<i>Insilico</i> Anticancer Peptide Prediction from <i>Curcuma longa</i>

Cancer is the second biggest cause of death globally, and the use of therapeutic peptides to specifically target and destroy cancer cells has gotten much interest. Cancer peptides or vaccinations are utilized to treat cancer nowadays, apart from chemotherapy, which has significant discomfort, side effects and costly. It is time demanding to identify and predict potential anticancer peptides using computational biology approaches. Thus, 3-D molecular modeling is being used to find possible ACP candidates. In this research, Curcuma longa has predicted peptide sequences were docked on breast cancer receptors and used a molecular docking technique to assess the anticipated peptides’ binding affinities to MHC molecules. A similar approach was utilized to simulate the interactions of the chosen peptide with the TCR. Additionally, the Pep10 LIRQHVASNIGIAKSKIREPIV was examined, and our findings indicated interaction with MHC classes I and II. However, the maximum binding energy was obtained with TCR at 695.61, giving strength through eight hydrogen bonds. Similarly, the Pep20, GAIIGNRKIKLQPHIIIRID, the projected, has the most significant overall binding energy with MHC classes I and II but a lower global E total value with TCR, namely −600.97 kj/Mol, and also four hydrogen bonds. This research could lead to the development of novel anticancer drugs based on the anticancer activity of the Curcuma longa medicinal plant.     

Identification of natural compound inhibitors against PfDXR: A hybrid structure-based molecular modeling approach and molecular dynamics simulation studies

In the present contribution, multicomplex-based pharmacophore studies were carried out on the structural proteome of Plasmodium falciparum 1-deoxy-D -xylulose-5-phosphate reductoisomerase. Among the constructed models, a representative model with complementary features, accountable for the inhibition was used as a primary filter for the screening of database molecules. Auxiliary evaluations of the screened molecules were performed via drug-likeness and molecular docking studies. Subsequently, the stability of the docked inhibitors was envisioned by molecular dynamics simulations, principle component analysis, and molecular mechanics-Poisson-Boltzmann surface area-based free binding energy calculations. The stability assessment of the hits was done by comparing with the reference (beta-substituted fosmidomycin analog, LC5) to prioritize more potent candidates. All the complexes showed stable dynamic behavior while three of them displayed higher binding free energy compared with the reference. The work resulted in the identification of the compounds with diverse scaffolds, which could be used as initial leads for the design of novel PfDXR inhibitors.     

Key Features for Designing Phosphodiesterase-5 Inhibitors

Abstract

Phosphodiesterase superfamily is the key regulator of 3′,5′-cyclic guanosine monophosphate (cGMP) decomposition in human body. Phosphodiesterase-5 (PDE-5) inhibitors, sildenafil, vardenafil and tadalafil, are well known oral treatment for males with erectile dysfunction. To investigate the inhibitory effects of traditional Chinese medicine (TCM) compounds to PDE-5, we performed both ligand-based and structure-based studies on this topic. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) studies were conducted to construct three dimensional quantitative structure-activity relationship (3D-QSAR) models of series of known PDE-5 inhibitors. The predictive models had cross-validated, q², and non cross-validated coefficient, r², values of 0.791 and 0.948 for CoMFA and 0.724 and 0.908 for CoMSIA. These two 3D-QSAR models were used to predict activity of TCM compounds. Docking simulations were performed to further analyze the binding mode of training set and TCM compounds. A putative binding model was proposed based on CoMFA and CoMSIA contour maps and docking simulations; formation of pi-stacking, water bridge and specific hydrogen bonding were deemed important interactions between ligands and PDE-5. Of our TCM compounds, engeletin, satisfied our binding model, and hence, emerged as PDE-5 inhibitor candidate.

Using this study as an example, we demonstrated that docking should be conducted for qualitative purposes, such as identifying protein characteristics, rather than for quantitative analyses that rank compound efficacy based on results of scoring functions. Prediction of compound activity should be reserved for QSAR analyses, and scoring functions and docking scores should be used for preliminary screening of TCM database (http://tcm.cmu.edu.tw/index.php).     

