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Human voltage-gated sodium (hNaV) channels are responsible for initiating and propagating action potentials in excitable cells, and mutations have been associated with numerous cardiac and neurological disorders. hNaV1.7 channels are expressed in peripheral neurons and are promising targets for pain therapy. The tarantula venom peptide protoxin-II (PTx2) has high selectivity for hNaV1.7 and is a valuable scaffold for designing novel therapeutics to treat pain. Here, we used computational modeling to study the molecular mechanisms of the state-dependent binding of PTx2 to hNaV1.7 voltage-sensing domains (VSDs). Using Rosetta structural modeling methods, we constructed atomistic models of the hNaV1.7 VSD II and IV in the activated and deactivated states with docked PTx2. We then performed microsecond-long all-atom molecular dynamics (MD) simulations of the systems in hydrated lipid bilayers. Our simulations revealed that PTx2 binds most favorably to the deactivated VSD II and activated VSD IV. These state-specific interactions are mediated primarily by PTx2’s residues R22, K26, K27, K28, and W30 with VSD and the surrounding membrane lipids. Our work revealed important protein–protein and protein–lipid contacts that contribute to high-affinity state-dependent toxin interaction with the channel. The workflow presented will prove useful for designing novel peptides with improved selectivity and potency for more effective and safe treatment of pain.

 

G protein-coupled receptors (GPCRs) represent the largest group of membrane receptors for transmembrane signal transduction. Ligand-induced activation of GPCRs triggers G protein activation followed by various signaling cascades. Understanding the structural and energetic determinants of ligand binding to GPCRs and GPCRs to G proteins is crucial to the design of pharmacological treatments targeting specific conformations of these proteins to precisely control their signaling properties. In this study, we focused on interactions of a prototypical GPCR, beta-2 adrenergic receptor (β 2 AR), with its endogenous agonist, norepinephrine (NE), and the stimulatory G protein (G s ). Using molecular dynamics (MD) simulations, we demonstrated the stabilization of cationic NE, NE(+), binding to β 2 AR by G s protein recruitment, in line with experimental observations. We also captured the partial dissociation of the ligand from β 2 AR and the conformational interconversions of G s between closed and open conformations in the NE(+)–β 2 AR–G s ternary complex while it is still bound to the receptor. The variation of NE(+) binding poses was found to alter G s α subunit (G s α) conformational transitions. Our simulations showed that the interdomain movement and the stacking of G s α α1 and α5 helices are significant for increasing the distance between the G s α and β 2 AR, which may indicate a partial dissociation of G s α The distance increase commences when G s α is predominantly in an open state and can be triggered by the intracellular loop 3 (ICL3) of β 2 AR interacting with G s α, causing conformational changes of the α5 helix. Our results help explain molecular mechanisms of ligand and GPCR-mediated modulation of G protein activation. 

Abstract Each year vast international resources are wasted on irreproducible research. The scientific community has been slow to adopt standard software engineering practices, despite the increases in high-dimensional data, complexities of workflows, and computational environments. Here we show how scientific software applications can be created in a reproducible manner when simple design goals for reproducibility are met. We describe the implementation of a test server framework and 40 scientific benchmarks, covering numerous applications in Rosetta bio-macromolecular modeling. High performance computing cluster integration allows these benchmarks to run continuously and automatically. Detailed protocol captures are useful for developers and users of Rosetta and other macromolecular modeling tools. The framework and design concepts presented here are valuable for developers and users of any type of scientific software and for the scientific community to create reproducible methods. Specific examples highlight the utility of this framework, and the comprehensive documentation illustrates the ease of adding new tests in a matter of hours. 

Lactic acid bacteria produce a variety of antimicrobial peptides known as bacteriocins. Most bacteriocins are understood to kill sensitive bacteria through receptor‐mediated disruptions. Here, we report on the identification of theLactobacillus plantarumplantaricin EF (PlnEF) receptor. Spontaneous PlnEF‐resistant mutants of the PlnEF‐indicator strainL. plantarumNCIMB 700965 (LP965) were isolated and confirmed to maintain cellular ATP levels in the presence of PlnEF. Genome comparisons resulted in the identification of a single mutated gene annotated as the membrane‐bound, magnesium/cobalt efflux protein CorC. All isolates contained a valine (V) at position 334 instead of a glycine (G) in a cysteine‐β‐synthase domain at the C‐terminal region of CorC. In silico template‐based modeling of this domain indicated that the mutation resides in a loop between two β‐strands. The relationship between PlnEF, CorC, and metal homeostasis was supported by the finding that PlnEF‐resistance was lost when PlnEF was applied together with high concentrations of Mg²⁺, Co²⁺, Zn²⁺, or Cu²⁺. Lastly, PlnEF sensitivity was increased upon heterologous expression of LP965corCbut not the G334V CorC mutant in the PlnEF‐resistant strainLactobacillus caseiBL23. These results show that PlnEF kills sensitive bacteria by targeting CorC.