Identification of potent virtual leads to design novel PLK1 inhibitors: pharmacophore modelling,virtual screening and molecular docking studies

The aim of this study was to identify novel scaffolds and utilise them in designing potent PLK1 inhibitors. Three-dimensional pharmacophore models on the basis of chemical features were developed for PLK1 on the basis of the known inhibitors. The best pharmacophore model, Hypo 1, which has the highest correlation (0.96), the highest cost difference (75.7494), the lowest total cost and RMSD (75.7494, 0.5458), contains two hydrophobics, one ring aromatic and one hydrogen donor. Hypo 1 was validated by the test set, decoy set and the Fischer's randomisation method. Then it was used for chemical database virtual screening. The hit compounds were filtered by Lipinski's rule of five and absorption, distribution, metabolism, elimination and toxicity properties. Finally, 24 compounds with good estimated activity values were used for docking studies. These results will be used to develop new inhibitors of PLK1 as leads.     

Identification of novel urease inhibitors: pharmacophore modeling,virtual screening and molecular docking studies

Abstract

Pharmacophore modeling and atom-based three-dimensional quantitative structure–activity relationship (3D-QSAR) have been developed on N-acylglycino- and hippurohydroxamic acid derivatives, which are known potential inhibitors of urease. This is followed by virtual screening and ADMET (absorption, distribution, metabolism, excretion and toxicity) studies on a large library of known drugs in order to get lead molecules as Helicobacter pylori urease inhibitors. A suitable three-featured pharmacophore model comprising one H-bond acceptor and two H-bond donor features (ADD.10) has been found to be the best QSAR model. An external library of compounds (～3000 molecules), pre-filtered using Lipinski’s rule of five, has been further screened using the pharmacophore model ADD.10. By analyzing the fitness of the hits with respect to the pharmacophore model and their binding interaction inside the urease active site, four molecules have been predicted to be extremely good urease inhibitors. Two of these have significant potential and should be taken up for further drug-designing process.     

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.     

The discovery of potential acetylcholinesterase inhibitors: A combination of pharmacophore modeling,virtual screening,and molecular docking studies

Background  

Alzheimer's disease (AD) is the most common cause of dementia characterized by progressive cognitive impairment in the elderly people. The most dramatic abnormalities are those of the cholinergic system. Acetylcholinesterase (AChE) plays a key role in the regulation of the cholinergic system, and hence, inhibition of AChE has emerged as one of the most promising strategies for the treatment of AD.     

In silico studies on potential MCF-7 inhibitors: a combination of pharmacophore and 3D-QSAR modeling,virtual screening,molecular docking,and pharmacokinetic analysis

Gallic acid and its derivatives exhibit a diverse range of biological applications, including anti-cancer activity. In this work, a data-set of forty-six molecules containing the galloyl moiety, and known to show anticarcinogenic activity against the MCF-7 human cancer cell line, have been chosen for pharmacophore modeling and 3D-Quantitative Structure Activity Relationship (3D-QSAR) studies. A tree-based partitioning algorithm has been used to find common pharmacophore hypotheses. The QSAR model was generated for three, four, and five featured hypotheses with increasing PLS factors and analyzed. Results for five featured hypotheses with three acceptors and two aromatic rings were the best out of all the possible combinations. On analyzing the results, the most robust (R^2?=?.8990) hypothesis with a good predictive power (Q^2?=?.7049) was found to be AAARR.35. A good external validation (R² = .6109) was also obtained. In order to design new MCF-7 inhibitors, the QSAR model was further utilized in pharmacophore-based virtual screening of a large database. The predicted IC₅₀ values of the identified potential MCF-7 inhibitors were found to lie in the micromolar range. Molecular docking into the colchicine domain of tubulin was performed in order to examine one of the probable mechanisms. This revealed various interactions between the ligand and the active site protein residues. The present study is expected to provide an effective guide for methodical development of potent MCF-7 inhibitors.     

