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.     

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.     

In silico screening of anti-inflammatory compounds from Lichen by targeting cyclooxygenase-2

Abstract

Non-steroidal anti-inflammatory drugs (NSAID) targeting cyclooxygenase-2 are clinically effective. However, they lack anti-thrombotic activity resulting in incidences of adverse effects like myocardial infarction, gastrointestinal and abdominal discomfort which necessitate for discovering new drug candidates with improved therapeutic effects and tolerability. Various recent researches have suggested that many lichens offer a vast reservoir for anti-inflammatory drug candidates which are natural as well as safe for human consumption. Drug discovery is a very complex and time-consuming process; however, in silico techniques can make this process simple and economic. Hence to find out natural anti-inflammatory compounds, we have carried out the virtual screening of 412 lichen compounds by molecular docking with human Cox-2 enzyme and validated the docking score by X-Score followed by ADMET and Drug-likeness analysis. The resulting 6 top-scored compounds were subjected to Molecular dynamics simulation (MDS) to analyze the stability of docked protein-ligand complex, to assess the fluctuation and conformational changes during protein-ligand interaction. The values of RMSD, Rg, and interaction energy after 30?ns of MDS revealed the good stability of these Lichen compounds in the active site pocket of Cox-2 in compare to reference, JMS. Additionally, we have done the pharmacophore analysis which found many common pharmacophore features between Lichen compounds and well known anti-inflammatory compounds. Our result shows that these lichen compounds are potential anti-inflammatory candidates and could be further modified and evaluated to develop more effective anti-inflammatory drugs with fewer side effects for the treatment of inflammatory diseases.

Communicated by Ramaswamy H. Sarma     

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.     

An in silico approach towards the identification of novel inhibitors of the TLR-4 signaling pathway

Precise functioning and fine-tuning of Toll-like receptor 4 (TLR4) signaling is a critical requirement for the smooth functioning of the innate immune system, since aberrant TLR4 activation causes excessive production of pro-inflammatory cytokines and interferons. This can result in life threatening conditions such as septic shock and other inflammatory disorders. The TRIF-related adaptor molecule (TRAM) adaptor protein is unique to the TLR4 signaling pathway and abrogation of TRAM-mediated TLR4 signaling is a promising strategy for developing therapeutics aimed at disrupting TRAM interactions with other components of the TLR4 signaling complex. The VIPER motif from the vaccinia virus-producing protein, A46 has been reported to disrupt TRAM-TLR4 interactions. We have exploited this information, in combination with homology modeling and docking approaches, to identify a potential binding site on TRAM lined by the BB loop and αC helix. Virtual screening of commercially available small molecules targeting the binding site enabled to short-list 12 small molecules to abrogate TRAM-mediated TLR4 signaling. Molecular dynamics and molecular mechanics calculations have been performed for the analysis of these receptor-ligand interactions.     

Cyclopropane derivatives as potential human serine racemase inhibitors: unveiling novel insights into a difficult target

d-Serine is the co-agonist of NMDA receptors and binds to the so-called glycine site. d-Serine is synthesized by human serine racemase (SR). Over activation of NMDA receptors is involved in many neurodegenerative diseases and, therefore, the inhibition of SR might represent a novel strategy for the treatment of these pathologies. SR is a very difficult target, with only few compounds so far identified exhibiting weak inhibitory activity. This study was aimed at the identification of novel SR inhibitor by mimicking malonic acid, the best-known SR inhibitor, with a cyclopropane scaffold. We developed, synthesized, and tested a series of cyclopropane dicarboxylic acid derivatives, complementing the synthetic effort with molecular docking. We identified few compounds that bind SR in high micromolar range with a lack of significant correlation between experimental and predicted binding affinities. The thorough analysis of the results can be exploited for the development of more potent SR inhibitors.     

