Pharmacophore modeling and in silico screening for new KDR kinase inhibitors

In order to elucidate the essential structural features for KDR kinase inhibitors, three-dimensional pharmacophore hypotheses were built on the basis of a set of known KDR kinase inhibitors selected from the literature with CATALYST program. Several methods tools used in validation of pharmacophore hypothsis were presented, and the first hypothesis (Hypo1) was considered to be the best pharmacophore hypothesis. The model (Hypo1) was then employed as 3D search query to screen the Traditional Chinese Medicine Database (TCMD) for other potential lead compounds. One hit illustrated high binding affinity with KDR kinase measured by the surface plasmon resonance biosensor. Docking studies may help elucidate the mechanisms of KDR kinase receptor-ligand interactions.     

Pharmacophore modeling and virtual screening studies to identify new c-Met inhibitors

Mesenchymal epithelial transition factor (c-Met) is an attractive target for cancer therapy. Three-dimensional pharmacophore hypotheses were built based on a set of known structurally diverse c-Met inhibitors. The best pharmacophore model, which identified inhibitors with an associated correlation coefficient of 0.983 between their experimental and estimated IC(50) values, consisted of two hydrogen-bond acceptors, one hydrophobic, and one ring aromatic feature. The highly predictive power of the model was rigorously validated by test set prediction and Fischer's randomization method. The high values of enrichment factor and receiver operating characteristic (ROC) score indicated the model performed fairly well at distinguishing active from inactive compounds. The model was then applied to screen compound database for potential c-Met inhibitors. A filtering protocol, including druggability and molecular docking, were also applied in hits selection. The final 38 molecules, which exhibited good estimated activities, desired binding mode and favorable drug likeness were identified as potential c-Met inhibitors. Their novel backbone structures could be served as scaffolds for further study, which may facilitate the discovery and rational design of potent c-Met kinase inhibitors.     

Comparative modeling and virtual screening for the identification of novel inhibitors for myo-inositol-1-phosphate synthase

Myo-inositol-1-phosphate (MIP) synthase is a key enzyme in the myo-inositol biosynthesis pathway. Disruption of the inositol signaling pathway is associated with bipolar disorders. Previous work suggested that MIP synthase could be an attractive target for the development of anti-bipolar drugs. Inhibition of this enzyme could possibly help in reducing the risk of a disease in patients. With this objective, three dimensional structure of the protein was modeled followed by the active site prediction. For the first time, computational studies were carried out to obtain structural insights into the interactive behavior of this enzyme with ligands. Virtual screening was carried out using FILTER, ROCS and EON modules of the OpenEye scientific software. Natural products from the ZINC database were used for the screening process. Resulting compounds were docked into active site of the target protein using FRED (Fast Rigid Exhaustive Docking) and GOLD (Genetic Optimization for Ligand Docking) docking programs. The analysis indicated extensive hydrogen bonding network and hydrophobic interactions which play a significant role in ligand binding. Four compounds are shortlisted and their binding assay analysis is underway.     

3D-QSAR based pharmacophore modeling and virtual screening for identification of novel pteridine reductase inhibitors

Pteridine reductase is a promising target for development of novel therapeutic agents against Trypanosomatid parasites. A 3D-QSAR pharmacophore hypothesis has been generated for a series of L. major pteridine reductase inhibitors using Catalyst/HypoGen algorithm for identification of the chemical features that are responsible for the inhibitory activity. Four pharmacophore features, namely: two H-bond donors (D), one Hydrophobic aromatic (H) and one Ring aromatic (R) have been identified as key features involved in inhibitor-PTR1 interaction. These features are able to predict the activity of external test set of pteridine reductase inhibitors with a correlation coefficient (r) of 0.80. Based on the analysis of the best hypotheses, some potent Pteridine reductase inhibitors were screened out and predicted with anti-PTR1 activity. It turned out that the newly identified inhibitory molecules are at least 300 fold more potent than the current crop of existing inhibitors. Overall the current SAR study is an effort for elucidating quantitative structure-activity relationship for the PTR1 inhibitors. The results from the combined 3D-QSAR modeling and molecular docking approach have led to the prediction of new potent inhibitory scaffolds.     

