Cryo-EM structure of the NLRP3 decamer bound to the cytokine release inhibitory drug CRID3

NLRP3 is an intracellular sensor protein whose activation by a broad spectrum of exogenous and endogenous stimuli leads to inflammasome formation and pyroptosis. The mechanisms leading to NLRP3 activation and the way how antagonistic small molecules function remain poorly understood. Here we report the cryo-electron microscopy structures of full-length NLRP3 in its native form and complexed with the inhibitor CRID3 (also named MCC950). Inactive, ADP-bound NLRP3 is a decamer composed of homodimers of intertwined LRR domains that assemble back-to-back as pentamers with the NACHT domain located at the apical axis of this spherical structure. Molecular contacts between the concave sites of two opposing LRRs are mediated by an acidic loop extending from an LRR transition segment. Binding of CRID3 significantly stabilizes the NACHT and LRR domains relative to each other, allowing structural resolution of 3.9-4.2 Ang. CRID3 binds into a cleft, connecting four subdomains of the NACHT with the transition LRR. Its central sulfonylurea group interacts with the Walker A motif of the NLRP3 nucleotide-binding domain and is sandwiched between two arginines from opposing sites, explaining the specificity of NLRP3 for this chemical entity. With the determination of the binding site of this lead therapeutic, specific targeting of NLRP3 for the treatment of autoinflammatory and autoimmune diseases and rational drug optimization are within reach.

Challenges in the Delivery Room: Integrated Analysis of Biomarkers Predicting Complications in Lupus Pregnancy

Pregnancy in autoimmune rheumatic diseases remains a real challenge in clinical practice due to complex interplay between disease activity, pregnancy and drugs, and account for potential influence of pregnancy on rheumatic condition and the impact of disease on pregnancy outcomes. Indeed, innovative and successful therapies have dramatically improved the quality of life in immune-mediated rheumatic conditions and, subsequently, allowed more patients of reproductive age to plan a pregnancy/to conceive. The purpose of this chapter is to discuss emerging data about the interaction of pregnancy and systemic erythematosus lupus (SLE) focusing on modulation of the immune system by pregnancy, pregnancy outcomes in women with active lupus, biomarkers of adverse pregnancy outcomes (APO) including predictors of pre-eclampsia, predictors of obstetric complications in SLE, the influence of autoantibodies on fetal health, and, finally, evidence about rheumatologic and obstetric follow-up. There are still unmet needs in this new field of reproductive rheumatology and it becomes crucial that researchers, physicians (rheumatologists, specialists in maternofetal medicine, obstetricians) and midwifes share their knowledge and expertise in counseling women with SLE wishing to conceive, assisting pregnancy and managing different issues related to APO as well as drug optimization in preconception, during pregnancy and postpartum period.

Molecular Docking Suggests the Targets of Anti-Mycobacterial Natural Products

Tuberculosis (TB) is a major global threat, mostly due to the development of antibiotic-resistant forms of Mycobacterium tuberculosis, the causal agent of the disease. Driven by the pressing need for new anti-mycobacterial agents several natural products (NPs) have been shown to have in vitro activities against M. tuberculosis. The utility of any NP as a drug lead is augmented when the anti-mycobacterial target(s) is unknown. To suggest these, we used a molecular reverse docking approach to predict the interactions of 53 selected anti-mycobacterial NPs against known “druggable” mycobacterial targets ClpP1P2, DprE1, InhA, KasA, PanK, PknB and Pks13. The docking scores/binding free energies were predicted and calculated using AutoDock Vina along with physicochemical and structural properties of the NPs, using PaDEL descriptors. These were compared to the established inhibitor (control) drugs for each mycobacterial target. The specific interactions of the bisbenzylisoquinoline alkaloids 2-nortiliacorinine, tiliacorine and 13′-bromotiliacorinine against the targets PknB and DprE1 (−11.4, −10.9 and −9.8 kcal·mol−1; −12.7, −10.9 and −10.3 kcal·mol−1, respectively) and the lignan α-cubebin and Pks13 (−11.0 kcal·mol−1) had significantly superior docking scores compared to controls. Our approach can be used to suggest predicted targets for the NP to be validated experimentally, but these in silico steps are likely to facilitate drug optimization.

Drug Optimization for Cystic Fibrosis Patients Based on Disease Pathways Crosstalk

Cystic fibrosis (CF) is a common autosomal recessive disease characterized by pancreatic insufficiency and progressive deterioration of lung function. It has been shown that CF is caused by the presence of mutations in both alleles at the cystic fibrosis transmembrane conductance regulator (CFTR) gene. The severity of CF disease reflects the change of molecular mechanism, including DNA mutations on CFTR gene and polymorphic variations in disease modifier genes. Better understanding the differences among different CF severity group is helpful for improving therapeutic plans for patients. In this paper, the authors present a computational network biology approach to screen precision drugs for CF patients, which is based on the intensity of drugs impact on the pathway crosstalk mediated by differential methylation genes. The results indicate that ivacaftor, tezacaftor, and lumacaftor are applicable to all severity cohorts, gefitinib, sorafenib, sunitinib, and imatinib mesylate have the potential to treat intermediary CF patients, and tamoxifen may be useful to mild and sever CF patients.