Zika virus NS5 protein potential inhibitors: an enhanced in silico approach in drug discovery

The re-emerging Zika virus (ZIKV) is an arthropod-borne virus that has been described to have explosive potential as a worldwide pandemic. The initial transmission of the virus was through a mosquito vector, however, evolving modes of transmission has allowed the spread of the disease over continents. The virus has already been linked to irreversible chronic central nervous system conditions. The concerns of the scientific and clinical community are the consequences of Zika viral mutations, thus suggesting the urgent need for viral inhibitors. There have been large strides in vaccine development against the virus but there are still no FDA approved drugs available. Rapid rational drug design and discovery research is fundamental in the production of potent inhibitors against the virus that will not just mask the virus, but destroy it completely. In silico drug design allows for this prompt screening of potential leads, thus decreasing the consumption of precious time and resources. This study demonstrates an optimized and proven screening technique in the discovery of two potential small molecule inhibitors of ZIKV Methyltransferase and RNA dependent RNA polymerase. This in silico ‘per-residue energy decomposition pharmacophore’ virtual screening approach will be critical in aiding scientists in the discovery of not only effective inhibitors of Zika viral targets, but also a wide range of anti-viral agents.     

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     

Ligand-based virtual screening,molecular docking,QSAR and pharmacophore analysis of quercetin-associated potential novel analogs against epidermal growth factor receptor

The present study was to explore expectation and examination of therapeutic potential quercetin analogs as efficient anticancer agents against human epidermal growth factor receptor (EGFR), which is a consistent hallmark for moderating the non-small-cell lung carcinoma (NSCLC). Here, ligand-based virtual screening, pharmacophore approach and molecular docking were established as rational strategies for recognition of small analogs against the ligand binding domain of EGFR (PDB code: 1XKK). Adverse effects, toxicogenomics and pharmacokinetics reported that 10 candidates showed reliable consequences with less side effects and more efficient for target receptor. Protein–ligand interaction profiles revealed that the probable H-bonds, atomic-π contacts, salt bridges and van der Waals interactions sustain the complexity and stability of receptor structure; thus, they could complicate to generate single alteration acquired for drug resistance. In silico anticancer properties explain the lead scaffolds which are assumed to be flexible and experimentally proved chemicals. The overall consequences indicated that recognized leads could be utilized as reference skeletons for new inhibitors envisaging toward EGFR to ameliorate NSCLC and other malignant disorders.     

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     

A common feature-based 3D-pharmacophore model generation and virtual screening: identification of potential PfDHFR inhibitors

A four-feature 3D-pharmacophore model was built from a set of 24 compounds whose activities were reported against the V1/S strain of the Plasmodium falciparum dihydrofolate reductase (PfDHFR) enzyme. This is an enzyme harboring Asn51Ile + Cys59Arg + Ser108Asn + Ile164Leu mutations. The HipHop module of the Catalyst program was used to generate the model. Selection of the best model among the 10 hypotheses generated by HipHop was carried out based on rank and best-fit values or alignments of the training set compounds onto a particular hypothesis. The best model (hypo1) consisted of two H-bond donors, one hydrophobic aromatic, and one hydrophobic aliphatic features. Hypo1 was used as a query to virtually screen Maybridge2004 and NCI2000 databases. The hits obtained from the search were subsequently subjected to FlexX and Glide docking studies. Based on the binding scores and interactions in the active site of quadruple-mutant PfDHFR, a set of nine hits were identified as potential inhibitors.     

In silico identification and design of potent peptide inhibitors against PDZ-3 domain of Postsynaptic Density Protein (PSD-95)

Unique intrinsic properties of peptides like low toxicity, high biological activity, and specificity make them attractive therapeutic agents. PDZ-binding peptide inhibitors have been demonstrated for curing of Alzheimer, Parkinson, Dementia, and other central nervous system ailments. In this article, we report the successful use of an integrated computational protocol to analyze the structural basis of how peptides bind to the shallow groove of the third PDZ domain (PDZ-3) from the postsynaptic density (PSD-95) protein. This protocol employs careful and precise computational techniques for design of new strategy for predicting novel and potent peptides against PDZ protein. We attempted to generate a pharmacophore model using crystal structure of peptide inhibitor bound to the PDZ-3. A highly specific and sensitive generated pharmacophore model was used for screening virtual database generated using different combination of amino acid substitutions as well as decoy peptide database for its sensitivity and specificity. Identified hit peptides were further analyzed by docking studies, and their stability analyzed using solvated molecular dynamics. Quantum Mechanics/Molecular Mechanics (QM/MM) interaction energy and GMX-PBSA scoring schemes were used for ranking of stable peptides. Computational approach applied here generated encouraging results for identifying peptides against PDZ interaction model. The workflow can be further exercised as a virtual screening technique for reducing the search space for candidate target peptides against PDZ domains.     

