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Infektionen mit Herpesviren sind bereits seit der Antike bekannt. So beschrieb zum Beispiel schon Hippokrates in seinem »Corpus Hippocraticum« die sich auf der Haut ausbreitenden Herpes Simplex Läsionen und gab der Krankheit ihren bis heute gültigen Namen. Verbürgt ist auch, dass der römische Kaiser Tiberius vor etwa 2000 Jahren während einer auftretenden Herpes labialis-Epidemie das Küssen bei öffentlichen Zeremonien per Dekret verbat. Shakespeare war ebenfalls bestens vertraut mit den periodisch auftretenden Herpes-Bläschen; in seinem Werk »Romeo & Julia« spricht Mercutio zu Romeo: »O’er ladies lips, who straight on kisses dream, which oft the angry Mab with blisters plagues, ….« Doch erst in den 1960er Jahren erkannte man die virale Herkunft der Erkrankung.
Oral presentations Background: We selected peptide ligands for the HIV-1 packaging signal PSI by screening phage displayed peptide libraries. Peptide ligands were optimized by screening spot synthesis peptide membranes. The aim of this study is the functional characterization of these peptide ligands with respect to inhibition of HIV-1 replication. Methods: Phage displayed peptide libraries were screened with PSI-RNA structures. The Trp-rich peptide motifs were optimized for specific binding on spot synthesis peptide membranes. The best binding peptide was expressed intracellularly in fusion with RFP or linked to a protein transduction domain (PTD) for intracellular delivery. The effects on virion production were analyzed using pseudotyped lentiviral particles. Results: After positive and negative selection rounds, phages binding specifically to PSI-RNA were identified by ELISA. Peptide inserts contained conserved motifs of aromatic amino acids known to be implicated in binding of PSI-RNA by the natural Gag ligand. The filter assay identified HKWPWW as the best binding ligand for PSI-RNA, which is delivered into several cell lines by addition of a PTD. Compared to a control peptide, the HKWPWW peptide inhibited HIV-1 replication as deduced from reduced titers of culture supernatants. As HKWPWW also binds to the TAR-RNA like the natural nucleocapsid PSI-RNA ligand, the effect on Tat-TAR inhibition will also be analyzed. Currently T-cell lines are established which stably express HKWPWW as well as a control peptide, which will be infected with HIV-1 to monitor the ability of HKWPWW to inhibit wild type HIV-1 replication. Conclusion: The selection of a peptide ligand for PSI-RNA able to inhibit HIV-1 replication proves the suitability of the phage display technology for the selection of peptides binding to RNA-structures. This enables the indentification of peptides serving as leads to interfere with additional targets in the HIV-1 replication cycle.
Ribosomal proteins are assumed to stabilize specific RNA structures and promote compact folding of the large rRNA. The conformational dynamics of the protein between the bound and unbound state play an important role in the binding process. We have studied those dynamical changes in detail for the highly conserved complex between the ribosomal protein L11 and the GTPase region of 23S rRNA. The RNA domain is compactly folded into a well defined tertiary structure, which is further stabilized by the association with the C-terminal domain of the L11 protein (L11ctd). In addition, the N-terminal domain of L11 (L11ntd) is implicated in the binding of the natural thiazole antibiotic thiostrepton, which disrupts the elongation factor function. We have studied the conformation of the ribosomal protein and its dynamics by NMR in the unbound state, the RNA bound state and in the ternary complex with the RNA and thiostrepton. Our data reveal a rearrangement of the L11ntd, placing it closer to the RNA after binding of thiostrepton, which may prevent binding of elongation factors. We propose a model for the ternary L11–RNA–thiostrepton complex that is additionally based on interaction data and conformational information of the L11 protein. The model is consistent with earlier findings and provides an explanation for the role of L11ntd in elongation factor binding.
Background: Particle Swarm Optimization (PSO) is an established method for parameter optimization. It represents a population-based adaptive optimization technique that is influenced by several "strategy parameters". Choosing reasonable parameter values for the PSO is crucial for its convergence behavior, and depends on the optimization task. We present a method for parameter meta-optimization based on PSO and its application to neural network training. The concept of the Optimized Particle Swarm Optimization (OPSO) is to optimize the free parameters of the PSO by having swarms within a swarm. We assessed the performance of the OPSO method on a set of five artificial fitness functions and compared it to the performance of two popular PSO implementations. Results: Our results indicate that PSO performance can be improved if meta-optimized parameter sets are applied. In addition, we could improve optimization speed and quality on the other PSO methods in the majority of our experiments. We applied the OPSO method to neural network training with the aim to build a quantitative model for predicting blood-brain barrier permeation of small organic molecules. On average, training time decreased by a factor of four and two in comparison to the other PSO methods, respectively. By applying the OPSO method, a prediction model showing good correlation with training-, test- and validation data was obtained. Conclusion: Optimizing the free parameters of the PSO method can result in performance gain. The OPSO approach yields parameter combinations improving overall optimization performance. Its conceptual simplicity makes implementing the method a straightforward task.