Molecular modeling, simulation and virtual screening of ribosomal phosphoprotein P1 from Plasmodium falciparum

Ovarian morphological features and proteome reveal fecundity fitness disadvantages in β-cypermethrin-resistant strains of Blattella germanica (L.) (Blattodea: Blattellidae)

To evaluate whether the development of β-cypermethrin resistance in Blattella germanica (L.) (Blattaria: Blattellidae) affects the fecundity fitness of this insect and to determine the underlying mechanism, we compared fecundity differences between β-cypermethrin-resistant (R) and sensitive (S) strains of B. germanica, observed the physiological structural changes of ovaries from an visual perspective, and analyzed differences in the ovarian proteome using proteomic methods. The results showed that, compared with the S strain of B. germanica, the R strain of B. germanica had a significantly higher ootheca shedding rate, a significantly lower number of hatched and surviving nymphs, a significantly higher female proportion in the population and defective ovarian development. Ovarian proteomic analysis showed a total of 64 differentially expressed proteins in the R strain, including 18 upregulated proteins and 46 downregulated proteins. Twenty-four significantly differentially expressed proteins were further studied, and 14 were successfully identified, which were mainly classified into the following categories: immunity-related proteins, development-related proteins, structural proteins, energy metabolism-related proteins and proteins with unknown functions. The differential expression of these proteins reflects the overall changes in cell structure and metabolism associated with β-cypermethrin resistance and explains the possible molecular mechanism of fecundity fitness disadvantages. In summary, β-cypermethrin resistance can cause fecundity fitness disadvantages in B. germanica. The metabolic deviations needed to overcome the adverse effects of insecticides may result in an energy exchange that affects energy allocation and, ultimately, the basic needs of the insect. The fitness cost due to insecticide resistance is critical to the delay of the evolution of resistance.

Computer-Aided Drug Discovery Approaches against the Tropical Infectious Diseases Malaria, Tuberculosis, Trypanosomiasis, and Leishmaniasis

Despite the tremendous improvement in overall global health heralded by the adoption of the Millennium Declaration in the year 2000, tropical infections remain a major health problem in the developing world. Recent estimates indicate that the major tropical infectious diseases, namely, malaria, tuberculosis, trypanosomiasis, and leishmaniasis, account for more than 2.2 million deaths and a loss of approximately 85 million disability-adjusted life years annually. The crucial role of chemotherapy in curtailing the deleterious health and economic impacts of these infections has invigorated the search for new drugs against tropical infectious diseases. The research efforts have involved increased application of computational technologies in mainstream drug discovery programs at the hit identification, hit-to-lead, and lead optimization stages. This review highlights various computer-aided drug discovery approaches that have been utilized in efforts to identify novel antimalarial, antitubercular, antitrypanosomal, and antileishmanial agents. The focus is largely on developments over the past 5 years (2010-2014).