Gugan Kothandan

Docking and 3D-QSAR (quantitative structure activity relationship) studies of flavones, the potent inhibitors of p-glycoprotein targeting the nucleotide binding domain

In order to explore the interactions between flavones and P-gp, in silico methodologies such as docking and 3D-QSAR were performed. CoMFA and CoMSIA analyses were done using ligand based and receptor guided alignment schemes. Validation statistics include leave-one-out cross-validated R(2) (q(2)), internal prediction parameter by progressive scrambling (Q(*2)), external prediction with test set. They show that models derived from this study are quite robust. Ligand based CoMFA (q(2) = 0.747, Q(*2) = 0.639, r(pred)(2)=0.802) and CoMSIA model (q(2) = 0.810, Q(*2) = 0.676, r(pred)(2)=0.785) were developed using atom by atom matching. Receptor guided CoMFA (q(2) = 0.712, Q(*2) = 0.497, r(pred)(2) = 0.841) and for CoMSIA (q(2) = 0.805, Q(*2) = 0.589, r(pred)(2) = 0.937) models were developed by docking of highly active flavone into the proposed NBD (nucleotide binding domain) of P-gp. The 3D-QSAR models generated here predicted that hydrophobic and steric parameters are important for activity toward P-gp. Our studies indicate the important amino acid in NBD crucial for binding in accordance with the previous results. This site forms a hydrophobic site. Since flavonoids have potential without toxicity, we propose to inspect this hydrophobic site including Asn1043 and Asp1049 should be considered for future inhibitor design.

Structural insights from binding poses of CCR2 and CCR5 with clinically important antagonists: a combined in silico study.

Chemokine receptors are G protein-coupled receptors that contain seven transmembrane domains. In particular, CCR2 and CCR5 and their ligands have been implicated in the pathophysiology of a number of diseases, including rheumatoid arthritis and multiple sclerosis. Based on their roles in disease, they have been attractive targets for the pharmaceutical industry, and furthermore, targeting both CCR2 and CCR5 can be a useful strategy. Owing to the importance of these receptors, information regarding the binding site is of prime importance. Structural studies have been hampered due to the lack of X-ray crystal structures, and templates with close homologs for comparative modeling. Most of the previous models were based on the bovine rhodopsin and β2-adrenergic receptor. In this study, based on a closer homolog with higher resolution (CXCR4, PDB code: 3ODU 2.5 Å), we constructed three-dimensional models. The main aim of this study was to provide relevant information on binding sites of these receptors. Molecular dynamics simulation was done to refine the homology models and PROCHECK results indicated that the models were reasonable. Here, binding poses were checked with some established inhibitors of high pharmaceutical importance against the modeled receptors. Analysis of interaction modes gave an integrated interpretation with detailed structural information. The binding poses confirmed that the acidic residues Glu291 (CCR2) and Glu283 (CCR5) are important, and we also found some additional residues. Comparisons of binding sites of CCR2/CCR5 were done sequentially and also by docking a potent dual antagonist. Our results can be a starting point for further structure-based drug design.

Magnolol Inhibits LPS-induced NF-κB/Rel Activation by Blocking p38 Kinase in Murine Macrophages.

This study demonstrates the ability of magnolol, a hydroxylated biphenyl compound isolated from Magnolia officinalis, to inhibit LPS-induced expression of iNOS gene and activation of NF-κB/Rel in RAW 264.7 cells. Immunohisto-chemical staining of iNOS and Western blot analysis showed magnolol to inhibit iNOS gene expression. Reporter gene assay and electrophoretic mobility shift assay showed that magnolol inhibited NF-κB/Rel transcriptional activation and DNA binding, respectively. Since p38 is important in the regulation of iNOS gene expression, we investigated the possibility that magnolol to target p38 for its anti-inflammatory effects. A molecular modeling study proposed a binding position for magnolol that targets the ATP binding site of p38 kinase (3GC7). Direct interaction of magnolol and p38 was further confirmed by pull down assay using magnolol conjugated to Sepharose 4B beads. The specific p38 inhibitor SB203580 abrogated the LPS-induced NF-κB/Rel activation, whereas the selective MEK-1 inhibitor PD98059 did not affect the NF-κB/Rel. Collectively, the results of the series of experiments indicate that magnolol inhibits iNOS gene expression by blocking NF-κB/Rel and p38 kinase signaling.

