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Indinavir (Crivaxan®) is a potent inhibitor of the HIV (human immunodeficiency virus) protease. This enzyme has an important role in viral replication and is considered to be very attractive target for new antiretroviral drugs. However, it becomes less effective due to highly resistant new viral strains of HIV, which have multiple mutations in their proteases. For this reason, we used a lead expansion method to create a new set of compounds with a new mode of action to protease binding site. 1300 compounds chemically diverse from the initial hit were generated and screened to determine their ability to interact with protease and establish their QSAR properties. Further computational analyses revealed one unique compound with different protease binding ability from the initial hit and its role for possible new class of protease inhibitors is discussed in this report.
Molecular modelling and simulation are powerful methods in providing important in-formation on different biological systems to elucidate their structural and functional proper-ties, which cannot be determined in experiment. These methods are applied to analyse versa-tile biological systems: lipid membrane bilayers stabilized by an intercalated single wall carbon nanotube and retroviral proteins such as HIV protease and integrase. HIV-1 integrase has nuclear localization signals (NLS) which play a crucial role in nuclear import of viral preintegration complex (PIC). However, the detailed mechanisms of PIC formation and its nuclear transport are not known. Previously it was shown that NLSs bind to the cell transport machinery e.g. proteins of nuclear pore complex such as transportins. I investigated the interaction of this viral protein HIV-1 integrase with proteins of the nuclear pore complex such as transportin-SR2 (Shityakov et al., 2010). I showed that the transportin-SR2 in nuclear import is required due to its interaction with the HIV-1 integrase. I analyzed key domain interaction, and hydrogen bond formation in transportin-SR2. These results were discussed in comparison to other retroviral species such as foamy viruses to better understand this specific and efficient retroviral trafficking route. The retroviral nuclear import was next analyzed in experiments regarding the retroviral ability to infect nondividing cells. To accomplish the gene transfer task successfully, ret-roviruses must efficiently transduce different cell cultures at different phases of cell cycle. However, promising and safe foamy viral vectors used for gene transfer are unable to effi-ciently infect quiescent cells. This drawback was due to their inability to create a preintegra-tion complex (PIC) for nuclear import of retroviral DNA. On the contrary, the lentiviral vec-tors are not dependant on cell cycle. In the course of reverse transcription the polypurine tract (PPT) is believed to be crucial for PIC formation. In this thesis, I compared the transduction frequencies of PPT modified FV vectors with lentiviral vectors in nondividing and dividing alveolar basal epithelial cells from human adenocarcinoma (A549) by using molecular cloning, transfection and transduction techniques and several other methods. In contrast to lentiviral vectors, FV vectors were not able to effi-ciently transduce nondividing cell (Shityakov and Rethwilm, unpublished data). Despite the findings, which support the use of FV vectors as a safe and efficient alternative to lentiviral vectors, major limitation in terms of foamy-based retroviral vector gene transfer in quiescent cells still remains. Many attempts have been made recently to search for the potential molecules as pos-sible drug candidates to treat HIV infection for over decades now. These molecules can be retrieved from chemical libraries or can be designed on a computer screen and then synthe-sized in a laboratory. Most notably, one could use the computerized structure as a reference to determine the types of molecules that might block the enzyme. Such structure-based drug design strategies have the potential to save off years and millions of dollars compared to a more traditional trial-and-error drug development process. After the crystal structure of the HIV-encoded protease enzyme had been elucidated, computer-aided drug design played a pivotal role in the development of new compounds that inhibit this enzyme which is responsible for HIV maturation and infectivity. Promising repre-sentatives of these compounds have recently found their way to patients. Protease inhibitors show a powerful sustained suppression of HIV-1 replication, especially when used in combi-nation therapy regimens. However, these drugs are becoming less effective to more resistant HIV strains due to multiple mutations in the retroviral proteases. In computational drug design I used molecular modelling methods such as lead ex-pansion algorithm (Tripos®) to create a virtual library of compounds with different binding affinities to protease binding site. In addition, I heavily applied computer assisted combinato-rial chemistry approaches to design and optimize virtual libraries of protease inhibitors and performed in silico screening and pharmacophore-similarity scoring of these drug candidates. Further computational analyses revealed one unique compound with different protease bind-ing ability from the initial hit and its role for possible new class of protease inhibitors is dis-cussed (Shityakov and Dandekar, 2009). A number of atomistic models were developed to elucidate the nanotube behaviour in lipid bilayers. However, none of them provided useful information for CNT effect upon the lipid membrane bilayer for implementing all-atom models that will allow us to calculate the deviations of lipid molecules from CNT with atomistic precision. Unfortunately, the direct experimental investigation of nanotube behaviour in lipid bilayer remains quite a tricky prob-lem opening the door before the molecular simulation techniques. In this regard, more de-tailed multi-scale simulations are needed to clearly understand the stabilization characteristics of CNTs in hydrophobic environment. The phenomenon of an intercalated single-wall carbon nanotube in the center of lipid membrane was extensively studied and analyzed. The root mean square deviation and root mean square fluctuation functions were calculated in order to measure stability of lipid mem-branes. The results indicated that an intercalated carbon nanotube restrains the conformational freedom of adjacent lipids and hence has an impact on the membrane stabilization dynamics (Shityakov and Dandekar, 2011). On the other hand, different lipid membranes may have dissimilarities due to the differing abilities to create a bridge formation between the adherent lipid molecules. The results derived from this thesis will help to develop stable nanobiocom-posites for construction of novel biomaterials and delivery of various biomolecules for medi-cine and biology.
