RESUMO
The Zika virus (ZIKV), discovered in Africa in 1947, swiftly spread across continents, causing significant concern due to its recent association with microcephaly in newborns and Guillain-Barré syndrome in adults. Despite a decrease in prevalence, the potential for a resurgence remains, necessitating urgent therapeutic interventions. Like other flaviviruses, ZIKV presents promising drug targets within its replication machinery, notably the NS3 helicase (NS3Hel) protein, which plays critical roles in viral replication. However, a lack of structural information impedes the development of specific inhibitors targeting NS3Hel. Here we applied high-throughput crystallographic fragment screening on ZIKV NS3Hel, which yielded structures that reveal 3D binding poses of 46 fragments at multiple sites of the protein, including 11 unique fragments in the RNA-cleft site. These fragment structures provide templates for direct design of hit compounds and should thus assist the development of novel direct-acting antivirals against ZIKV and related flaviviruses, thus opening a promising avenue for combating future outbreaks.
RESUMO
Several Schistosoma species cause Schistosomiasis, an endemic disease in 78 countries that is ranked second amongst the parasitic diseases in terms of its socioeconomic impact and human health importance. The drug recommended for treatment by the WHO is praziquantel (PZQ), but there are concerns associated with PZQ, such as the lack of information about its exact mechanism of action, its high price, its effectiveness - which is limited to the parasite's adult form - and reports of resistance. The parasites lack the de novo purine pathway, rendering them dependent on the purine salvage pathway or host purine bases for nucleotide synthesis. Thus, the Schistosoma purine salvage pathway is an attractive target for the development of necessary and selective new drugs. In this study, the purine nucleotide phosphorylase II (PNP2), a new isoform of PNP1, was submitted to a high-throughput fragment-based hit discovery using a crystallographic screening strategy. PNP2 was crystallized and crystals were soaked with 827 fragments, a subset of the Maybridge 1000 library. X-ray diffraction data was collected and structures were solved. Out of 827-screened fragments we have obtained a total of 19 fragments that show binding to PNP2. Fourteen of these fragments bind to the active site of PNP2, while five were observed in three other sites. Here we present the first fragment screening against PNP2.
Assuntos
Descoberta de Drogas/métodos , Purina-Núcleosídeo Fosforilase/química , Purina-Núcleosídeo Fosforilase/metabolismo , Piridinas/metabolismo , Pirimidinas/metabolismo , Schistosoma mansoni/enzimologia , Tiazóis/metabolismo , Animais , Domínio Catalítico , Cristalização , Cristalografia por Raios X/métodos , Dimetil Sulfóxido/farmacologia , Avaliação Pré-Clínica de Medicamentos/métodos , Modelos Moleculares , Conformação Proteica em alfa-Hélice , Purina-Núcleosídeo Fosforilase/genética , Esquistossomose mansoni/tratamento farmacológico , Esquistossomose mansoni/parasitologiaRESUMO
Simulations of molecular dynamics (MD) are playing an increasingly important role in structure-based drug discovery (SBDD). Here we review the use of MD for proteins in aqueous solvation, organic/aqueous mixed solvents (MDmix) and with small ligands, to the classic SBDD problems: Binding mode and binding free energy predictions. The simulation of proteins in their condensed state reveals solvent structures and preferential interaction sites (hot spots) on the protein surface. The information provided by water and its cosolvents can be used very effectively to understand protein ligand recognition and to improve the predictive capability of well-established methods such as molecular docking. The application of MD simulations to the study of the association of proteins with drug-like compounds is currently only possible for specific cases, as it remains computationally very expensive and labor intensive. MDmix simulations on the other hand, can be used systematically to address some of the common tasks in SBDD. With the advent of new tools and faster computers we expect to see an increase in the application of mixed solvent MD simulations to a plethora of protein targets to identify new drug candidates.