In silico analysis of a few dietary phytochemicals as potential tumor chemo-sensitizers

P-glycoprotein (P-gp) is a membrane ATP-binding cassette (ABC) transporter that extrudes different xenobiotics out of cells. Besides its tissue protection role, overexpression of P-gp on the surface of many neoplastic cells restricts the cell entry of many anti-cancer drugs, the phenomenon which is known as multidrug resistance (MDR). It has been demonstrated that MDR cells can be sensitized toward anti-cancer agents when treated with P-gp inhibitors/modulators known as chemo-sensitizers. Due to the clinical significance and also considering the fact that many P-gp inhibitors are transported by P-gp, the search for more potent and low toxic non-transported chemo-sensitizers is an active area of research. Regarding this, several naturally occurring compounds were reported as MDR reversal agents, a category which is generally referred to as “fourth-generation P-gp inhibitors.” Dietary supplements containing natural products are widely used, and it is possible that they interact with co-administered pharmaceutical substances that are P-gp substrates, leading to altered pharmacokinetic profile. In silico approaches for quantitative and quantitative prediction of binding mechanism of dietary natural products to P-gp may be regarded as appropriate strategy in the early phase of drug discovery projects since they describe structural features of various phytochemicals for interaction with P-gp and pave the way toward alternative and novel anti-MDR scaffolds. In the present contribution, some phytochemicals of turmeric, black pepper, and green tea as commonly consumed dietary sources were subjected to systematic combined in silico analysis including molecular docking and amino acid decomposition analysis through B3LYP functional in association with 6-31G basis set. On the basis of major identified drug binding sites within P-gp internal pocket, modeled natural compounds were categorized as substrate, inhibitor, or modulator while structure binding relationship of each category was developed and elucidated.     

Understanding microscopic binding of human microsomal prostaglandin E synthase-1 with substrates and inhibitors by molecular modeling and dynamics simulation

Microsomal prostaglandin E synthase-1 (mPGES-1) is a promising target for development of next-generation anti-inflammatory drugs. It is crucial for rational design of the next-generation anti-inflammatory drugs to know the three-dimensional (3D) structure of mPGES-1 trimer and to understand how mPGES-1 binds with substrates and inhibitors. In the current work, a 3D structural model of human mPGES-1 trimer has been developed, for the first time, by performing combined homology modeling, molecular docking, and molecular dynamics simulation. The 3D structural model enables us to understand how mPGES-1 binds with its substrates/inhibitors, and the key amino acid residues for the mPGES-1 binding with ligands have been identified. The detailed 3D structures and calculated binding free energies for mPGES-1's binding with substrates and inhibitors are all consistent with available experimental data, suggesting that the 3D model of the mPGES-1 trimer and the enzyme-ligand binding modes are reasonable. The new structural insights obtained from this study should be valuable for rational design of next-generation anti-inflammatory drugs.     

An <Emphasis Type="BoldItalic">in silico</Emphasis> approach for screening flavonoids as P-glycoprotein inhibitors based on a Bayesian-regularized neural network

Summary P-glycoprotein (P-gp), an ATP-binding cassette (ABC) transporter, functions as a biological barrier by extruding cytotoxic agents out of cells, resulting in an obstacle in chemotherapeutic treatment of cancer. In order to aid in the development of potential P-gp inhibitors, we constructed a quantitative structure–activity relationship (QSAR) model of flavonoids as P-gp inhibitors based on Bayesian-regularized neural network (BRNN). A dataset of 57 flavonoids collected from a literature binding to the C-terminal nucleotide-binding domain of mouse P-gp was compiled. The predictive ability of the model was assessed using a test set that was independent of the training set, which showed a standard error of prediction of 0.146 ± 0.006 (data scaled from 0 to 1). Meanwhile, two other mathematical tools, back-propagation neural network (BPNN) and partial least squares (PLS) were also attempted to build QSAR models. The BRNN provided slightly better results for the test set compared to BPNN, but the difference was not significant according to F-statistic at p = 0.05. The PLS failed to build a reliable model in the present study. Our study indicates that the BRNN-based in silico model has good potential in facilitating the prediction of P-gp flavonoid inhibitors and might be applied in further drug design.     