Structural insight into Mycobacterium tuberculosis maltosyl transferase inhibitors: pharmacophore-based virtual screening,docking, and molecular dynamics simulations

Pharmacophore-based virtual screening, subsequent docking, and molecular dynamics (MD) simulations have been done to identify potential inhibitors of maltosyl transferase of Mycobacterium tuberculosis (mtb GlgE). Ligand and structure-based pharmacophore models representing its primary binding site (pbs) and unique secondary binding site 2 (sbs2), respectively, were constructed based on the three dimensional structure of mtb GlgE. These pharmacophore models were further used for screening of ZINC and antituberculosis compounds database (ATD). Virtually screened molecules satisfying Lipinski’s rule of five were then analyzed using docking studies and have identified 23 molecules with better binding affinity than its natural substrate, maltose. Four top scoring ligands from ZINC and ATD that either binds to pbs or sbs2 have been subjected to 10 ns each MD simulations and binding free energy calculations. Results of these studies have confirmed stable protein ligand binding. Results reported in the article are likely to be helpful in antitubercular therapeutic development research.     

Identifying HER2 inhibitors from natural products database

The relationship between abnormal HER2 expression and cancer is important in cancer therapeutics. Formation and spread of cancer cells may be restricted by inhibiting HER2. We conducted ligand-based and structure-based studies to assess the potency of natural compounds as potential HER2 inhibitors. Multiple linear regression (MLR) and support vector machine (SVM) models were constructed to predict biological activities of natural compounds, and molecular dynamics (MD) was used to assess their stability with HER2 under a dynamic environment. Predicted bioactivities of the natural compounds ranged from 6.014-9.077 using MLR (r(2) = 0.7954) and 5.122-6.950 using SVM (r(2) = 0.8620). Both models were in agreement and suggest bioactivity based on candidate structure. Conformation changes caused by MD favored the formation of stabilizing H-bonds. All candidates had higher stability than Lapinatib, which may be due to the number and spatial distribution of additional H-bonds and hydrophobic interactions. Amino acids Lys724 and Lys736 are critical for binding in HER2, and Thr798, Cys805, and Asp808 are also important for increased stability. Candidates may block the entrance to the ATP binding site located within the inner regions and prevent downstream activation of HER2. Our multidirectional approach indicates that the natural compounds have good ligand efficacy in addition to stable binding affinities to HER2, and should be potent candidates of HER2 inhibitors. With regard to drug design, designing HER2 inhibitors with carboxyl or carbonyl groups available for H-bond formation with Lys724 and Lys736, and benzene groups for hydrophobic contact with Cys805 may improve protein-ligand stability.     

Docking and molecular dynamics studies of new potential inhibitors of the human epidermal receptor 2

Compounds similar to lapatinib and gefitinib have been investigated as potential inhibitors of the intracellular receptor tyrosine kinase (RTK) domain of the human epidermal receptor 2 (HER2), which is a promising molecular target to the drug design of new chemotherapies for breast, lung, ovarian and colorectal cancers. In this study, we have searched potential HER2 inhibitors used for treatment of other illnesses such as hepatitis, bacterial infections and sexual impotence screened in the DrugBank. The compounds selected were subjected to virtual screening docking in order to evaluate the main interactions between them and the RTK domain of HER2. The selected compounds were investigated by flexible docking, molecular dynamics studies and ΔG _bind calculations. The results suggest that antrafenine, saprisartan, reserpine, irinotecan and udenafil are potential candidates to inhibit the RTK domain of HER2.     

3D-QSAR pharmacophore-based virtual screening,molecular docking and molecular dynamics simulation toward identifying lead compounds for NS2B–NS3 protease inhibitors

NS2B–NS3 protease has been identified to serve as lead drug design target due to its significant role in West Nile viral (WNV) and dengue virus (DENV) reproduction and replication. There are currently no approved chemotherapeutic drugs and effective vaccines to inhibit DENV and WNV infections. In this work, 3D-QSAR pharmacophore model has been developed to discover potential inhibitory candidates. Validation through Fischer’s model and decoy test indicate that the developed 3D pharmacophore model is highly predictive for DENV inhibitors, which was then employed to screen ZINC chemical library to obtain reasonable hits. Following ADMET filtering, 15 hits were subjected to further filter through molecular docking and CoMFA modeling. Finally, top three hits were identified as lead compounds or potential inhibitory candidates with IC₅₀ values of ～0.4637?µM and fitness of ～57.73. It is implied from CoMFA modeling that substituents at the side site of benzotriazole such as a p-nitro group (e.g. biphenyl head) and a carbonyl (e.g. carboxylate function) at the side site of furan or amino group may improve bioactivity of ZINC85645245, respectively. Molecular dynamics simulations (MDS) were performed to discover new interactions and reinforce the binding modes from docking for the hits also. The QSAR and MDS results obtained from this work should be useful in determining structural requirements for inhibitor development as well as in designing more potential inhibitors for NS2B–NS3 protease.     

