Reversion mutations in phosphoprotein P of a codon-pair-deoptimized human respiratory syncytial virus confer increased transcription, immunogenicity, and genetic stability without loss of attenuation.

Recoding viral genomes by introducing numerous synonymous nucleotide substitutions that create suboptimal codon pairs provides new live-attenuated vaccine candidates. Because recoding typically involves a large number of nucleotide substitutions, the risk of de-attenuation is presumed to be low. However, this has not been thoroughly studied. We previously generated human respiratory syncytial virus (RSV) in which the NS1, NS2, N, P, M and SH ORFs were codon-pair deoptimized (CPD) by 695 synonymous nucleotide changes (Min A virus). Min A exhibited a global reduction in transcription and protein synthesis, was restricted for replication in vitro and in vivo, and exhibited moderate temperature sensitivity. Here, we show that under selective pressure by serial passage at progressively increasing temperatures, Min A regained replication fitness and lost its temperature sensitivity. Whole-genome deep sequencing identified numerous missense mutations in several genes, in particular ones accumulating between codons 25 and 34 of the phosphoprotein (P), a polymerase cofactor and chaperone. When re-introduced into Min A, these P mutations restored viral transcription to wt level, resulting in increased protein expression and RNA replication. Molecular dynamic simulations suggested that these P mutations increased the flexibility of the N-terminal domain of P, which might facilitate its interaction with the nucleoprotein N, and increase the functional efficiency of the RSV transcription/replication complex. Finally, we evaluated the effect of the P mutations on Min A replication and immunogenicity in hamsters. Mutation P[F28V] paradoxically reduced Min A replication but not its immunogenicity. The further addition of one missense mutation each in M and L generated a version of Min A with increased genetic stability. Thus, this study provides further insight into the adaptability of large-scale recoded RNA viruses under selective pressure and identified an improved CPD RSV vaccine candidate.

Modulation of free energy landscapes as a strategy for the design of antimicrobial peptides.

Computational design of antimicrobial peptides (AMPs) is a promising area of research for developing novel agents against drug-resistant bacteria. AMPs are present naturally in many organisms, from bacteria to humans, a time-tested mechanism that makes them attractive as effective antibiotics. Depending on the environment, AMPs can exhibit α-helical or ß-sheet conformations, a mix of both, or lack secondary structure; they can be linear or cyclic. Prediction of their structures is challenging but critical for rational design. Promising AMP leads can be developed using essentially two approaches: traditional modeling of the physicochemical mechanisms that determine peptide behavior in aqueous and membrane environments and knowledge-based, e.g., machine learning (ML) techniques, that exploit ever-growing AMP databases. Here, we explore the conformational landscapes of two recently ML-designed AMPs, characterize the dependence of these landscapes on the medium conditions, and identify features in peptide and membrane landscapes that mediate protein-membrane association. For both peptides, we observe greater conformational diversity in an aqueous solvent than in a less polar solvent, and one peptide is seen to alter its conformation more dramatically than the other upon the change of solvent. Our results support the view that structural rearrangement in response to environmental changes is central to the mechanism of membrane-structure disruption by linear peptides. We expect that the design of AMPs by ML will benefit from the incorporation of peptide conformational substates as quantified here with molecular simulations.

Artificial neural networks for the inverse design of nanoparticles with preferential nano-bio behaviors.

Safe and efficient use of ultrasmall nanoparticles (NPs) in biomedicine requires numerous independent conditions to be met, including colloidal stability, selectivity for proteins and membranes, binding specificity, and low affinity for plasma proteins. The ability of a NP to satisfy one or more of these requirements depends on its physicochemical characteristics, such as size, shape, and surface chemistry. Multiscale and pattern recognition techniques are here integrated to guide the design of NPs with preferential nano-bio behaviors. Data systematically collected from simulations (or experiments, if available) are first used to train one or more artificial neural networks, each optimized for a specific kind of nano-bio interaction; the trained networks are then interconnected in suitable arrays to obtain the NP core morphology and layer composition that best satisfy all the nano-bio interactions underlying more complex behaviors. This reverse engineering approach is illustrated in the case of NP-membrane interactions, using binding modes and affinities and early stage membrane penetrations as training data. Adaptations for designing NPs with preferential nano-protein interactions and for optimizing solution conditions in the test tube are discussed.

The Intriguing Effects of Substituents in the N-Phenethyl Moiety of Norhydromorphone: A Bifunctional Opioid from a Set of "Tail Wags Dog" Experiments.