Computational Insights into Allosteric Conformational Modulation of P-Glycoprotein by Substrate and Inhibitor Binding

The ATP-binding cassette (ABC) transporter P-glycoprotein (P-gp) is a physiologically essential membrane protein that protects many tissues against xenobiotic molecules, but limits the access of chemotherapeutics into tumor cells, thus contributing to multidrug resistance. The atomic-level mechanism of how substrates and inhibitors differentially affect the ATP hydrolysis by P-gp remains to be elucidated. In this work, atomistic molecular dynamics simulations in an explicit membrane/water environment were performed to explore the effects of substrate and inhibitor binding on the conformational dynamics of P-gp. Distinct differences in conformational changes that mainly occurred in the nucleotide-binding domains (NBDs) were observed from the substrate- and inhibitor-bound simulations. The binding of rhodamine-123 can increase the probability of the formation of an intermediate conformation, in which the NBDs were closer and better aligned, suggesting that substrate binding may prime the transporter for ATP hydrolysis. By contrast, the inhibitor QZ-Leu stabilized NBDs in a much more separated and misaligned conformation, which may result in the deficiency of ATP hydrolysis. The significant differences in conformational modulation of P-gp by substrate and inhibitor binding provided a molecular explanation of how these small molecules exert opposite effects on the ATPase activity. A further structural analysis suggested that the allosteric communication between transmembrane domains (TMDs) and NBDs was primarily mediated by two intracellular coupling helices. Our computational simulations provide not only valuable insights into the transport mechanism of P-gp substrates, but also for the molecular design of P-gp inhibitors.     

In silico model for P-glycoprotein substrate prediction: insights from molecular dynamics and in vitro studies

P-glycoprotein (P-gp) is a plasma membrane efflux transporter belonging to ATP-binding cassette superfamily, responsible for multidrug resistance in tumor cells. Over-expression of P-gp in cancer cells limits the efficacy of many anticancer drugs. A clear understanding of P-gp substrate binding will be advantageous in early drug discovery process. However, substrate poly-specificity of P-gp is a limiting factor in rational drug design. In this investigation, we report a dynamic trans-membrane model of P-gp that accurately identified the substrate binding residues of known anticancer agents. The study included homology modeling of human P-gp based on the crystal structure of C. elegans P-gp, molecular docking, molecular dynamics analyses and binding free energy calculations. The model was further utilized to speculate substrate propensity of in-house anticancer compounds. The model demonstrated promising results with one anticancer compound (NSC745689). As per our observations, the molecule could be a potential lead for anticancer agents devoid of P-gp mediated multiple drug resistance. The in silico results were further validated experimentally using Caco-2 cell lines studies, where NSC745689 exhibited poor permeability (P _app 1.03 ± 0.16 × 10^?6 cm/s) and low efflux ratio of 0.26.     

Discovery of Novel Symmetrical 1,4-Dihydropyridines as Inhibitors of Multidrug-Resistant Protein (MRP4) Efflux Pump for Anticancer Therapy

Despite the development of targeted therapies in cancer, the problem of multidrug resistance (MDR) is still unsolved. Most patients with metastatic cancer die from MDR. Transmembrane efflux pumps as the main cause of MDR have been addressed by developed inhibitors, but early inhibitors of the most prominent and longest known efflux pump P-glycoprotein (P-gp) were disappointing. Those inhibitors have been used without knowledge about the expression of P-gp by the treated tumor. Therefore the use of inhibitors of transmembrane efflux pumps in clinical settings is reconsidered as a promising strategy in the case of the respective efflux pump expression. We discovered novel symmetric inhibitors of the symmetric efflux pump MRP4 encoded by the ABCC4 gene. MRP4 is involved in many kinds of cancer with resistance to anticancer drugs. All compounds showed better activities than the best known MRP4 inhibitor MK571 in an MRP4-overexpressing cell line assay, and the activities could be related to the various substitution patterns of aromatic residues within the symmetric molecular framework. One of the best compounds was demonstrated to overcome the MRP4-mediated resistance in the cell line model to restore the anticancer drug sensitivity as a proof of concept.     