Combined pharmacophore modeling, 3D-QSAR and docking studies to identify novel HDAC inhibitors using drug repurposing

Abstract

Histone deacetylases (HDACs), a critical family of epigenetic enzymes, has emerged as a promising target for antitumor drugs. Here, we describe our protocol of virtual screening in identification of novel potential HDAC inhibitors through pharmacophore modeling, 3D-QSAR, molecular docking and molecular dynamics (MD) simulation. Considering the limitation of current virtual screening works, drug repurposing strategy was applied to discover druggable HDAC inhibitor. The ligand-based pharmacophore and 3D-QSAR models were established, and their reliability was validated by different methods. Then, the DrugBank database was screened, followed by molecular docking. MD simulation (100?ns) was performed to further study the stability of ligand binding modes. Finally, results indicated the hit DB03889 with high in silico inhibitory potency was suitable for further experimental analysis.

Communicated by Ramaswamy H. Sarma     

Identification of potential tumour-associated carbonic anhydrase isozyme IX inhibitors: atom-based 3D-QSAR modelling,pharmacophore-based virtual screening and molecular docking studies

Abstract

Tumour hypoxia results in dramatic changes in the gene expression, proliferation and survival of tumour cells. The tumour cells shift towards anaerobic glycolysis which results in change of pH in their microenvironment. In response to this stress, over expression of carbonic anhydrase IX (CA IX) genes is observed in many solid tumours. So, selective inhibition of CA IX can be a promising target for anti-cancer drugs. In this work in silico tools like atom-based 3D-QSAR modelling, pharmacophore-based virtual screening and molecular docking were used to identify potential CA IX inhibitors. Based on the training set used in the QSAR model, twenty pharmacophore models were generated. Out of these, HHHR_1, AHHR_1, DHHHR_1, AHHHR_1 model was used to screen a database of 1,50,000 compounds retrieved from ZINC 15 database. R² and Q² was 0.9864 and 0.8799, respectively, for the developed QSAR model. 163 compounds showed a phase screen score above 2.4 in which ZINC02260669 was the highest ranked (screen score, 2.852058) compound in all the four models. Built QSAR model was used to predict the activity of all these 163 compounds and ZINC72370966 showed the highest predicted activity with pKi value of 7.649. These compounds were docked against CA IX (human) protein (PDB ID 5FL6) and molecular docking results showed favourable binding interactions for the best ten identified hits. This work gives design insights and some potential scaffolds which can be developed as CA IX inhibitors.

Communicated by Ramaswamy H. Sarma     

Discovery of potential novel microsomal triglyceride transfer protein inhibitors via virtual screening of pharmacophore modelling and molecular docking

In order to identify potential natural inhibitors against the microsomal triglyceride transfer protein (MTP), HipHop models were generated using 20 known inhibitors from the Binding Database. Using evaluation indicators, the best hypothesis model, Hypo1, was selected and utilised to screen the Traditional Chinese Medicine Database, which resulted in a hit list of 58 drug-like compounds. A homology model of MTP was built by MODELLER and was minimised by CHARMm force field. It was then validated by Ramachandran plot and Verify-3D so as to obtain a stable structure, which was further used to refine the 58 hits using molecular docking studies. Then, five compounds with higher docking scores which satisfied the docking requirements were discovered. Among them, Ginkgetin and Dauricine were most likely to be candidates that exhibition inhibiting effect on MTP. The screening strategy in this study is relatively new to the discovery of MTP inhibitors in medicinal chemistry. Moreover, it is important to note that, lomitapide, an approved MTP inhibitor, fits well with Hypo1 as well as our homology model of MTP, which confirmed the rationality of our studies. The results indicated the applicability of molecular modeling for the discovery of potential natural MTP inhibitors from traditional Chinese herbs.     

Discovery of novel 5α-reductase type II inhibitors by pharmacophore modelling,virtual screening,molecular docking and molecular dynamics simulations

Benign prostatic hyperplasia (BPH) is caused by augmented levels of androgen dihydrotestosterone (DHT) which is involved in the growth of the prostate in humans. 5α-Reductase type II (5αR2) is an intracellular enzyme that catalyses the formation of DHT from testosterone; hence, the inhibition of 5αR2 has emerged as one of the most promising strategies for the treatment of BPH. In this study, a computational approach that integrates ligand-based pharmacophore modelling, virtual screening, molecular docking and molecular dynamics (MD) simulations was adopted to discover novel 5αR2 inhibitors with less side effects. After validating by Fischer's randomisation and Güner–Henry test, the best quantitative pharmacophore model (Hypo1), consisting of two hydrogen-bond acceptors and three hydrophobic features, was subsequently used as a three-dimensional-query in virtual screening to identify potential hits from Maybridge and National Cancer Institute databases. These hits were further filtered by ADMET (absorption, distribution, metabolism, elimination and toxicology) and molecular docking experiments, and their binding stabilities were validated by 10-ns MD simulations. Finally, only one hit was identified as a potential lead based on higher predicted inhibitory activity to 5αR2 compared with the most active inhibitor (finasteride). Our results further suggest that this potential lead could easily be synthesised and has structural novelty, making it a promising candidate for treating BPH.     