(-)-N-Phenethyl analogs of optically pure N-norhydromorphone were synthesized and pharmacologically evaluated in several in vitro assays (opioid receptor binding, stimulation of [35S]GTPγS binding, forskolin-induced cAMP accumulation assay, and MOR-mediated ß-arrestin recruitment assays). "Body" and "tail" interactions with opioid receptors (a subset of Portoghese's message-address theory) were used for molecular modeling and simulations, where the "address" can be considered the "body" of the hydromorphone molecule and the "message" delivered by the substituent (tail) on the aromatic ring of the N-phenethyl moiety. One compound, N-p-chloro-phenethynorhydromorphone ((7aR,12bS)-3-(4-chlorophenethyl)-9-hydroxy-2,3,4,4a,5,6-hexahydro-1H-4,12-methanobenzofuro[3,2-e]isoquinolin-7(7aH)-one, 2i), was found to have nanomolar binding affinity at MOR and DOR. It was a potent partial agonist at MOR and a full potent agonist at DOR with a δ/µ potency ratio of 1.2 in the ([35S]GTPγS) assay. Bifunctional opioids that interact with MOR and DOR, the latter as agonists or antagonists, have been reported to have fewer side-effects than MOR agonists. The p-chlorophenethyl compound 2i was evaluated for its effect on respiration in both mice and squirrel monkeys. Compound 2i did not depress respiration (using normal air) in mice or squirrel monkeys. However, under conditions of hypercapnia (using air mixed with 5% CO2), respiration was depressed in squirrel monkeys.

Strong dependence of the nano-bio interactions on core morphology and layer composition of ultrasmall nanostructures.

The interactions between nanoparticles (NPs) and proteins, cells, and tissues, broadly known as nano-bio interactions, depend on the NP size and shape and on the characteristics of the NP coating layer, such as density, thickness, and chemical makeup. The dependence of nano-membrane interactions on the design parameters of ultrasmall nanostructures is studied by computer simulations. Considered here are spheres, plates, rings, rods, tubes, and helices made up of either bare magnetite or passivated gold, interacting with charged or zwitterionic membranes. The analysis reveals a strong dependence on shape, size, and layer composition of various quantities that characterize the nano-bio behavior, including binding modes and affinities. This sensitivity can be exploited to design nanostructures that bind preferentially to membranes or that stabilize or disrupt membrane structural integrity. The method used here is general and not limited to the ultrasmall regime, so it can be adopted to study other nano-bio interactions systematically. The implications for the distribution of NPs in cells and tissues (biodistribution) and for passive and active transmembrane transport are discussed, both important processes in biomedicine.

Correction: Self-adaptive multiscaling algorithm for efficient simulations of many-protein systems in crowded conditions.

Correction for 'Self-adaptive multiscaling algorithm for efficient simulations of many-protein systems in crowded conditions' by Sergio A. Hassan et al., Phys. Chem. Chem. Phys., 2018, DOI: 10.1039/c8cp05517c.

Self-adaptive multiscaling algorithm for efficient simulations of many-protein systems in crowded conditions.

A method is described for the efficient simulation of multiprotein systems in crowded environments. It is based on an adaptive, reversible structural coarsening algorithm that preserves relevant physical features of the proteins across scales. Water is treated implicitly whereas all the other components of the aqueous solution, such as ions, cosolutes, or osmolytes, are treated in atomic detail. The focus is on the analytical adaptation of the solvent model to different levels of molecular resolutions, which allows continuous, on-the-fly transitions between scales. This permits the analytical calculation of forces during dynamics and preserves detailed balance in Monte Carlo simulations. A major computational speedup can be achieved in systems containing hundreds of proteins without cutting off the long-range interactions. The method can be combined with a self-adaptive configurational-bias sampling technique described previously, designed to detect strong, weak, or ultra-weak protein associations and shown to improve sampling efficiency and convergence. The implementation aims to simulate early stages of multimeric complexation, aggregation, or self-assembly. The method can be adopted as the basis for a more general algorithm to identify vertices, edges, and hubs in protein interaction networks or to predict critical steps in signal transduction pathways.

Modulation of opioid receptor affinity and efficacy via N-substitution of 9ß-hydroxy-5-(3-hydroxyphenyl)morphan: Synthesis and computer simulation study.