Pharmacophore modeling and virtual screening to identify potential RET kinase inhibitors

Chemical features based 3D pharmacophore model for REarranged during Transfection (RET) tyrosine kinase were developed by using a training set of 26 structurally diverse known RET inhibitors. The best pharmacophore hypothesis, which identified inhibitors with an associated correlation coefficient of 0.90 between their experimental and estimated anti-RET values, contained one hydrogen-bond acceptor, one hydrogen-bond donor, one hydrophobic, and one ring aromatic features. The model was further validated by a testing set, Fischer’s randomization test, and goodness of hit (GH) test. We applied this pharmacophore model to screen NCI database for potential RET inhibitors. The hits were docked to RET with GOLD and CDOCKER after filtering by Lipinski’s rules. Ultimately, 24 molecules were selected as potential RET inhibitors for further investigation.     

Pharmacophore modeling and virtual screening for designing potential PLK1 inhibitors

Pharmacophore models of Polo-like kinase-1 (PLK1) inhibitors have been established by using the HipHop and HypoGen algorithms implemented in the Catalyst software package. The best quantitative pharmacophore model, Hypo1, which has the highest correlation coefficient (0.9895), consists of one hydrogen bond acceptor, one hydrogen bond donor, one hydrophobic feature, and one hydrophobic aliphatic feature. Hypo1 was further validated by test set and cross validation method. Then Hypo1 was used as a 3D query to screen several databases including Specs, NCI, Maybridge, and Chinese Nature Product Database (CNPD). The hit compounds were subsequently subjected to filtering by Lipinski's rule of five and docking study to refine the retrieved hits and as a result to reduce the rate of false positive. Finally, a total of 20 compounds were selected and have been shifted to in vitro and in vivo studies. As far as we know, this is the first report on the pharmacophore modeling even the first publicly reported virtual screening study of PLK1 inhibitors.     

Pharmacophore modeling and virtual screening for designing potential 5-Lipoxygenase inhibitors

Inhibitors of the 5-Lipoxygenase (5-LOX) pathway have a therapeutic potential in a variety of inflammatory disorders such as asthma. In this study, chemical feature based pharmacophore models of inhibitors of 5-LOX have been developed with the aid of HipHop and HypoGen modules within Catalyst program package. The best quantitative pharmacophore model, Hypo1, which has the highest correlation coefficient (0.97), consists of two hydrogen-bond acceptors, one hydrophobic feature and one ring aromatic feature. Hypo1 was further validated by test set and cross validation method. The application of the model shows great success in predicting the activities of 65 known 5-LOX inhibitors in our test set with a correlation coefficient of 0.85 with a cross validation of 95% confidence level, proving that the model is reliable in identifying structurally diverse compounds for inhibitory activity against 5-LOX. Furthermore, Hypo1 was used as a 3D query for screening Maybridge and NCI databases within catalyst and also drug like compounds obtained from Enamine Ltd, which follow Lipinski’s rule of five. The hit compounds were subsequently subjected to filtering by docking and visualization, to identify the potential lead molecules. Finally 5 potential lead compounds, identified in the above process, were evaluated for their inhibitory activities. These studies resulted in the identification of two compounds with potent inhibition of 5-LOX activity with IC₅₀ of 14 μM and 35 μM, respectively. These studies thus validate the pharmacophore model generated and suggest the usefulness of the model in screening of various small molecule libraries and identification of potential lead compounds for 5-LOX inhibition.     

Molecular modeling,in silico screening and molecular dynamics of PfPRL-PTP of P. falciparum for identification of potential anti-malarials

Millions of deaths occur every year due to malaria. Growing resistance against existing drugs for treatment of malaria has exaggerated the problem further. There is an intense demand of identifying drug targets in malaria parasite. PfPRL-PTP protein is PRL group of phosphatase, and one of the interesting drug targets being involved in three important pathways of malaria parasite (secretion, phosphorylation, and prenylation). Therefore, in this study, we have modeled three-dimensional structure of PfPRL-PTP followed by validation of 3D structure using RAMPAGE, verify3D, and other structure validation tools. We could identify 12 potential inhibitory compounds using in silico screening of NCI library against PfPRL-PTP with Glide. The molecular dynamics simulation was also performed using GROMACS on PfPRL-PTP model alone and PfPRL-PTP-inhibitor complex. This study of identifying potential drug-like molecules would add up to the process of drug discovery against malaria parasite.     