Identification of novel CDK2 inhibitors by a multistage virtual screening method based on SVM,pharmacophore and docking model

Abstract

Cyclin-dependent kinase 2 (CDK2) is the family of Ser/Thr protein kinases that has emerged as a highly selective with low toxic cancer therapy target. A multistage virtual screening method combined by SVM, protein-ligand interaction fingerprints (PLIF) pharmacophore and docking was utilised for screening the CDK2 inhibitors. The evaluation of the validation set indicated that this method can be used to screen large chemical databases because it has a high hit-rate and enrichment factor (80.1% and 332.83 respectively). Six compounds were screened out from NCI, Enamine and Pubchem database. After molecular dynamics and binding free energy calculation, two compounds had great potential as novel CDK2 inhibitors and they also showed selective inhibition against CDK2 in the kinase activity assay.     

Design,synthesis, docking studies and biological evaluation of novel chalcone derivatives as potential histone deacetylase inhibitors

A group of novel chalcone derivatives comprising hydroxamic acid or 2-aminobenzamide group as zinc binding groups (ZBG) were synthesized. The structure of the prepared compounds was fully characterized by IR, NMR and elemental microanalyses. Most of the tested compounds displayed strong to moderate HDAC inhibitory activity. Some of these compounds showed potent anti-proliferative activity against human HepG2, MCF-7 and HCT-116 cell lines. In particular, compounds 4a and 4b exhibited significant anti-proliferative activity against the three cell lines compared to SAHA as reference drug and displayed promising profile as anti-tumor candidates. The results indicated that these chalcone derivatives could serve as a promising lead compounds for further optimization as antitumor agents.     

Computational studies of COX-2 inhibitors: 3D-QSAR and docking

The 3D-QSAR (three-dimensional quantitative structure-activity relationships) studies for 88 selective COX-2 (cyclooxygenase-2) inhibitors belonging to three chemical classes (triaryl rings, diaryl cycloalkanopyrazoles, and diphenyl hydrazides) were conducted using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Partial least squares analysis produced statistically significant models with q(2) values of 0.84 and 0.79 for CoMFA and CoMSIA, respectively. The binding energies calculated from flexible docking were correlated with inhibitory activities by the least-squares fit method. The three chemical classes of inhibitors showed reasonable internal predictability (r(2)=0.51, 0.49, and 0.54), but the sulfonyl-containing inhibitors demonstrated distinctively low binding energy compared to the others. The electrostatic interaction energy between the Arg513 of the COX-2 active site and sulfonyl group of the triaryl rings seemed to have the responsibility for difference in binding energy. Comparative binding energy (COMBINE) analyses gave q(2) values of 0.64, 0.63, and 0.50 for triaryl rings, diaryl cycloalkanopyrazoles, and diphenyl hydrazides, respectively. In this COMBINE model, some protein residues were highlighted as particularly important for inhibitory activity. The combination of ligand-based and structure-based models provided an improved understanding in the interaction between the three chemical classes and the COX-2.     

Exploration of potential RSK2 inhibitors by pharmacophore modelling,structure-based 3D-QSAR,molecular docking study and molecular dynamics simulation

Abstract

The p90 ribosomal s6 kinase 2 (RSK2) is a promising target because of its over expression and activation in human cancer cells and tissues. Over the last few years, significant efforts have been made in order to develop RSK2 inhibitors to treat myeloma, prostatic cancer, skin cancer and etc., but with limited success so far. In this paper, pharmacophore modelling, molecular docking study and molecular dynamics (MD) simulation have been performed to explore the novel inhibitors of RSK2. Pharmacophore models were developed by 95 molecules having pIC₅₀ ranging from 4.577 to 9.000. The pharmacophore model includes one hydrogen bond acceptor (A), one hydrogen bond donor (D), one hydrophobic feature (H) and one aromatic ring (R). It is the best pharmacophore hypothesis that has the highest correlation coefficient (R² = 0.91) and cross validation coefficient (Q² = 0.71) at 5 component PLS factor. It was evaluated using enrichment analysis and the best model was used for virtual screening. The constraints used in this study were docking score, ADME properties, binding free energy estimates and IFD Score to screen the database. Ultimately, 12 hits were identified as potent and novel RSK2 inhibitors. A 15 ns molecular dynamics (MD) simulation was further employed to validate the reliability of the docking results.     