New potential inhibitors of mTOR: a computational investigation integrating molecular docking,virtual screening and molecular dynamics simulation

The mTOR (mammalian or mechanistic Target Of Rapamycin), a complex metabolic pathway that involves multiple steps and regulators, is a major human metabolic pathway responsible for cell growth control in response to multiple factors and that is dysregulated in various types of cancer. The classical inhibition of the mTOR pathway is performed by rapamycin and its analogs (rapalogs). Considering that rapamycin binds to an allosteric site and performs a crucial role in the inhibition of the mTOR complex without causing the deleterious side effects common to ATP-competitive inhibitors, we employ ligand-based drug design strategies, such as virtual screening methodology, computational determination of ADME/Tox properties of selected molecules, and molecular dynamics in order to select molecules with the potential to become non-ATP-competitive inhibitors of the mTOR enzymatic complex. Our findings suggest five novel potential mTOR inhibitors, with similar or better properties than the classic inhibitor complex, rapamycin.     

Design,synthesis and biological evaluation of 2-aminopyrimidinones and their 6-aza-analogs as a new class of CK2 inhibitors

Abstract

In order to find the new potent CK2 inhibitors the 60 derivatives of 2-aminopyrimidinone and their 6-aza-substituted analogs were synthesized and tested in vitro. Among them, the most efficient inhibitor 2-hydroxy-5-[4-(4-methoxyphehyl)-6-oxo-1,6-dihydropyrimidin-2-ylamino] benzoic acid was identified (IC₅₀?=?1.1?μM). The structure--activity relationship study of newly synthesized derivatives was carried out and their binding mode with adenosine triphosphate-acceptor site of CK2 was proposed.     

Hierarchical virtual screening of the dual MMP-2/HDAC-6 inhibitors from natural products based on pharmacophore models and molecular docking

The dual-target inhibitors tend to improve the response rate in treating tumors, comparing with the single-target inhibitors. Matrix metalloproteinase-2 (MMP-2) and histone deacetylase-6 (HDAC-6) are attractive targets for cancer therapy. In this study, the hierarchical virtual screening of dual MMP-2/HDAC-6 inhibitors from natural products is investigated. The pharmacophore model of MMP-2 inhibitors is built based on ligands, but the pharmacophore model of HDAC-6 inhibitors is built based on the experimental crystal structures of multiple receptor–ligand complexes. The reliability of these two pharmacophore models is validated subsequently. The hierarchical virtual screening, combining these two different pharmacophore models of MMP-2 and HDAC-6 inhibitors with molecular docking, is carried out to identify the dual MMP-2/HDAC-6 inhibitors from a database of natural products. The four potential dual MMP-2/HDAC-6 inhibitors of natural products, STOCK1 N-46177, STOCK1 N-52245, STOCK1 N-55477, and STOCK1 N-69706, are found. The studies of binding modes show that the screened four natural products can simultaneously well bind with the MMP-2 and HDAC-6 active sites by different kinds of interactions, to inhibit the MMP-2 and HDAC-6 activities. In addition, the ADMET properties of screened four natural products are assessed. These found dual MMP-2/HDAC-6 inhibitors of natural products could serve as the lead compounds for designing the new dual MMP-2/HDAC-6 inhibitors having higher biological activities by carrying out structural modifications and optimizations in the future studies.     

Discovery of novel inhibitors of Mycobacterium tuberculosis MurG: homology modelling,structure based pharmacophore,molecular docking,and molecular dynamics simulations

MurG (Rv2153c) is a key player in the biosynthesis of the peptidoglycan layer in Mycobacterium tuberculosis (Mtb). This work is an attempt to highlight the structural and functional relationship of Mtb MurG, the three-dimensional (3D) structure of protein was constructed by homology modelling using Discovery Studio 3.5 software. The quality and consistency of generated model was assessed by PROCHECK, ProSA and ERRAT. Later, the model was optimized by molecular dynamics (MD) simulations and the optimized model complex with substrate Uridine-diphosphate-N-acetylglucosamine (UD1) facilitated us to employ structure-based virtual screening approach to obtain new hits from Asinex database using energy-optimized pharmacophore modelling (e-pharmacophore). The pharmacophore model was validated using enrichment calculations, and finally, validated model was employed for high-throughput virtual screening and molecular docking to identify novel Mtb MurG inhibitors. This study led to the identification of 10 potential compounds with good fitness, docking score, which make important interactions with the protein active site. The 25 ns MD simulations of three potential lead compounds with protein confirmed that the structure was stable and make several non-bonding interactions with amino acids, such as Leu290, Met310 and Asn167. Hence, we concluded that the identified compounds may act as new leads for the design of Mtb MurG inhibitors.     