Exploring Natural Product Activity and Species Source Candidates for Hunting ABCB1 Transporter Inhibitors: An In Silico Drug Discovery Study

The P-glycoprotein (P-gp/ABCB1) is responsible for a xenobiotic efflux pump that shackles intracellular drug accumulation. Additionally, it is included in the dud of considerable antiviral and anticancer chemotherapies because of the multidrug resistance (MDR) phenomenon. In the search for prospective anticancer drugs that inhibit the ABCB1 transporter, the Natural Product Activity and Species Source (NPASS) database, containing >35,000 molecules, was explored for identifying ABCB1 inhibitors. The performance of AutoDock4.2.6 software to anticipate ABCB1 docking score and pose was first assessed according to available experimental data. The docking scores of the NPASS molecules were predicted against the ABCB1 transporter. Molecular dynamics (MD) simulations were conducted for molecules with docking scores lower than taxol, a reference inhibitor, pursued by molecular mechanics-generalized Born surface area (MM-GBSA) binding energy estimations. On the basis of MM-GBSA calculations, five compounds revealed promising binding affinities as ABCB1 inhibitors with ΔG_binding < −105.0 kcal/mol. The binding affinity and stability of the identified inhibitors were compared to the chemotherapeutic agent. Structural and energetical analyses unveiled great steadiness of the investigated inhibitors within the ABCB1 active site throughout 100 ns MD simulations. Conclusively, these findings point out that NPC104372, NPC475164, NPC2313, NPC197736, and NPC477344 hold guarantees as potential ABCB1 drug candidates and warrant further in vitro/in vivo tests.     

Diversity evolution and jump of Polo-like kinase 1 inhibitors

Polo-like kinase 1 (Plk1), a member of a family of serine/threonine kinases, is an attractive target for the development of anticancer drugs because it is involved in the regulation of cell-cycle progression and cytokinesis. This kinase provides two pockets for developing Plk1 inhibitors: the N-terminal catalytic domain (NCD) and the polo-box domain (PBD). For both of the two pockets, some natural products were identified as Plk1 inhibitors and some synthetic Plk1 inhibitors were developed by mimicking ATP and phosphopeptides, natural products binding to NCD and PBD respectively. This article not only reviews the progression of Plk1 inhibitors binding to these two pockets, but also discusses diversity evolution and jump in the process of drug development using Plk1 inhibitors as examples and how they impact on drug design and pharmacophore modeling.     

The Glitazone Class of Drugs as Carbonic Anhydrase Inhibitors—A Spin-Off Discovery from Fragment Screening

The approved drugs that target carbonic anhydrases (CA, EC 4.2.1.1), a family of zinc metalloenzymes, comprise almost exclusively of primary sulfonamides (R-SO₂NH₂) as the zinc binding chemotype. New clinical applications for CA inhibitors, particularly for hard-to-treat cancers, has driven a growing interest in the development of novel CA inhibitors. We recently discovered that the thiazolidinedione heterocycle, where the ring nitrogen carries no substituent, is a new zinc binding group and an alternate CA inhibitor chemotype. This heterocycle is curiously also a substructure of the glitazone class of drugs used in the treatment options for type 2 diabetes. Herein, we investigate and characterise three glitazone drugs (troglitazone 11, rosiglitazone 12 and pioglitazone 13) for binding to CA using native mass spectrometry, protein X-ray crystallography and hydrogen–deuterium exchange (HDX) mass spectrometry, followed by CA enzyme inhibition studies. The glitazone drugs all displayed appreciable binding to and inhibition of CA isozymes. Given that thiazolidinediones are not credited as a zinc binding group nor known as CA inhibitors, our findings indicate that CA may be an off-target of these compounds when used clinically. Furthermore, thiazolidinediones may represent a new opportunity for the development of novel CA inhibitors as future drugs.     

基于随机森林与Chemistry Development Kit描述符的P-gp底物识别

应用随机森林方法、开放源代码软件-CDK(Chemistry Development Kit)描述符与170个化合物的训练数据集[其中96个为磷糖蛋白(P-gp)底物], 建立了P-gp底物的识别模型. 研究了CDK描述符与P-gp底物识别的关系, 结果表明, 原子极化性和电荷偏面积等分子属性对P-gp底物识别起到重要作用. 该模型对训练集的预测正确率为99.42%; 对外部测试集(42个化合物, 其中24个为P-gp底物)的预测结果为P-gp底物、非底物及总测试集的识别正确率分别为87.50%, 83.33%和85.71%. 212个化合物数据集上的Leave-One-Out交叉验证识别正确率为77.4%.     