Interactions of ketoamide inhibitors on HCV NS3/4A protease target: molecular docking studies

HCV infection in more than 200 million individuals worldwide is a principal health problem. Prior to the development of HCV protease inhibitor combination therapy, HCV infected patients were treated with pegylated interferon-α and ribavirin. The adverse side effects associated with this type of treatment may lead to the discontinuation of treatment in certain number of patients. Currently, the inhibitors of NS3/4A Protease were found promising candidates for the treatment of HCV infection. There are several inhibitors of HCV NS3/4A protease that are passing through clinical improvement showing good potency against HCV infections in a number of patients. To further recognize binding interactions and activity trend, the molecular docking studies were performed on a number of HCV NS3/4A protease ketoamide inhibitors via MOE docking protocol. The docking analysis resulted in the detection of important ligand interactions with respect to binding site of target proteinand produced good correlation coefficient (r² = 0.690) between docking score and biological activities. These molecular docking results should, in our view, contribute for further optimization of ketoamide derivatives as NS3/4A protease inhibitors.     

Computational analyses of curcuminoid analogs against kinase domain of HER2

Background

Human epidermal growth factor receptor 2 (HER2) has an important role in cancer aggressiveness and poor prognosis. HER2 has been used as a drug target for cancers. In particular, to effectively treat HER2-positive cancer, small molecule inhibitors were developed to target HER2 kinase. Knowing that curcumin has been used as food to inhibit cancer activity, this study evaluated the efficacy of natural curcumins and curcumin analogs as HER2 inhibitors using in vitro and in silico studies. The curcumin analogs considered in this study composed of 4 groups classified by their core structure, β-diketone, monoketone, pyrazole, and isoxazole.

Results

In the present study, both computational and experimental studies were performed. The specificity of curcumin analogs selected from the docked results was examined against human breast cancer cell lines. The screened curcumin compounds were then subjected to molecular dynamics simulation study. By modifying curcumin analogs, we found that protein-ligand affinity increases. The benzene ring with a hydroxyl group could enhance affinity by forming hydrophobic interactions and the hydrogen bond with the hydrophobic pocket. Hydroxyl, carbonyl or methoxy group also formed hydrogen bonds with residues in the adenine pocket and sugar pocket of HER2-TK. These modifications could suggest the new drug design for potentially effective HER2-TK inhibitors. Two outstanding compounds, bisdemethylcurcumin (AS-KTC006) and 3,5-bis((E)-3,4-dimethoxystyryl)isoxazole (AS-KTC021 ),were well oriented in the binding pocket almost in the simulation time, 30 ns. This evidence confirmed the results of cell-based assays and the docking studies. They possessed more distinguished interactions than known HER2-TK inhibitors, considering them as a promising drug in the near future.

Conclusions

The series of curcumin compounds were screened using a computational molecular docking and followed by human breast cancer cell lines assay. Both AS-KTC006 and AS-KTC021 could inhibit breast cancer cell lines though inhibiting of HER2-TK. The intermolecular interactions were confirmed by molecular dynamics simulation studies. This information would explore more understanding of curcuminoid structures and HER2-TK.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-261) contains supplementary material, which is available to authorized users.     

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.     

Pharmacophore models generation by catalyst and phase consensus-based virtual screening protocol against PI3Kα inhibitors

Phosphoinositide 3-kinases (PI3Ks) family has emerged as promising targets for novel therapeutic agents against neoplastic diseases. Pharmacophore and 3D-quantitative structure–activity relationship modelling were applied to study the structure–activity relationship of PI3K inhibitors. The best HypoGen pharmacophore hypothesis Hypo1 with a correlation coefficient of 0.961 consists of one hydrogen-bond acceptor, one hydrogen-bond donor and two hydrophobic features, whereas the best phase hypothesis AADRRR.378 with favourable statistics (q² = 0.7368, r² = 0.9863) has two hydrogen-bond acceptors, one hydrogen-bond donor and three ring aromatic features. Multiple methods, such as Fischer validation, molecular docking and mapping of test set molecules, were carried out to validate these pharmacophore models. Furthermore, a comparative molecular similarity indices analysis candidate hypothesis model was generated as a supplement of pharmacophore hypothesis. Detailed protein–ligand binding information obtained by Glide was utilised in compound optimisation and virtual screening. A molecular database of 133 known inhibitors and 6179 decoys was built for a screening test to quantitatively analyse various hypotheses and scoring parameters. Finally, we designed a workflow integrating HypoGen pharmacophore searching, phase pharmacophore searching and molecular docking for screening the database. With an improved criterion of enrichment factor (EF = 17.43) and ROC curve (AUC = 0.946), this workflow would provide us an original method for novel PI3K inhibitors.     

