RESUMO
The pneumococcal capsular serotype is an important determinant of complement resistance and invasive disease potential, but other virulence factors have also been found to contribute. Pneumococcal surface protein C (PspC), a highly variable virulence protein that binds complement factor H to evade C3 opsonization, is divided into two subgroups: choline-bound subgroup I and LPxTG-anchored subgroup II. The prevalence of different PspC subgroups in invasive pneumococcal disease (IPD) and functional differences in complement evasion are unknown. The prevalence of PspC subgroups in IPD isolates was determined in a collection of 349 sequenced strains of Streptococcus pneumoniae isolated from adult patients. pspC deletion mutants and isogenic pspC switch mutants were constructed to study differences in factor H binding and complement evasion in relation to capsule thickness. Subgroup I pspC was far more prevalent in IPD isolates than subgroup II pspC The presence of capsule was associated with a greater ability of bound factor H to reduce complement opsonization. Pneumococcal subgroup I PspC bound significantly more factor H and showed more effective complement evasion than subgroup II PspC in isogenic encapsulated pneumococci. We conclude that variation in the PspC subgroups, independent of capsule serotypes, affects pneumococcal factor H binding and its ability to evade complement deposition.
Assuntos
Proteínas de Bactérias/genética , Proteínas de Bactérias/imunologia , Proteínas do Sistema Complemento/imunologia , Genótipo , Infecções Pneumocócicas/imunologia , Infecções Pneumocócicas/microbiologia , Streptococcus pneumoniae/genética , Streptococcus pneumoniae/imunologia , Idoso , Fator H do Complemento/imunologia , Fator H do Complemento/metabolismo , Proteínas do Sistema Complemento/metabolismo , Feminino , Humanos , Evasão da Resposta Imune , Masculino , Pessoa de Meia-Idade , Tipagem Molecular , Mutação , Infecções Pneumocócicas/epidemiologia , Prevalência , Sorogrupo , Virulência/genética , Fatores de Virulência/genéticaRESUMO
Efforts to tackle malaria must continue for a disease that threatens half of the global population. Parasite resistance to current therapies requires new chemotypes that are able to demonstrate effectiveness and safety. Previously, we developed a machine-learning-based approach to predict compound antimalarial activity, which was trained on the compound collections of several organizations. The resulting prediction platform, MAIP, was made freely available to the scientific community and offers a solution to prioritize molecules of interest in virtual screening and hit-to-lead optimization. Here, we experimentally validate MAIP and demonstrate how the approach was used in combination with a robust compound selection workflow and a recently introduced innovative high-throughput screening (HTS) cascade to select and purchase compounds from a public library for subsequent experimental screening. We observed a 12-fold enrichment compared with a randomly selected set of molecules, and the eight hits we ultimately selected exhibit good potency and absorption, distribution, metabolism, and excretion (ADME) profiles.
RESUMO
A central challenge of antimalarial therapy is the emergence of resistance to the components of artemisinin-based combination therapies (ACTs) and the urgent need for new drugs acting through novel mechanism of action. Over the last decade, compounds identified in phenotypic high throughput screens (HTS) have provided the starting point for six candidate drugs currently in the Medicines for Malaria Venture (MMV) clinical development portfolio. However, the published screening data which provided much of the new chemical matter for malaria drug discovery projects have been extensively mined. Here we present a new screening and selection cascade for generation of hit compounds active against the blood stage of Plasmodium falciparum. In addition, we validate our approach by testing a library of 141,786 compounds not reported earlier as being tested against malaria. The Hit Generation Library 1 (HGL1) was designed to maximise the chemical diversity and novelty of compounds with physicochemical properties associated with potential for further development. A robust HTS cascade containing orthogonal efficacy and cytotoxicity assays, including a newly developed and validated nanoluciferase-based assay was used to profile the compounds. 75 compounds (Screening Active hit rate of 0.05%) were identified meeting our stringent selection criteria of potency in drug sensitive (NF54) and drug resistant (Dd2) parasite strains (IC50 ≤ 2 µM), rapid speed of action and cell viability in HepG2 cells (IC50 ≥ 10 µM). Following further profiling, 33 compounds were identified that meet the MMV Confirmed Active profile and are high quality starting points for new antimalarial drug discovery projects.