P-glycoprotein (P-gp)-mediated efflux system plays an important role to maintain chemical balance in mammalian cells for endogenous and exogenous chemical compounds. However, despite the extensive characterisation of P-gp potential interaction with drug-like molecules, the interaction of carbon nanoparticles with this type of protein molecule is poorly understood. Thus, carbon nanoparticles were analysed, such as buckminsterfullerenes (C20, C60, C70), capped armchair single-walled carbon nanotube (SWCNT or C168), and P-gp interactions using different molecular docking techniques, such as gradient optimisation algorithm (ADVina), Lamarckian genetic algorithm (FastDock), and shape-based approach (PatchDock) to estimate the binding affinities between these structures. The theoretical results represented in this work show that fullerenes might be P-gp binders because of low levels of Gibbs free energy of binding (ΔG) and potential of mean force (PMF) values. Furthermore, the SWCNT binding is energetically unfavourable, leading to a total decrease in binding affinity by elevation of the residual area (Ares), which also affects the π-π stacking mechanisms. Further, the obtained data could potentially call experimental studies using carbon nanostructures, such as SWCNT for development of drug delivery vehicles, to administer and assess drug-like chemical compounds to the target cells since organisms probably did not develop molecular sensing elements to detect these types of carbon molecules.
Glucocorticoids (GCs) are steroid hormones that have inflammatory and immunosuppressive effects on a wide variety of cells. They are used as therapy for inflammatory disease and as a common agent against edema. The blood brain barrier (BBB), comprising microvascular endothelial cells, serves as a permeability screen between the blood and the brain. As such, it maintains homeostasis of the central nervous system (CNS). In many CNS disorders, BBB integrity is compromised. GC treatment has been demonstrated to improve the tightness of the BBB. The responses and effects of GCs are mediated by the ubiquitous GC receptor (GR). Ligand-bound GR recognizes and binds to the GC response element located within the promoter region of target genes. Transactivation of certain target genes leads to improved barrier properties of endothelial cells. In this review, we deal with the role of GCs in endothelial cell barrier function. First, we describe the mechanisms of GC action at the molecular level. Next, we discuss the regulation of the BBB by GCs, with emphasis on genes targeted by GCs such as occludin, claudins and VE-cadherin. Finally, we present currently available GC therapeutic strategies and their limitations.
The dispersion routes of cyclodextrin complexes with nicardipine (NC), such as hydrophilic hydroxypropyl-\(\beta\)-cyclodextrin (NC/HP\(\beta\)CD) and hydrophobic triacetyl-\(\beta\)-cyclodextrin (NC/TA\(\beta\)CD), through the body for controlled drug delivery and sustained release have been examined. The two-compartment pharmacokinetic model described the mechanisms of how the human body handles with ingestion of NC-cyclodextrin complexes in gastrointestinal tract (GI), distribution in plasma, and their metabolism in the liver. The model showed that drug bioavailability was significantly improved after oral administration of cyclodextrin complexes. The mathematical significance of this study to predict nicardipine delivery using pharmacokinetic two-compartment mathematical model with linear ordinary differential equations (ODE) approach represents a valuable tool to emphasize its effectiveness and metabolizing rate and diminish the side effects.
We investigated the ionization profiles for open-ring (OR) and closed-ring (CR) forms of midazolam and drug-binding modes with heptakis-(2,3,6-tri-O-methyl)-β-cyclodextrin (trimethyl-β-cyclodextrin; TRIMEB) using molecular modeling techniques and quantum mechanics methods. The results indicated that the total net charges for different molecular forms of midazolam tend to be cationic for OR and neutral for CR at physiological pH levels. The thermodynamic calculations demonstrated that CR is less water-soluble than OR, mainly due to the maximal solvation energy (ΔG(CR)(solv = -9.98 kcal·mol ⁻¹), which has a minimal ΔG(OR)(solv) of -67.01 kcal·mol⁻¹. A cell viability assay did not detect any signs of TRIMEB and OR/CR-TRIMEB complex toxicity on the cEND cells after 24 h of incubation in either Dulbecco's Modified Eagles Medium or in heat-inactivated human serum. The molecular docking studies identified the more flexible OR form of midazolam as being a better binder to TRIMEB with the fluorophenyl ring introduced inside the amphiphilic cavity of the host molecule. The OR binding affinity was confirmed by a minimal Gibbs free energy of binding (ΔG(bind)) value of -5.57 ± 0.02 kcal·mol⁻¹, an equilibrium binding constant (K(b)) of 79.89 ± 2.706 μM, and a ligand efficiency index (LE(lig)) of -0.21 ± 0.001. Our current data suggest that in order to improve the clinical applications of midazolam via its complexation with trimethyl-β-cyclodextrin to increase drug's overall aqueous solubility, it is important to concern the different forms and ionization states of this anesthetic. All mean values are indicated with their standard deviations.