Homology modeling,docking and structure-based virtual screening for new inhibitor identification of Klebsiella pneumoniae heptosyltransferase-III

Abstract

Klebsiella pneumoniae (K. pneumoniae) is a Gram-negative opportunistic pathogen commonly associated with hospital-acquired infections that are often resistant even to antibiotics. Heptosyltransferase (HEP) belongs to the family of glycosyltransferase-B (GT-B) and plays an important in the synthesis of lipopolysaccharides (LPS) essential for the formation of bacterial cell membrane. HEP-III participates in the transfer of heptose sugar to the outer surface of bacteria to synthesize LPS. LPS truncation increases the bacterial sensitivity to hydrophobic antibiotics and detergents, making the HEP as a novel drug target. In the present study, we report the 3D homology model of K. pneumoniae HEP-III and its structure validation. Active site was identified based on similarities with known structures using Dali server, and structure-based pharmacophore model was developed for the active site substrate ADP. The generated pharmacophore model was used as a 3D search query for virtual screening of the ASINEX database. The hit compounds were further filtered based on fit value, molecular docking, docking scores, molecular dynamics (MD) simulations of HEP-III complexed with hit molecules, followed by binding free energy calculations using Molecular Mechanics-Poisson–Boltzmann Surface Area (MM-PBSA). The insights obtained in this work provide the rationale for design of novel inhibitors targeting K. pneumoniae HEP-III and the mechanistic aspects of their binding.

Communicated by Ramaswamy H. Sarma     

Molecular modeling of drug-DNA interactions: virtual screening to structure-based design

Virtual ligand screening (VLS) and structure-based design are strategies that have been routinely used for the development of pharmaceuticals, particularly those targeting enzymes and other protein targets. In recent years, an increased understanding of the role played by nucleic acids in biological systems made DNA an alternative candidate for the development of new drugs. This review highlights some successful applications of molecular modeling in virtual ligand screening and structure-based design of organic and inorganic molecules that target non-canonical nucleic acid structures such as G-quadruplex and triplex DNA.     

Discovery of dual binding site acetylcholinesterase inhibitors identified by pharmacophore modeling and sequential virtual screening techniques

Dual binding site acetylcholinesterase (AChE) inhibitors are promising for the treatment of Alzheimer’s disease (AD). They alleviate the cognitive deficits and AD-modifying agents, by inhibiting the β-amyloid (Aβ) peptide aggregation, through binding to both the catalytic and peripheral anionic sites, the so called dual binding site of the AChE enzyme. In this Letter, chemical features based 3D-pharmacophore models were developed based on the eight potent and structurally diverse AChE inhibitors (I-VIII) obtained from high-throughput in vitro screening technique. The best 3D-pharmacophore model, Hypo1, consists of two hydrogen-bond acceptor lipid, one hydrophobe, and two hydrophobic aliphatic features obtained by Catalyst/HIPHOP algorithm adopted in Discovery studio program. Hypo1 was used as a 3D query in sequential virtual screening study to filter three small compound databases. Further, a total of nine compounds were selected and followed on in vitro analysis. Finally, we identified two leads—Specs1 (IC₅₀ = 3.279 μM) and Spec2 (IC₅₀ = 5.986 μM) dual binding site compounds from Specs database, having good AChE enzyme inhibitory activity.     

Identification of novel, less toxic PTP-LAR inhibitors using in silico strategies: pharmacophore modeling, SADMET-based virtual screening and docking

Human leukocyte antigen-related (PTP-LAR) is a receptor-like transmembrane phosphatase and a potential target for diabetes, obesity and cancer. In the present study, a sequence of in silico strategies (pharmacophore mapping, a 3D database searching, SADMET screening, and docking and toxicity studies) was performed to identify eight novel nontoxic PTP-LAR inhibitors. Twenty different pharmacophore hypotheses were generated using two methods; the best (hypothesis 2) consisted of three hydrogen-bond acceptor (A), one ring aromatic (R), and one hydrophobic aliphatic (Z) features. This hypothesis was used to screen molecules from several databases, such as Specs, IBS, MiniMaybridge, NCI, and an in-house PTP inhibitor database. In order to overcome the general bioavailability problem associated with phosphatases, the hits obtained were filtered by Lipinski’s rule of five and SADMET properties and validated by molecular docking studies using the available crystal structure 1LAR. These docking studies suggested the ligand binding pattern and interactions required for LAR inhibition. The docking analysis also revealed that sulfonylurea derivatives with an isoquinoline or naphthalene scaffold represent potential LAR drugs. The screening protocol was further validated using ligand pharmacophore mapping studies, which showed that the abovementioned interactions are indeed crucial and that the screened molecules can be presumed to possess potent inhibitory activities.     