Binding Site Analysis of CCR2 Through In Silico Methodologies: Docking, CoMFA, and CoMSIA

Chemokine receptor (CCR2) is a G protein‐coupled receptor that contains seven transmembrane domains. CCR2 is targeted for diseases like arthritis, multiple sclerosis, vascular disease, obesity and type 2 diabetes. Herein, we report on a binding site analysis of CCR2 through docking and three‐dimensional quantitative structure–activity relationship (3D‐QSAR). The docking study was performed with modeled receptor (CCR2) using β2‐andrenergic receptor structure as a template. Comparative molecular field analysis (CoMFA)‐ and comparative molecular similarity indices analysis (CoMSIA)‐based 3D‐QSAR models were developed using two different schemes: ligand‐based (CoMFA; q2 = 0.820, r2 = 0.966,  = 0.854 and CoMSIA; q2 = 0.762, r2 = 0.846,  = 0.684) and receptor‐guided (CoMFA; q2 = 0.753, r2 = 0.962,  = 0.786, CoMSIA; q2 = 0.750, r2 = 0.800,  = 0.797) methods. 3D‐QSAR analysis revealed the contribution of electrostatic and hydrogen bond donor parameters to the inhibitory activity. Contour maps suggested that bulky substitutions on the para position of R1 substituted phenyl ring, electronegative and donor substitutions on meta (5′) and ortho (2′) position of R2 substituted phenyl ring were favorable for activity. The results correlate well with previous results and newly report additional residues that may be crucial in CCR2 antagonism.

Large variation in electrostatic contours upon addition of steric parameters and the effect of charge calculation schemes in CoMFA on mutagenicity of MX analogues

Partial atomic charge is a useful concept to describe physico-chemical properties of a molecule. For this, various schemes have been devised to get reasonable values. Mutagen X is an ideal set to test the effect of partial atomic charge variation. Therefore, we collected data from previous reports and studied various charge schemes. Our systematic study covers 26 charge calculation schemes along with a broad range of levels of theory. Charge calculation schemes include charges from charge equalisation, electrostatic potential fitting, molecular orbital and atomic polar tensor. Calculation levels span from empirical, semi-empirical, Hartree–Fock, density functional and Møller–Plesset 2. We also used two validation statistics for internal prediction. To observe the electrostatic effect accurately during comparative molecular field analysis (CoMFA) modelling, we first studied isolated electrostatic parameters to avoid interaction effect with steric parameters. The results clearly show that adding steric parameters does change statistical conclusions as well as CoMFA maps. Although there was a weak trend that quantum mechanical (QM)-derived charges gave better statistical values, it is not apparent statistically (alpha = 0.05). Particularly, Mülliken population analysis (MPA) did not produce better results. Therefore, when we excluded MPA schemes from QM calculation, the QM-derived charges were found to be significant, i.e. sophisticated charge schemes other than MPA with QM methods were found to be superior to simple empirical charge schemes. In addition, we demonstrated that in order to test charge schemes properly, excluding steric parameter is more important. This work exemplifies Occams theorem of parsimony. A simpler model is a better model.