The enantiomers of a variety of N-alkyl-, N-aralkyl-, and N-cyclopropylalkyl-9ß-hydroxy-5-(3-hydroxyphenyl)morphans were synthesized employing cyanogen bromide and K2CO3 to improve the original N-demethylation procedure. Their binding affinity to the µ-, δ-, and κ-opioid receptors (ORs) was determined and functional (GTPγ35S) assays were carried out on those with reasonable affinity. The 1R,5R,9S-enantiomers (1R,5R,9S)-(-)-5-(3-hydroxyphenyl)-2-(4-nitrophenethyl)-2-azabicyclo[3.3.1]nonan-9-ol (1R,5R,9S-16), (1R,5R,9S)-(-) 2-cinnamyl-5-(3-hydroxyphenyl)-2-azabicyclo[3.3.1]nonan-9-ol (1R,5R,9S-20), and (1R,5R,9S)-(-)-5-(3-hydroxyphenyl)-2-(4-(trifluoromethyl)phenethyl)-2-azabicyclo[3.3.1]nonan-9-ol (1R,5R,9S-15), had high affinity for the µ-opioid receptor (e.g., 1R,5R,9S-16: Ki=0.073, 0.74, and 1.99nM, respectively). The 1R,5R,9S-16 and 1R,5R,9S-15 were full, high efficacy µ-agonists (EC50=0.74 and 18.5nM, respectively) and the former was found to be a partial agonist at δ-OR and an antagonist at κ-OR, while the latter was a partial agonist at δ-OR and κ-OR in the GTPγ35S assay. The enantiomer of 1R,5R,9S-16, (+)-1S,5S,9R-16 was unusual, it had good affinity for the µ-OR (Ki=26.5nM) and was an efficacious µ-antagonist (Ke=29.1nM). Molecular dynamics simulations of the µ-OR were carried out with the 1R,5R,9S-16 µ-agonist and the previously synthesized (1R,5R,9S)-(-)-5-(9-hydroxy-5-(3-hydroxyphenyl-2-phenylethyl)-2-azabicyclo[3.3.1]nonane (1R,5R,9S-(-)-NIH 11289) to provide a structural basis for the observed high affinities and efficacies. The critical roles of both the 9ß-OH and the p-nitro group are elucidated, with the latter forming direct, persistent hydrogen bonds with residues deep in the binding cavity, and the former interacting with specific residues via highly structured water bridges.

Detection and characterization of nonspecific, sparsely populated binding modes in the early stages of complexation.

A method is proposed to study protein-ligand binding in a system governed by specific and nonspecific interactions. Strong associations lead to narrow distributions in the proteins configuration space; weak and ultraweak associations lead instead to broader distributions, a manifestation of nonspecific, sparsely populated binding modes with multiple interfaces. The method is based on the notion that a discrete set of preferential first-encounter modes are metastable states from which stable (prerelaxation) complexes at equilibrium evolve. The method can be used to explore alternative pathways of complexation with statistical significance and can be integrated into a general algorithm to study protein interaction networks. The method is applied to a peptide-protein complex. The peptide adopts several low-population conformers and binds in a variety of modes with a broad range of affinities. The system is thus well suited to analyze general features of binding, including conformational selection, multiplicity of binding modes, and nonspecific interactions, and to illustrate how the method can be applied to study these problems systematically. The equilibrium distributions can be used to generate biasing functions for simulations of multiprotein systems from which bulk thermodynamic quantities can be calculated.

Implicit treatment of solvent dispersion forces in protein simulations.

A model is proposed for the evaluation of dispersive forces in a continuum solvent representation for use in large-scale computer simulations. The model captures the short- and long-range effects of water-exclusion in conditions of partial and anisotropic hydration. The model introduces three parameters, one of which represents the degree of hydration (water occupancy) at any point in the system, which depends on the solute conformation, and two that represent the strength of water-water and water-solute dispersive interactions. The model is optimized for proteins, using hydration data of a suboptimally hydrated binding site and results from dynamics simulations in explicit water. The model is applied to a series of aliphatic-alcohol/protein complexes and a set of binary and ternary complexes of various sizes. Implications for weak and ultra-weak protein-protein association and for simulation in crowded media are discussed.

An unusual dual sugar-binding lectin domain controls the substrate specificity of a mucin-type O-glycosyltransferase.

N-acetylgalactosaminyl-transferases (GalNAc-Ts) initiate mucin-type O-glycosylation, an abundant and complex posttranslational modification that regulates host-microbe interactions, tissue development, and metabolism. GalNAc-Ts contain a lectin domain consisting of three homologous repeats (α, ß, and γ), where α and ß can potentially interact with O-GalNAc on substrates to enhance activity toward a nearby acceptor Thr/Ser. The ubiquitous isoenzyme GalNAc-T1 modulates heart development, immunity, and SARS-CoV-2 infectivity, but its substrates are largely unknown. Here, we show that both α and ß in GalNAc-T1 uniquely orchestrate the O-glycosylation of various glycopeptide substrates. The α repeat directs O-glycosylation to acceptor sites carboxyl-terminal to an existing GalNAc, while the ß repeat directs O-glycosylation to amino-terminal sites. In addition, GalNAc-T1 incorporates α and ß into various substrate binding modes to cooperatively increase the specificity toward an acceptor site located between two existing O-glycans. Our studies highlight a unique mechanism by which dual lectin repeats expand substrate specificity and provide crucial information for identifying the biological substrates of GalNAc-T1.