A selectivity study of sodium‐dependent glucose cotransporter 2/sodium‐dependent glucose cotransporter 1 inhibitors by molecular modeling

Sodium‐dependent glucose cotransporters (SGLTs) play an important role in glucose reabsorption in the kidney and have been identified as promising targets to treat diabetes. Because of the side effects like glucose and galactose malabsorption by targeting SGLT1, highly selective SGLT2 inhibitors are more promising in the treatment of diabetes. To understand the mechanism of selectivity, we conducted selectivity‐based three‐dimensional quantitative structure–activity relationship studies to highlight the structure requirements for highly selective SGLT2 inhibitors. The best comparative molecular field analysis and comparative molecular similarity indices analysis models showed the noncross‐validated coefficient (r²) of 0.967 and 0.943, respectively. The predicted correlation coefficients (r²_pred) of 0.974 and 0.938 validated the reliability and predictability of these models. Besides, homology models of SGLT2 and SGLT1 were also constructed to investigate the selective mechanism from structure‐based perspective. Molecular dynamics simulation and binding free energy calculation were performed on the systems of a potent and selective compound interacting with SGLT2 and SGLT1 to compare the different binding modes. The simulation results showed that the stretch of the methylthio group on Met241 had an essential effect on the different binding modes between SGLT1 and SGLT2, which was consistent with the three‐dimensional quantitative structure–activity relationship analysis. Hydrogen bond analysis and binding free energy calculation revealed that SGLT2 binding complex was more stable and favorable than SGLT1 complex, which was highly correlated with the experimental results. Our obtained results give useful information for the investigation of the inhibitors' selectivity between SGLT2 and SGLT1 and will help for further development of highly selective SGLT2 inhibitors. Copyright © 2015 John Wiley & Sons, Ltd.     

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     

A systematic analysis of the resistance and sensitivity of HER2YVMA receptor tyrosine kinase mutant to tyrosine kinase inhibitors in HER2-positive lung cancer

Human epidermal growth factor receptor 2 (HER2) has become a well-established target for the treatment of HER2-positive lung cancer. However, a frequently observed in-frame mutation that inserts amino acid quadruplex Tyr776-Val777-Met778-Ala779 at G776 (G776^YVMA) in HER2 kinase domain can cause drug resistance and sensitivity, largely limiting the application of reversible tyrosine kinase inhibitors in lung cancer therapy. A systematic investigation of the intermolecular interactions between the HER2^YVMA mutant and clinical small-molecule inhibitors would help to establish a complete picture of drug response to HER2 G776^YVMA insertion in lung cancer, and to design new tyrosine kinase inhibitors with high potency and selectivity to target the lung cancer-related HER2^YVMA mutant. Here, we combined homology modeling, ligand grafting, structure minimization, molecular simulation and binding affinity analysis to profile a number of tyrosine kinase inhibitors against the G776^YVMA insertion in HER2. It is found that the insertion is far away from HER2 active pocket and thus cannot contact inhibitor ligand directly. However, the insertion is expected to induce marked allosteric effect on some regions around the pocket, including A-loop and hinges connecting between the N- and C-lobes of HER2 kinase domain, which may exert indirect influence to inhibitor binding. Most investigated inhibitors exhibit weak binding strength to both wild-type and mutant HER2, which can be attributed to steric hindrance that impairs ligand compatibility with HER2 active pocket. However, the cognate inhibitor lapatinib and the non-cognate inhibitor bosutinib were predicted to have low affinity for wild-type HER2 but high affinity for HER2^YVMA mutant, which was confirmed by subsequent kinase assay experiments; the inhibitory potencies of bosutinib against wild-type and mutant HER2 were determined to be IC₅₀?>?1000 and =27?nM, respectively, suggesting that the bosutinib might be exploited as a selective inhibitor for mutant over wild-type HER2. Structural examination revealed that formation of additional non-bonded interactions such as hydrogen bonds and hydrophobic contacts with HER2 A-loop region due to G776^YVMA insertion is the primary factor to improve bosutinib affinity upon the mutation.     