Computational modeling of human coreceptor CCR5 antagonist as a HIV-1 entry inhibitor: using an integrated homology modeling, docking, and membrane molecular dynamics simulation analysis approach

Chemokine receptor 5 (CCR5) is an integral membrane protein that is utilized during human immunodeficiency virus type-1 entry into host cells. CCR5 is a G-protein coupled receptor that contains seven transmembrane (TM) helices. However, the crystal structure of CCR5 has not been reported. A homology model of CCR5 was developed based on the recently reported CXCR4 structure as template. Automated docking of the most potent (14), medium potent (37), and least potent (25) CCR5 antagonists was performed using the CCR5 model. To characterize the mechanism responsible for the interactions between ligands (14, 25, and 37) and CCR5, membrane molecular dynamic (MD) simulations were performed. The position and orientation of ligands (14, 25, and 37) were found to be changed after MD simulations, which demonstrated the ability of this technique to identify binding modes. Furthermore, at the end of simulation, it was found that residues identified by docking were changed and some new residues were introduced in the proximity of ligands. Our results are in line with the majority of previous mutational reports. These results show that hydrophobicity is the determining factor of CCR5 antagonism. In addition, salt bridging and hydrogen bond contacts between ligands (14, 25, and 37) and CCR5 are also crucial for inhibitory activity. The residues newly identified by MD simulation are Ser160, Phe166, Ser180, His181, and Trp190, and so far no site-directed mutagenesis studies have been reported. To determine the contributions made by these residues, additional mutational studies are suggested. We propose a general binding mode for these derivatives based on the MD simulation results of higher (14), medium (37), and lower (25) potent inhibitors. Interestingly, we found some trend for these inhibitors such as, salt bridge interaction between basic nitrogen of ligand and acidic Glu283 seemed necessary for inhibitory activity. Also, two aromatic pockets (pocket I – TM1-3 and pocket II – TM3-6) were linked by the central polar region in TM7, and the simulated inhibitors show important interactions with the Trp86, Tyr89, Tyr108, Phe112, Ile198, Tyr251, Leu255, and Gln280 and Glu283 residues. These results shed light on the usage of MD simulation to identify more stable, optimal binding modes of the inhibitors.

In silico study on indole derivatives as anti HIV-1 agents: a combined docking, molecular dynamics and 3D-QSAR study

The HIV-1 envelope glycoprotein gp120 plays a vital role in the entry of virus into the host cells and is a potential antiviral drug target. Recently, indole derivatives have been reported to inhibit HIV-1 through binding to gp120, and this prevents gp120 and CD4 interaction to inhibit the infectivity of HIV-1. In this work, molecular docking, molecular dynamics (MD) and three-dimensional quantitative structure–activity relationship studies were carried out. Molecular docking studies of the most active and the least active compounds were performed to identify important residues in the binding pocket. We refined the docked poses by MD simulations which resulted in conformational changes. After equilibration, the structure of the ligand and receptor complex was stable. Therefore, we just took the last snapshot as the representative binding pose for this study. This pose for the most active inhibitor was used as a template for receptor-based alignment which was subsequently used for comparative molecular field analysis. Resultant 3D contour maps suggested smaller substituents are desirable at the 7-position of indole ring to avoid steric interactions with Ser375, Phe382 and Tyr384 residues in the active site. These results can be exploited to develop potential leads and for structure-based drug design of novel HIV-1 inhibitors.

3D-QSAR studies of JNK1 inhibitors utilizing various alignment methods.

We report our three‐dimensional quantitative structure activity relationship (3D‐QSAR) studies of the series of anilinopyrimidine derivatives of JNK1 inhibitors. The comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were applied using different alignment methods. The ligand‐based atom‐by‐atom matching alignment has produced better values for CoMFA (q2 = 0.646 and r2 = 0.983), while in CoMSIA it has achieved only lower statistical values. The pharmacophore‐based model has produced (q2 = 0.568, r2 = 0.938) and (q2 = 0.670, r2 = 0.982) for CoMFA and CoMSIA models, respectively. As the model was based on the receptor‐guided alignment, all the compounds were optimized within the receptor, resulting in q2 = 0.605 and r2 = 0.944 for CoMFA, and q2 = 0.587 and r2 = 0.863 for CoMSIA. Molecular Dynamic simulation studies suggested that the generated models were consistent with the low‐energy protein ligand conformation. The CoMFA and CoMSIA contour maps indicated that the substitutions of the electropositive groups in the phenyl ring, and an addition of hydrophobic groups in the pyrimidine ring, are important to enhance the activity of this series. Moreover, the virtual screening analysis against NCI database yields potentials hits, and the results obtained would be useful to synthesize selective and highly potent c‐Jun N‐terminal kinase 1 analogs.

