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The development of novel anti-infectives against Kinetoplastids pathogens targeting proteins is a big problem occasioned by the antigenic variation in these parasites. This is also a global concern due to the zoonosis of these parasites, as they infect both humans and animals. Therefore, we need not only to create novel antibiotics, but also to speed up the development pipeline for these antibiotics. This may be achieved by using novel drug targets for Kinetoplastids drug discovery. In this study, we focused our attention on motifs of rRNA molecules that have been created using homology modeling. The RNA is the most ambiguous biopolymer in the kinetoplatid, which carries many different functions. For instance, tRNAs, rRNAs, and mRNAs are essential for gene expression both in the pro-and eukaryotes. However, all these types of RNAs have sequences with unique 3D structures that are specific for kinetoplastids only and can be used to shut down essential biochemical processes in kinetoplastids only. All these features make RNA very potent targets for antibacterial drug development. Here, we combine in silico methods combined with both computational biology and structure prediction tools to address our hypothesis. In this study, we outline a systematic approach for identifying kinetoplastid rRNA-ligand interactions and, more specifically, techniques that can be used to identify small molecules that target particular RNA. The high-resolution optimized model structures of these kineoplastids were generated using RNA 123, where all the stereochemical conflicts were solved and energies minimized to attain the best biological qualities. The high-resolution optimized model's structures of these kinetoplastids were generated using RNA 123 where all the stereochemical conflicts were solved and energies minimized to attain the best biological qualities. These models were further analyzed to give their docking assessment reliability. Docking strategies, virtual screening, and fishing approaches successfully recognized novel and myriad macromolecular targets for the myxobacterial natural products with high binding affinities to exploit the unmet therapeutic needs. We demonstrate a sensible exploitation of virtual screening strategies to 18S rRNA using natural products interfaced with classical maximization of their efficacy in phamacognosy strategies that are well established. Integration of these virtual screening strategies in natural products chemistry and biochemistry research will spur the development of potential interventions to these tropical neglected diseases.

Background: Visceral leishmaniasis (VL) and zoonotic cutaneous leishmaniasis (ZCL) are of public health concern in Merti sub-County, Kenya, but epidemiological data on transmission, vector abundance, distribution, and reservoir hosts remain limited. To better understand the disease and inform control measures to reduce transmission, we investigated the abundance and distribution of sand fly species responsible for Leishmania transmission in the sub-County and their blood-meal hosts., Methods: We conducted an entomological survey in five villages with reported cases of VL in Merti sub-County, Kenya, using CDC miniature light traps and castor oil sticky papers. Sand flies were dissected and identified to the species level using standard taxonomic keys and PCR analysis of the cytochrome c oxidase subunit 1 (cox1) gene. Leishmania parasites were detected and identified by PCR and sequencing of internal transcribed spacer 1 (ITS1) genes. Blood-meal sources of engorged females were identified by high-resolution melting analysis of vertebrate cytochrome b (cyt-b) gene PCR products., Results: We sampled 526 sand flies consisting of 8 species, Phlebotomus orientalis (1.52%; n = 8), and 7 Sergentomyia spp. Sergentomyia squamipleuris was the most abundant sand fly species (78.71%; n = 414) followed by Sergentomyia clydei (10.46%; n = 55). Leishmania major, Leishmania donovani, and Trypanosoma DNA were detected in S. squamipleuris specimens. Humans were the main sources of sand fly blood meals. However, we also detected mixed blood meals; one S. squamipleuris specimen had fed on both human and mouse (Mus musculus) blood, while two Ph. orientalis specimens fed on human, hyrax (Procavia capensis), and mouse (Mus musculus) blood., Conclusions: Our findings implicate the potential involvement of S. squamipleuris in the transmission of Leishmania and question the dogma that human leishmaniases in the Old World are exclusively transmitted by sand flies of the Phlebotomus genus. The presence of Trypanosoma spp. may indicate mechanical transmission, whose efficiency should be investigated. Host preference analysis revealed the possibility of zoonotic transmission of leishmaniasis and other pathogens in the sub-County. Leishmania major and L. donovani are known to cause ZCL and VL, respectively. However, the reservoir status of the parasites is not uniform. Further studies are needed to determine the reservoir hosts of Leishmania spp. in the area.

Generation of three dimensional structures of macromolecules using in silico structural modeling technologies such as homology and de novo modeling has improved dramatically and increased the speed by which tertiary structures of organisms can be generated. This is especially the case if a homologous crystal structure is already available. High-resolution structures can be rapidly created using only their sequence information as input, a process that has the potential to increase the speed of scientific discovery. In this study, homology modeling and structure prediction tools such as RNA123 and SWISS-MODEL were used to generate the 40S ribosomal subunit from Plasmodium falciparum. This structure was modeled using the published crystal structure from Tetrahymena thermophila , a homologous eukaryote. In the absence of the Plasmodium falciparum 40S ribosomal crystal structure, the model accurately depicts a global topology, secondary and tertiary connections, and gives an overall root mean square deviation (RMSD) value of 3.9 Å relative to the template׳s crystal structure. Deviations are somewhat larger in areas with no homology between the templates. These results demonstrate that this approach has the power to identify motifs of interest in RNA and identify potential drug targets for macromolecules whose crystal structures are unknown. The results also show the utility of RNA homology modeling software for structure determination and lay the groundwork for applying this approach to larger and more complex eukaryotic ribosomes and other RNA-protein complexes. Structures generated from this study can be used in in silico screening experiments and lead to the determination of structures for targets/hit complexes.