RNA DEPENDENT RNA POLYMERASE: A VALUABLE TARGET TO BLOCK VIRAL REPLICATION IN SINGLE-STRANDED (+)SENSE RNA VIRUSES.

The (+)strand RNA viruses include a very large group of viruses that cause epidemic diseases in humans, including dengue fever and gastroenteritis. The human (+)RNA viruses include Flaviviruses (FV) and Norovirus (NV). Both encode for proteins essential for viral replication, such as the RNA dependent RNA polymerase (RdRp). Since human cells lack RdRp, it appears as one of the most promising targets for antivirals development. I worked on the identification of new non-nucleotide inhibitors against FV and NV, using RdRp as the main target. In this context, suramin and NF023 have been identified in my lab as NV RdRp inhibitors that, however both are hampered in their application by pharmacokinetics problems. To overcome such problems, I analyzed the potential inhibitory role of Naf2, a fragment derived from these two molecules. Although Naf2 showed a low inhibitory activity, the crystal structures of NV RdRp/Naf2 complex revealed a new binding site. To further map this new site, I tested a Naf2 related molecule, PPNDS. The crystal structures of the RdRp/PPNDS complex revealed interesting features about the new binding site. I also focused on structurally related molecules synthesized following structure-driven information. NV RdRp crystal structures in complex with one of these compounds (Cpd6) were analyzed, providing new knowledge on the interactions between a small fragment and NV RdRps, establishing a platform for structure-guided drug optimization. In parallel to the NV work, I screened in silico a library of compounds against FV RdRp. One of the best compounds identified (HeE1-2Tyr) was able to inhibit the RdRp activity and several FVs in cell-based assays. Although the crystallographic analyses don't reveal clear enough electron density for the inhibitor, indirect evidence suggests that HeE1-2Tyr interferes with the RdRp priming loop that appears disordered

A Comparative Numerical Study on GEM, MHSP and MSGC

In this work, we have tried to develop a detailed understanding of the physical processes occurring in those variants of Micro Pattern Gas Detectors (MPGDs) that share micro hole and micro strip geometry, like GEM, MHSP and MSGC etc. Some of the important and fundamental characteristics of these detectors such as gain, transparency, efficiency and their operational dependence on different device parameters have been estimated following detailed numerical simulation of the detector dynamics. We have used a relatively new simulation framework developed especially for the MPGDs that combines packages such as GARFIELD, neBEM, MAGBOLTZ and HEED. The results compare closely with the available experimental data. This suggests the efficacy of the framework to model the intricacies of these micro-structured detectors in addition to providing insight into their inherent complex dynamical processes

Naval Target Classification by Fusion of Multiple Imaging Sensors Based on the Confusion Matrix

This paper presents an algorithm for the classification of targets based on the fusion of the class information provided by different imaging sensors. The outputs of the different sensors are combined to obtain an accurate estimate of the target class. The performance of each imaging sensor is modelled by means of its confusion matrix (CM), whose elements are the conditional error probabilities in the classification and the conditional correct classification probabilities. These probabilities are used by each sensor to make a decision on the target class. Then, a final decision on the class is made using a suitable fusion rule in order to combine the local decisions provided by the sensors. The overall performance of the classification process is evaluated by means of the "fused" confusion matrix, i.e. the CM pertinent to the final decision on the target class. Two fusion rules are considered: a majority voting (MV) rule and a maximum likelihood (ML) rule. A case study is then presented, where the developed algorithm is applied to three imaging sensors located on a generic air platform: a video camera, an infrared camera (IR), and a spotlight Synthetic Aperture Radar (SAR)