Synthesis,biological evaluation, 3D-QSAR studies of novel aryl-2H-pyrazole derivatives as telomerase inhibitors

A series of novel aryl-2H-pyrazole derivatives bearing 1,4-benzodioxan or 1,3-benzodioxole moiety were designed as potential telomerase inhibitors to enhance the ability of aryl-2H-pyrazole derivatives to inhibit telomerase, a target of anticancer. The telomerase inhibition tests showed that compound 16A displayed the most potent inhibitory activity with IC₅₀ value of 0.9 μM for telomerase. The antiproliferative tests showed that compound 16A exhibited high activity against human gastric cancer cell SGC-7901 and human melanoma cell B16-F10 with IC₅₀ values of 18.07 and 5.34 μM, respectively. Docking simulation showed that compound 16A could bind well with the telomerase active site and act as telomerase inhibitor. 3D-QSAR model was also built to provide more pharmacophore understanding that could be used to design new agents with more potent telomerase inhibitory activity.     

Novel Pyrazoloquinolin-2-ones: Design,synthesis, docking studies,and biological evaluation as antiproliferative EGFR-TK inhibitors

Two new series of diethyl 2-[2-(substituted-2-oxo-1,2-dihydroquinolin-4-yl)hydrazono]-succinates 6a-g and 1-(2-oxo-1,2-dihydroquinolin-4-yl)-1H-pyrazoles 7a-f have been designed and synthesized. The structures of the synthesized compounds were proved by IR, mass, NMR (2D) spectra and elemental analyses. The target compounds were evaluated for their in vitro cytotoxic activity against 60 cancer cell lines according to NCI protocol. Consequently, seven compounds were further examined against the most sensitive cell lines, leukemia CCRF-CEM, and MOLT-4. 5-Amino-1-(6-bromo-2-oxo-1,2-dihydroquinolin-4-yl)-1H-pyrazole-3,4-dicarbonitrile (7f) was the most active product, with IC₅₀ = 1.35 uM and 2.42 uM against MOLT-4 and CCRF-CEM, respectively. Also, it showed a remarkable inhibitory activity compared to erlotinib on the EGFR TK with IC₅₀ = 247.14 nM and 208.42 nM, respectively. Cell cycle analysis of MOLT-4 cells treated with 7f showed cell cycle arrest at G2/M phase (supported by Caspases, BAX and Bcl-2 studies) with a significant pro-apoptotic activity as indicated by annexin V-FITC staining. Moreover, the docking study indicated that both the pyrazole moiety and the quinolin-2-one ring showed good fitting into EGFR (PDB code: 1M17). In order to interpret SAR of the designed compounds, and provide a basis for further optimization, molecular docking of the synthesized compounds to known EGFR inhibitors was performed. The study illustrated the effect of several factors on the compounds’ activity.     

Discovery,molecular dynamic simulation and biological evaluation of structurally diverse cholinesterase inhibitors with new scaffold through shape-based pharmacophore virtual screening

Designing small molecule inhibitors targeting cholinesterases (ChEs) is considered as an efficient strategy for the treatment of Alzheimer′s disease (AD). In the present study, based on a shaped-based pharmacophore (SBP) model that we reported previously, virtual screening was performed on four commercial compound databases, from which eight small molecules containing new structurally scaffolds were retained and evaluated. In general, six of these potential hits were identified to be selective ChEs inhibitors. Three compounds exhibited IC₅₀ values and K_i values in micromolar range on acetylcholinesterase (AChE), the most active compound 4 showed IC₅₀ value of 6.31 ± 2.68 μM and K_i value of 4.76 μM. Other three compounds displayed IC₅₀ values and K_i values in micromolar range on butyrylcholinesterase (BChE) with high target selectivity, the most active compound 1 showed IC₅₀ value of 3.87 ± 2.48 μM and K_i value of 1.52 μM. Multiple biological evaluations were performed to determine their cytotoxicity, cyto-protective effects, antioxidant effect as well as druglike properties. These compounds provide new cores for the further design and optimization, with the aim to discover new ChEs inhibitors for the treatment of AD.     