Spectroscopic and molecular modeling approaches to investigate the binding of proton pump inhibitors to human serum albumin

The interaction between two proton pump inhibitors viz., omeprazole (OME) and esomeprazole (EPZ) with human serum albumin (HSA) was studied by fluorescence, absorption, circular dichroism (CD), Fourier transform infrared spectroscopy (FT-IR), voltammetry, and molecular modeling approaches. The Stern–Volmer quenching constants (K_sv) for OME-HSA and EPZ-HSA systems obtained at different temperatures revealed that both OME and EPZ quenched the intensity of HSA through dynamic mode of quenching mechanism. The binding constants of OME-HSA and EPZ-HSA increased with temperature, indicating the increased stability of these systems at higher temperatures. Thermodynamic parameters viz., ?H^°, ?S^°, and ?G^° were determined for both systems. These values revealed that both systems were stabilized by hydrophobic forces. The competitive displacement and molecular docking studies suggested that OME/EPZ was bound to Sudlow’s site I in subdomain IIA in HSA. The extent of energy transfer from HSA to OME/EPZ and the distance of separation in tryptophan (Trp214) Trp214-OME and Trp214-EPZ was determined based on the theory of fluorescence resonance energy transfer. UV absorption, 3D fluorescence, and CD studies indicated that the binding of OME/EPZ to HSA has induced micro environmental changes around the protein which resulted changes in its secondary structure.     

3D QSAR pharmacophore-based virtual screening for the identification of potential inhibitors of tyrosinase

Abstract

Tyrosinase plays an important role in melanin biosynthesis and protects skin against ultraviolet radiations. Functional deficiency of tyrosinase results in serious dermatological diseases. Tyrosinase also participates in neuromelanin formation in the human brain, which leads to neurodegeneration resulting in Parkinson’s disease. In fruits and vegetables, tyrosinase plays a critical role in senescence, causing undesired browning that results in faster deterioration and shorter shelf lines. The only commercially available tyrosinase is mushroom tyrosinase and it shows the highest homology to the mammalian tyrosinase. Although kojic acid is currently used as a tyrosinase inhibitor, they have serious side effects such as dermatitis, carcinogenesis and hepatotoxicity. Therefore, in order to develop a more active and safer tyrosinase inhibitor, 3D QSAR pharmacophore models were generated based on experimentally known inhibitors. The pharmacophore model, Hypo1, was developed with a large cost difference, high correlation coefficient and low RMS deviation. Hypo1 showed a good spatial arrangement; consisting of five-point features including two hydrogen bond acceptor, one hydrogen bond donor and two hydrophobic features. Hypo1 was further validated by cost analysis, test set and Fisher’s randomisation method. Hypo1 was used as a 3D query for screening the in-house drug-like databases, and the hits were further selected by applying ADMET, Lipinski’s rule of five and fit value criteria. To identify binding conformations, the obtained hits were subjected to molecular docking. Finally, molecular dynamics simulations revealed the appropriate binding modes of hit compounds. To conclude, we propose the final three hit compounds with new structural scaffolds as a virtual candidate as tyrosinase inhibitors.

Communicated by Ramaswamy H. Sarma     

Discovery of potent inhibitors of pseudomonal quorum sensing via pharmacophore modeling and in silico screening

HipHop-Refine was employed to derive a binding hypothesis for pseudomonal quorum sensing (QS) antagonists. The model was employed as 3D search query to screen the National Cancer Institute (NCI) database. One of the hits illustrated nanomolar QS inhibitory activity. The fact that this compound contained tetravalent lead (Pb) prompted us to evaluate the activities of phenyl mercuric nitrate and thimerosal, both fit the binding pharmacophore. The two mercurials illustrated nanomolar to low micromolar IC50 inhibitory values against pseudomonal QS. The three compounds represent a new class of QS inhibitors.     