Identification of potential inhibitor and enzyme-inhibitor complex on trypanothione reductase to control Chagas disease

Chagas is a parasitic disease with major threat to public health due to its resistance against commonly available drugs. Trypanothione reductase (TryR) is the key enzyme to develop this disease. Though this enzyme is well thought-out as potential drug target, the accurate structure of enzyme-inhibitor complex is required to design a potential inhibitor which is less available for TryR. In this research, we aimed to investigate the advanced drug over the available existing drugs by designing inhibitors as well as to identify a new enzyme-inhibitor complex that may act as a template for drug design. A set of analogues were designed from a known inhibitor Quinacrine Mustard (QUM) to identify the effective inhibitor against this enzyme. Further, the pharmacoinformatics elucidation and structural properties of designed inhibitor proposed effective drug candidates against Chagas disease. Molecular docking study suggests that a designed inhibitor has higher binding affinity in both crystal and modeled TryR and also poses similar interacting residues as of crystal TryR-QUM complex structure. The comparative studies based on in silico prediction proposed an enzyme-inhibitor complex which could be effective to control the disease activity. So our in silico analysis based on TryR built model, Pharmacophore and docking analysis might play an important role for the development of novel therapy for Chagas disease. But both animal model experiments and clinical trials must be done to confirm the efficacy of the therapy.     

Mapping of the active site of proteases in the 1960s and rational design of inhibitors/drugs in the 1990s

For several decades the specificity of proteases has been presented as an active site divided into subsites, using the nomenclature of Schechter & Berger from 1967 (S1, S2... for subsites of the active site; P1, P2... for residues of the substrate occupying the corresponding subsites). At early stages of the research (1960s) it was realized that the size of the active site was larger than expected and important interactions occur in regions remote from the catalytic site. Since the active site was found to be large it was divided into subsites, and a procedure to map it up was developed. The map provides information on the size of the active site (number of subsites), the properties of each subsite (free energy of ligand binding, nature of binding forces, etc.), and it enables rational design of new substrates and inhibitors. Already in 1968 inhibitors with binding constants ten thousand fold higher than available inhibitors, were prepared. The model of a large active site was initially met with strong opposition. Before long, however, predictions of the model (size of the active site, interactions in subsites remote from the catalytic site) were confirmed by X-ray crystallography (1970). During the 1990s proteolytic enzymes received renewed attention in biology and medicine, they became therapeutic targets, and protease inhibitors were successfully applied in the treatment of AIDS and hypertension. The model of large active site divided into subsites, proposed 38 years ago, stood the test of time. This model is still in use in basic research to evaluate enzyme activity, and in pharmaceutical research for the development of inhibitors/drugs.     

Toward eradicating HIV reservoirs in the brain: inhibiting P-glycoprotein at the blood-brain barrier with prodrug abacavir dimers

Eradication of HIV reservoirs in the brain necessitates penetration of antiviral agents across the blood-brain barrier (BBB), a process limited by drug efflux proteins such as P-glycoprotein (P-gp) at the membrane of brain capillary endothelial cells. We present an innovative chemical strategy toward the goal of therapeutic brain penetration of the P-gp substrate and antiviral agent abacavir, in conjunction with a traceless tether. Dimeric prodrugs of abacavir were designed to have two functions: inhibit P-gp efflux at the BBB and revert to monomeric therapeutic within cellular reducing environments. The prodrug dimers are potent P-gp inhibitors in cell culture and in a brain capillary model of the BBB. Significantly, these agents demonstrate anti-HIV activity in two T-cell-based HIV assays, a result that is linked to cellular reversion of the prodrug to abacavir. This strategy represents a platform technology that may be applied to other therapies with limited brain penetration due to P-glycoprotein.     

Computational and conformational evaluation of FTase alternative substrates: insight into a novel enzyme binding pocket

Protein farnesyltransferase (FTase) is an important anticancer drug target. In an effort to develop isoprenoid diphosphate-based FTase inhibitors, striking variations have been observed in the ability of conservatively modified analogues to bind to the enzyme. For example, 2Z-GGPP is an alternative substrate with high binding affinity, while GGPP is not an alternative substrate. Using the availability of high-resolution FTase crystal structures, we have used pharmacophore and docking studies to elucidate a new binding pocket for isoprenoid analogues. The unique conformations between the first two isoprene units of 2Z-GGPP, but not GGPP, allows 2Z-GGPP to exploit this new binding pocket. The discovered conformation allows the molecule to adopt a reactive conformation while placing hydrophobic groups within the predominately hydrophobic binding pocket. This computational finding is supported by NMR studies on (13)C-labeled 2Z-farnesol, which confirm that the computationally predicted conformation is also favored in solution. These discoveries suggest that ligand conformational flexibility may be an important design consideration for the development of both inhibitors and alternative substrates of FTase.