Discover potential inhibitors for PFKFB3 using 3D-QSAR,virtual screening,molecular docking and molecular dynamics simulation

Abstract

The 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase-3 (PFKFB3) is a master regulator of glycolysis in cancer cells by synthesizing fructose-2,6-bisphosphate (F-2,6-BP), a potent allosteric activator of phosphofructokinase-1 (PFK-1), which is a rate-limiting enzyme of glycolysis. PFKFB3 is an attractive target for cancer treatment. It is valuable to discover promising inhibitors by using 3D-QSAR pharmacophore modeling, virtual screening, molecular docking and molecular dynamics simulation. Twenty molecules with known activity were used to build 3D-QSAR pharmacophore models. The best pharmacophore model was ADHR called Hypo1, which had the highest correlation value of 0.98 and the lowest RMSD of 0.82. Then, the Hypo1 was validated by cost value method, test set method and decoy set validation method. Next, the Hypo1 combined with Lipinski's rule of five and ADMET properties were employed to screen databases including Asinex and Specs, total of 1,048,159 molecules. The hits retrieved from screening were docked into protein by different procedures including HTVS, SP and XP. Finally, nine molecules were picked out as potential PFKFB3 inhibitors. The stability of PFKFB3-lead complexes was verified by 40?ns molecular dynamics simulation. The binding free energy and the energy contribution of per residue to the binding energy were calculated by MM-PBSA based on molecular dynamics simulation.     

Discovery of potential pancreatic cholesterol esterase inhibitors using pharmacophore modelling, virtual screening, and optimization studies

Pancreatic cholesterol esterase (CEase) is a serine hydrolase involved in the hydrolysis of variety of lipids and transport of free cholesterol. In this study, pharmacophore hypotheses based on known inhibitors were generated using common feature pharmacophore generation protocol available in Discovery Studio program. The best pharmacophore model containing two hydrogen bond acceptor and three hydrophobic features was selected and validated. It was further used in screening three diverse chemical databases. Hit compounds were subjected to drug-likeness and molecular docking studies. Four hits, namely SEW00846, NCI0040784, GK03167, and CD10645, were selected based on the GOLD fitness score and interaction with active site amino acids. All hit compounds were further optimized to improve their binding in the active site. The optimized compounds were found to have improved binding at the active site. Strongly binding optimized hits at the active site can act as virtual leads in potent CEase inhibitor designing.     

Rational design,synthesis, pharmacophore modeling,and docking studies for identification of novel potent DNA-PK inhibitors

Drugs of cancer based upon ionizing radiation or chemotherapeutic treatment may affect breaking of DNA double strand in cell. DNA-PK enzyme has emerged as an attractive target for drug discovery efforts toward DNA repair pathways. Hence, the search for potent and selective DNA-PK inhibitors has particularly considered state-of-the art and several series of inhibitors have been designed. In this article, a novel benchmark DNA-PK database of 43 compounds was built and described. Ligand-based approaches including pharmacophore and QSAR modeling were applied and novel models were introduced and analyzed for predicting activity test for DNA-PK drug candidates. Based upon the modeling results, we gave a report of synthesis of fifteen novel 2-((8-methyl-2-morpholino-4-oxo-4H-benzo[e][1,3]oxazin-7-yl)oxy)acetamide derivatives and in vitro evaluation for DNA-PK inhibitory and antiproliferative activities. These fifteen compounds overall are satisfied with Lipinski's rule of five. The biological testing of target compounds showed five promising active compounds 7c, 7d, 7f, 9e and 9f with micromolar DNA-PK activity range from 0.25 to 5 µM. In addition, SAR of the compounds activity was investigated and confirmed that the terminal aryl moiety was found to be quite crucial for DNA-PK activity. Moreover flexible docking simulation was done for the potent compounds into the putative binding site of the 3D homology model of DNA-PK enzyme and the probable interaction model between DNA-PK and the ligands was investigated and interpreted.