Pharmacophore modeling and structure-based virtual screening to identify potent inhibitors targeting LuxP of Vibrio harveyi

The main aim of the study is to identify molecules that can disrupt quorum sensing (QS) system of Vibrio harveyi and therefore perhaps the production of toxins. Recently, a novel class of dioxazaborocane derivatives has been found to block AI-2 QS by targeting LuxPQ, but the mechanism of protein inhibition is still unclear. In order to investigate the possible binding modes, all the derivatives were docked into the binding site of LuxP using induced fit docking (IFD). The computed binding affinity is in good agreement with the experimental data. Resultant protein–ligand complexes were simulated using Desmond module and the result revealed better binding of ligands in the binding site of LuxP. Both pharmacophore- and structure-based virtual screening was performed to identify novel hits against LuxP. A filtering protocol, including lipinski filters, number of rotatable bonds and three levels of docking precisions were used for the selection of hits with specific properties. The virtual screening results were then combined and analyzed, which retrieved six hits with significant Glide score, binding affinity toward LuxP. The pharmacokinetic properties of the retrieved hits are in the acceptable range. Enrichment calculation was performed to validate the final hits, to discriminate the active compounds from the inactive compounds. The identified hits could serve as a base for further drug development against LuxP of Vibrio harveyi.     

Large-scale virtual screening for the identification of new Helicobacter pylori urease inhibitor scaffolds

Here, we report a structure-based virtual screening of the ZINC database (containing about five million compounds) by computational docking and the analysis of docking energy calculations followed by in vitro screening against H. pylori urease enzyme. One of the compounds selected showed urease inhibition in the low micromolar range. Barbituric acid and compounds 1a, 1d, 1e, 1f, 1g, 1h were found to be more potent urease inhibitors than the standard inhibitor hydroxyurea, yielding IC(50) values of 41.6, 83.3, 66.6, 50, 58.8, and 60 μM, respectively (IC(50) of hydroxyurea = 100 μM). 5-Benzylidene barbituric acid has enhanced biological activities compared to barbituric acid. Furthermore, the results indicated that among the substituted 5-benzylidene barbiturates, those with para substitution have higher urease inhibitor activities. This may be because the barbituric acid moiety is closer to the bimetallic nickel center in unsubstituted or para-substituted than in ortho- or meta-substituted analogs, so it has greater chelating ability.     

Discovery of Entamoeba histolytica hexokinase 1 inhibitors through homology modeling and virtual screening

Abstract

Entamoeba histolytica, the parasite which causes amebiasis is responsible for 110?000 deaths a year. Entamoeba histolytica depends on glycolysis to obtain ATP for cellular work. According to metabolic flux studies, hexokinase exerts the highest flux control of this metabolic pathway; therefore, it is an excellent target in the search of new antiamebic drugs. To this end, a tridimensional model of E. histolytica hexokinase 1 (EhHK1) was constructed and validated by homology modeling. After virtual screening of 14?400 small molecules, the 100 with the best docking scores were selected, purchased and assessed in their inhibitory capacity. The results showed that three molecules (compounds 2921, 11275 and 2755) inhibited EhHK1 with an I₅₀ of 48, 91 and 96?µM, respectively. Thus, we found the first inhibitors of EhHK1 that can be used in the search of new chemotherapeutic agents against amebiasis.     

Ligand-based pharmacophore mapping and virtual screening for identification of potential discoidin domain receptor 1 inhibitors

Abbreviations ADME absorption, distribution, metabolism, and excretion

MMGB/SA molecular mechanics generalized born surface area

IFD induced fit docking

RTK receptor tyrosine kinase

NSCLC non-small-cell lung cancer

ATP adenosine triphosphate

OPLS optimized potential for liquid stimulation

RMSD root mean square deviation

HTVS high-throughput virtual screening

SP standard precision

XP extra precision

OPLS-AA optimized potential for liquid stimulation-all atom

MD molecular simulation

MME molecular mechanics energies

SGB surface generalized born

POPC membrane 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine membrane

PDB Protein Data Bank

DDR1 discoidin domain receptor 1

DDR2 discoidin domain receptor 2

DDRs discoidin domain receptors

ECM extracellular matrix

TIP4P transferable intermolecular potential 4 point

NPT constant particle number, pressure and temperature

RMSF root mean square fluctuation

Communicated by Ramaswamy H. Sarma