The blood–brain barrier choline transporter (BBB-ChT) may have utility as a drug delivery vector to the central nervous system (CNS). We therefore initiated molecular docking studies with the AutoDock and AutoDock Vina (ADVina) algorithms to develop predictive models for compound screening and to identify structural features important for binding to this transporter. The binding energy predictions were highly correlated with r2=0.88, F=692.4, standard error of estimate =0.775, and P-value<0.0001 for selected BBB-ChT-active/inactive compounds (n=93). Both programs were able to cluster active (Gibbs free energy of binding <−6.0 kcal*mol-1) and inactive (Gibbs free energy of binding >−6.0 kcal*mol-1) molecules and dock them significantly better than at random with an area under the curve value of 0.86 and 0.84, respectively. In ranking smaller molecules with few torsional bonds, a size-related bias in scoring producing false-negative outcomes was detected. Finally, important blood–brain barrier parameters, such as the logBBpassive and logBBactive values, were assessed to predict compound transport to the CNS accurately. Knowledge gained from this study is useful to better understand the binding requirements in BBB-ChT, and until such time as its crystal structure becomes available, it may have significant utility in developing a highly predictive model for the rational design of drug-like compounds targeted to the brain.
P-glycoprotein (P-gp) is an ATP (adenosine triphosphate)-binding cassette transporter that causes multidrug resistance of various chemotherapeutic substances by active efflux from mammalian cells. P-gp plays a pivotal role in limiting drug absorption and distribution in different organs, including the intestines and brain. Thus, the prediction of P-gp–drug interactions is of vital importance in assessing drug pharmacokinetic and pharmacodynamic properties. To find the strongest P-gp blockers, we performed an in silico structure-based screening of P-gp inhibitor library (1,300 molecules) by the gradient optimization method, using polynomial empirical scoring (POLSCORE) functions. We report a strong correlation (r2=0.80, F=16.27, n=6, P<0.0157) of inhibition constants (Kiexp or pKiexp; experimental Ki or negative decimal logarithm of Kiexp) converted from experimental IC50 (half maximal inhibitory concentration) values with POLSCORE-predicted constants (KiPOLSCORE or pKiPOLSCORE), using a linear regression fitting technique. The hydrophobic interactions between P-gp and selected drug substances were detected as the main forces responsible for the inhibition effect. The results showed that this scoring technique might be useful in the virtual screening and filtering of databases of drug-like compounds at the early stage of drug development processes.
The cytochrome P450 (CYP)3A4 enzyme affects the metabolism of most drug-like substances, and its inhibition may influence drug safety. Modulation of CYP3A4 by flavonoids, such as anthocyanins, has been shown to inhibit the mutagenic activity of mammalian cells. Considering the previous investigations addressing CYP3A4 inhibition by these substances, we studied the three-dimensional quantitative structure-activity relationship (3D-QSAR) in a series of anthocyanin derivatives as CYP3A4 inhibitors. For the training dataset (n=12), comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) yielded crossvalidated and non-crossvalidated models with a q (2) of 0.795 (0.687) and r (2) of 0.962 (0.948), respectively. The models were also validated by an external test set of four compounds with r (2) of 0.821 (CoMFA) and r (2) of 0.812 (CoMSIA). The binding affinity modes associated with experimentally derived IC50 (half maximal inhibitory concentration) values were confirmed by molecular docking into the CYP3A4 active site with r (2) of 0.66. The results obtained from this study are useful for a better understanding of the effects of anthocyanin derivatives on inhibition of carcinogen activation and cellular DNA damage.
Retroviral vectors are potent tools for gene delivery and various biomedical applications. To accomplish a gene transfer task successfully, retroviral vectors must effectively transduce diverse cell cultures at different phases of a cell cycle. However, very promising retroviral vectors based on the foamy viral (FV) backbone lack the capacity to efficiently transduce quiescent cells. It is hypothesized that this phenomenon might be explained as the inability of foamy viruses to form a pre-integration complex (PIC) with nuclear import activity in growth-arrested cells, which is the characteristic for lentiviruses (HIV-1). In this process, the HIV-1 central polypurine tract (cPPT) serves as a primer for plus-strand synthesis to produce a “flap” element and is believed to be crucial for the subsequent double-stranded cDNA formation of all retroviral RNA genomes. In this study, the effects of the lentiviral cPPT element on the FV transduction potential in dividing and growth-arrested (G1/S phase) adenocarcinomic human alveolar basal epithelial (A549) cells are investigated by experimental and theoretical methods. The results indicated that the HIV-1 cPPT element in a foamy viral vector background will lead to a significant reduction of the FV transduction and viral titre in growth-arrested cells due to the absence of PICs with nuclear import activity.