experimental and predicted free energy. Some ligand efficiency indices, such as DeltaG/W (Wiener index), DeltaG/NoC (number of carbons), and DeltaG/P (partition coefficient), improve the correlation between experimental and calculated values. This effect was shown to be valid across the different scoring functions and docking programs. It also removes the common bias of scoring functions in favor of larger ligands. For all scoring functions, the efficiency indices effectively normalize the free energy derived indices, to give values closer to experiment. Compound collection filtering can be done prior or after docking, using pharmacokinetic as well as pharmacodynamic profiles. Achieving these better correlations with experiment can improve the ability of docking scoring functions to predict active molecules in virtual screening.

3D-QSAR studies of Checkpoint Kinase Weel inhibitors based on molecular docking, CoMFA and CoMSIA

Three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were performed on 97 4-phenylpyrrolo[3,4-c]carbazole-1,3(2 H,6 H)-dione inhibitors, based on molecular docking scores obtained by using GOLD 3.1, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices (CoMSIA). The docking results provided a reliable conformational alignment scheme for the 3D-QSAR model. Based on the docking conformations and alignments, highly predictive CoMFA and CoMSIA were obtained with cross-validated q 2 value of 0.828 and 0.796, respectively, and non-cross-validated partial least-squares (PLS) analysis with the optimum components of five showed a conventional r 2 of 0.962 and 0.949, respectively. The predictive ability was validated by compounds that were not included in the training set. Furthermore, the CoMFA and CoMSIA model plots were mapped back to the binding sites of Checkpoint Kinase Weel, to get a better understanding of vital interactions between the inhibitors and Weel kinase. As a result, we have identified some key features in the 4-phenylpyrrolo[3,4-c]carbazole-1,3(2 H,6 H)-diones responsible for the Weel inhibitory activity that may be used to design more potent 4-phenylpyrrolo[3,4-c]carbazole-1,3(2 H,6 H)-diones and predict their activity prior to synthesis.

3D QSAR studies of AChE inhibitors based on molecular docking scores and CoMFA

Three-dimensional quantitative structure–activity relationship (3D QSAR) studies were performed on acetylcholinesterase (AChE) inhibitors, based on molecular docking scores obtained by using FlexX and FlexiDock and comparative molecular field analysis (CoMFA). The docking scores were used as molecular descriptors along with the steric and electrostatic field values of CoMFA, for partial least square (PLS) analysis. The high leave one out (LOO) cross-validated correlation coefficient ( q 2 = 0.714) reveals that the model is a useful tool for the prediction of test set as well as newly designed structures against AChE activity. The superimposed CoMFA models on the receptor site of AChE are guiding the design of potential inhibitory structures directed against AChE activity.

Accurate Prediction of the Relative Potencies of Members of a Series of Kinase Inhibitors Using Molecular Docking and MM-GBSA Scoring

The ability of molecular docking, using the program Glide and an MM-GBSA postdocking scoring protocol, to correctly rank a number of congeneric kinase inhibitors was assessed. The approach was successful for the cases considered and suggests that this may be useful for the design of inhibitors in the lead optimization phase of drug discovery.