In silico identification and screening of CYP24A1 inhibitors: 3D QSAR pharmacophore mapping and molecular dynamics analysis

Vitamin D is a key signalling molecule that plays a vital role in the regulation of calcium phosphate homeostasis and bone remodelling. The circulating biologically active form of vitamin D is regulated by the catabolic mechanism of cytochrome P450 24-hydroxylase (CYP24A1) enzyme. The over-expression of CYP24A1 negatively regulates the vitamin D level, which is the causative agent of chronic kidney disease, osteoporosis and several types of cancers. In this study, we found three potential lead molecules adverse to CYP24A1 through structure-based, atom-based pharmacophore and e-pharmacophore-based screening methods. Analysis was done by bioinformatics methods and tools like binding affinity (binding free energy), chemical reactivity (DFT studies) and molecular dynamics simulation (protein–ligand stability). Combined computational investigation showed that the compounds NCI_95001, NCI_382818 and UNPD_141613 may have inhibitory effects against the CYP24A1 protein.     

Human dopamine transporter: the first implementation of a combined in silico/in vitro approach revealing the substrate and inhibitor specificities

Parkinson’s disease (PD) is characterized by the loss of dopamine-generating neurons in the substantia nigra and corpus striatum. Current treatments alleviate PD symptoms rather than exerting neuroprotective effect on dopaminergic neurons. New drugs targeting the dopaminergic neurons by specific uptake through the human dopamine transporter (hDAT) could represent a viable strategy for establishing selective neuroprotection. Molecules able to increase the bioactive amount of extracellular dopamine, thereby enhancing and compensating a loss of dopaminergic neurotransmission, and to exert neuroprotective response because of their accumulation in the cytoplasm, are required. By means of homology modeling, molecular docking, and molecular dynamics simulations, we have generated 3D structure models of hDAT in complex with substrate and inhibitors. Our results clearly reveal differences in binding affinity of these compounds to the hDAT in the open and closed conformations, critical for future drug design. The established in silico approach allowed the identification of promising substrate compounds that were subsequently analyzed for their efficiency in inhibiting hDAT-dependent fluorescent substrate uptake, through in vitro live cell imaging experiments. Taken together, our work presents the first implementation of a combined in silico/in vitro approach enabling the selection of promising dopaminergic neuron-specific substrates.     

Novel virtual lead identification in the discovery of hematopoietic cell kinase (HCK) inhibitors: application of 3D QSAR and molecular dynamics simulation

High level of hematopoietic cell kinase (Hck) is associated with drug resistance in chronic myeloid leukemia. Additionally, Hck activity has also been connected with the pathogenesis of HIV-1 and chronic obstructive pulmonary disease. In this study, three-dimensional (3D) QSAR pharmacophore models were generated for Hck based on experimentally known inhibitors. A best pharmacophore model, Hypo1, was developed with high correlation coefficient (0.975), Low RMS deviation (0.60) and large cost difference (49.31), containing three ring aromatic and one hydrophobic aliphatic feature. It was further validated by the test set (r?=?0.96) and Fisher’s randomization method (95%). Hypo 1 was used as a 3D query for screening the chemical databases, and the hits were further screened by applying Lipinski’s rule of five and ADMET properties. Selected hit compounds were subjected to molecular docking to identify binding conformations in the active site. Finally, the appropriate binding modes of final hit compounds were revealed by molecular dynamics (MD) simulations and free energy calculation studies. Hence, we propose the final three hit compounds as virtual candidates for Hck inhibitors.     

Design,synthesis and evaluation of 2-phenylisothiazolidin-3-one-1,1-dioxides as a new class of human protein kinase CK2 inhibitors

Abstract

The synthesis and in vitro evaluation of 40 new 2-phenylisothiazolidin-3-one-1,1-dioxide derivatives are described. The optimization based on biological screening data and molecular modeling resulted in a 10-fold increase in inhibitory activity compared with previously reported inhibitors of this class and led to the identification of 3-{[2-chloro-4-(1,1-dioxido-3-oxoisothiazolidin-2-yl)benzoyl]amino}benzoic acid, a potent inhibitor of human protein kinase CK2 (?C₅₀?=?1.5?μM).