Molecular docking and pharmacophore model studies of Rho kinase inhibitors

Molecular docking and pharmacophore model approaches were used to characterise the binding features of four different series of Rho kinase (ROCK) inhibitors. Docking simulation of 20 inhibitors with ROCK was performed. The binding conformations and binding affinities of these inhibitors were obtained using AutoDock 4.0 software. The predicted binding affinities correlate well with the activities of these inhibitors (R ² = 0.904). 3D pharmacophore models were generated for ROCK based on highly active inhibitors implemented in Catalyst 4.11 program. The best pharmacophore model consists of one hydrogen bond acceptor feature and two hydrophobic features, and they all seemed to be essential for inhibitors in terms of their binding activities. It is anticipated that the findings reported in this paper may provide very useful information for designing new ROCK inhibitors.     

In silico insights into the identification of potential novel angiogenic inhibitors against human VEGFR-2: a new SAR-based hierarchical clustering approach

Abstract

In this study, binding efficiency of new pyrrolopyrimidine structural analogs against human vascular endothelial growth factor receptor-2 (VEGFR-2) were elucidated using integrated in silico methods. Optimized high-resolution model of VEGFR-2 was generated and adopted for structure-based virtual screening approaches. Pyrrolopyrimidine inhibitor (CP15) associated compounds were screened from PubChem database and subjected to virtual screening and comparative docking methods against the receptor ligand-binding domain. Accordingly, high efficient compounds were clustered with similarity indices through PubChem structure cluster module using single-linkage algorithm. Moreover, pharmacokinetics including drug metabolism activities of high-binding leads under investigation was portrayed using ADMET and similarity ensemble analysis. Optimal energy orientations of the selected protein model have been shown to be reliable, and highly recommended for screening and docking studies. Docking and clustering strategies were shown that nineteen candidates as most effective binders for VEGFR-2 than CP15, and are grouped as three classes. Lys⁸⁶⁸, Glu⁸⁸⁵, Cys⁹¹⁹, His¹⁰²⁶, Arg¹⁰²⁷, Asp¹⁰⁴⁶, and Gly¹⁰⁴⁸ residues were predicted as novel hotspot residues, and participate in H-bonds, π-cation, π-stacking, halogen bonds, and salt-bridges formation with ligands. These additional bonds are contributing extent stability that holds the receptor structure at flexible state, this make difficult to any further conformational changes for evoking angiogenic signals. The ADMET and similarity ensemble analysis results were strongly indicated that thirteen candidates as best ligands for angiogenesis targets. Altogether, these findings indicate potential angiogenic templates and their binding levels with VEGFR-2; sorted viewpoints could be useful as a promising way to describe potential angiogenesis inhibitors with related molecular targets.     

Ligand-Guided Investigation of a Series of Formamidine-Based Thiuram Disulfides as Potential Dual-Inhibitors of COX-1and COX-2

A series of thiuram disulfides 1–6 which had been previously synthesized and characterized,^[1] were studied for their potential therapeutic properties. Target-fishing analyses through HitPick and SwissTarget prediction identified COX1 and COX2, which are essential biomolecules in cancer-related inflammations, as the possible targets for compounds 1 and 4 among all the compounds tested. These two proteins have enjoyed interest as targets for treating some neoplastic cancer types such as breast, colorectal, skin, pancreatic, haematological and head cancers. The inhibitory potency of 1 and 4 as lead anticancer drug candidates with dual-target ability against COX1 and COX2 was examined through molecular docking, molecular dynamics simulation and post-MD analyses such as binding energy calculation, RMSD, RMSF, and RoG. The two compounds had better docking scores and binding energies than the known inhibitors of COX1 and COX2. Insights from the RMSD, RMSF, and RoG suggested that both 1 and 4 showed observable influence on the structural stability of these targets throughout the simulation. The reported observations of the effects of 1 and 4 on the structures of COX1 and COX2 indicate their probable inhibitory properties against these target proteins and their potential as lead anticancer drug candidates.