Universitätsbibliothek

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to lentiviral vectors, FV vectors were not able to effi-ciently transduce nondividing cell (Shityakov and Rethwilm, unpublished data).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.

The high level of Axl tyrosine kinase expression in various cancer cell lines makes it an attractive target for the development of anti-cancer drugs. In this study, we carried out several sets of in silico screening for the ATP-competitive Axl kinase inhibitors based on different molecular docking protocols. The best drug-like candidates were identified, after parental structure modifications, by their highest affinity to the target protein. We found that our newly designed compound R5, a derivative of the R428 patented analog, is the most promising inhibitor of the Axl kinase according to the three molecular docking algorithms applied in the study. The molecular docking results are in agreement with the molecular dynamics simulations using the MM-PBSA/GBSA implicit solvation models, which confirm the high affinity of R5 toward the protein receptor. Additionally, the selectivity test against other kinases also reveals a high affinity of R5 toward ABL1 and Tyro3 kinases, emphasizing its promising potential for the treatment of malignant tumors.

Central nervous system dysfunction is an important cause of morbidity and mortality in patients with human immunodeficiency virus type 1 (HIV-1) infection and acquired immunodeficiency virus syndrome (AIDS). Patients with AIDS are usually affected by HIV-associated encephalitis (HIVE) with viral replication limited to cells of monocyte origin. To examine the molecular mechanisms underlying HIVE-induced dementia, the GSE4755 Affymetrix data were obtained from the Gene Expression Omnibus database and the differentially expressed genes (DEGs) between the samples from AIDS patients with and without apparent features of HIVE-induced dementia were identified. In addition, protein–protein interaction networks were constructed by mapping DEGs into protein–protein interaction data to identify the pathways that these DEGs are involved in. The results revealed that the expression of 1,528 DEGs is mainly involved in the immune response, regulation of cell proliferation, cellular response to inflammation, signal transduction, and viral replication cycle. Heat-shock protein alpha, class A member 1 (HSP90AA1), and fibronectin 1 were detected as hub nodes with degree values >130. In conclusion, the results indicate that HSP90A and fibronectin 1 play important roles in HIVE pathogenesis.

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.

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.