In silico quantitative structure-activity relationship studies on P-gp modulators of tetrahydroisoquinoline-ethyl-phenylamine series.

BackgroundMultidrug resistance (MDR) is a major obstacle in cancer chemotherapy. The drug efflux by a transport protein is the main reason for MDR. In humans, MDR mainly occurs when the ATP-binding cassette (ABC) family of proteins is overexpressed simultaneously. P-glycoprotein (P-gp) is most commonly associated with human MDR; it utilizes energy from adenosine triphosphate (ATP) to transport a number of substrates out of cells against concentration gradients. By the active transport of substrates against concentration gradients, intracellular concentrations of substrates are decreased. This leads to the cause of failure in cancer chemotherapy.ResultsHerein, we report Topomer CoMFA (Comparative Molecular Field Analysis) and HQSAR (Hologram Quantitative Structure Activity Relationship) models for third generation MDR modulators. The Topomer CoMFA model showed good correlation between the actual and predicted values for training set molecules. The developed model showed cross validated correlation coefficient (q2) = 0.536 and non-cross validated correlation coefficient (r2) = 0.975 with eight components. The best HQSAR model (q2 = 0.777, r2 = 0.956) with 5-8 atom counts was used to predict the activity of test set compounds. Both models were validated using test set compounds, and gave a good predictive values of 0.604 and 0.730.ConclusionsThe contour map near R1 indicates that substitution of a bulkier and polar group to the ortho position of the benzene ring enhances the inhibitory effect. This explains why compounds with a nitro group have good inhibitory potency. Molecular fragment analyses shed light on some essential structural and topological features of third generation MDR modulators. Fragments analysis showed that the presence of tertiary nitrogen, a central phenyl ring and an aromatic dimethoxy group contributed to the inhibitory effect. Based on contour map information and fragment information, five new molecules with variable R1 substituents were designed. The activity of these designed molecules was predicted by the Topomer CoMFA and HQSAR models. The novel compounds showed higher potency than existing compounds.

In Silico Study of Desmosdumotin as an Anticancer Agent: Homology Modeling, Docking and Molecular Dynamics Simulation Approach

P-glycoprotein (P-gp) is responsible for the multidrug resistance (MDR) and involved in the expulsion of xenobiotics out of cell. In this paper, homology modeling, docking and molecular dynamics simulation (MDS) was performed for the human P-gp desmosdumotin inhibitor. Docking study was carried out in the P-gp nucleotide binding domain 2 (NBD2). The desmosdumotin binding region occupied the ATP binding region (flavonoid binding region) with hydrophobic and hydrophilic interactions. Analysis of root mean square deviations (RMSDs) of active site residues indicated the binding site residues were stable throughout the simulation period. As shown in previous results with structurally similar flavonoid compounds, van der Waals and electrostatic interactions were found to be important factors for the desmosdumotin-NBD2 inhibition. Docking results suggest that desmosdumotin interacts with the NBD2 through both hydrogen bonds (Lys1076, Ser1077 and Thr1078) and hydrophobic interactions (Tyr1044, Val1052, Gly1073 and Cys1074). In addition, the involvement of other amino-acids was identified via MDS (Lys1076 and Ser1077 for hydrogen bonds and Tyr1044, Val1052, Gly1073, Cys1074 and Gly1075 for hydrophobic interactions). Thus, current preliminary model of interactions between desmosdumotin-NBD2 could be helpful to understand the in-depth inhibition mechanism of P-gp at NBD2 level and to design more potent inhibitors which could effectively overcome MDR of anticancer agents.