A conserved oligomerization domain in the disordered linker of coronavirus nucleocapsid proteins.

The nucleocapsid (N-)protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a key role in viral assembly and scaffolding of the viral RNA. It promotes liquid-liquid phase separation (LLPS), forming dense droplets that support the assembly of ribonucleoprotein particles with as-of-yet unknown macromolecular architecture. Combining biophysical experiments, molecular dynamics simulations, and analysis of the mutational landscape, we describe a heretofore unknown oligomerization site that contributes to LLPS, is required for the assembly of higher-order protein-nucleic acid complexes, and is coupled to large-scale conformational changes of N-protein upon nucleic acid binding. The self-association interface is located in a leucine-rich sequence of the intrinsically disordered linker between N-protein folded domains and formed by transient helices assembling into trimeric coiled-coils. Critical residues stabilizing hydrophobic and electrostatic interactions between adjacent helices are highly protected against mutations in viable SARS-CoV-2 genomes, and the oligomerization motif is conserved across related coronaviruses, thus presenting a target for antiviral therapeutics.

Cannabinoformins: Designing Biguanide-Embedded, Orally Available, Peripherally Selective Cannabinoid-1 Receptor Antagonists for Metabolic Syndrome Disorders.

We have designed orally bioavailable, non-brain-penetrant antagonists of the cannabinoid-1 receptor (CB1R) with a built-in biguanide sensor to mimic 5'-adenosine monophosphate kinase (AMPK) activation for treating obesity-associated co-morbidities. A series of 3,4-diarylpyrazolines bearing rational pharmacophoric pendants designed to limit brain penetration were synthesized and evaluated in CB1R ligand binding assays and recombinant AMPK assays. The compounds displayed high CB1R binding affinity and potent CB1R antagonist activities and acted as AMPK activators. Select compounds showed good oral exposure, with compounds 36, 38-S, and 39-S showing <5% brain penetrance, attesting to peripheral restriction. In vivo studies of 38-S revealed decreased food intake and body weight reduction in diet-induced obese mice as well as oral in vivo efficacy of 38-S in ameliorating glucose tolerance and insulin resistance. The designed "cannabinoformin" four-arm CB1R antagonists could serve as potential leads for treatment of metabolic syndrome disorders with negligible neuropsychiatric side effects.

The Host Adapted Fungal Pathogens of Pneumocystis Genus Utilize Genic Regional Centromeres.

Centromeres are genomic regions that coordinate accurate chromosomal segregation during mitosis and meiosis. Yet, despite their essential function, centromeres evolve rapidly across eukaryotes. Centromeres are often the sites of chromosomal breaks which contribute to genome shuffling and promote speciation by inhibiting gene flow. How centromeres form in strongly host-adapted fungal pathogens has yet to be investigated. Here, we characterized the centromere structures in closely related species of mammalian-specific pathogens of the fungal phylum of Ascomycota. Methods allowing reliable continuous culture of Pneumocystis species do not currently exist, precluding genetic manipulation. CENP-A, a variant of histone H3, is the epigenetic marker that defines centromeres in most eukaryotes. Using heterologous complementation, we show that the Pneumocystis CENP-A ortholog is functionally equivalent to CENP-ACnp1 of Schizosaccharomyces pombe. Using organisms from a short-term in vitro culture or infected animal models and ChIP-seq, we identified centromeres in three Pneumocystis species that diverged ~100 million years ago. Each species has a unique short regional centromere (< 10kb) flanked by heterochromatin in 16-17 monocentric chromosomes. They span active genes and lack conserved DNA sequence motifs and repeats. CENP-C, a scaffold protein that links the inner centromere to the kinetochore appears dispensable in one species, suggesting a kinetochore rewiring. Despite the loss of DNA methyltransferases, 5-methylcytosine DNA methylation occurs in these species, though not related to centromere function. These features suggest an epigenetic specification of centromere function.

Self-consistent treatment of the local dielectric permittivity and electrostatic potential in solution for polarizable macromolecular force fields.

A self-consistent method is presented for the calculation of the local dielectric permittivity and electrostatic potential generated by a solute of arbitrary shape and charge distribution in a polar and polarizable liquid. The structure and dynamics behavior of the liquid at the solute/liquid interface determine the spatial variations of the density and the dielectric response. Emphasis here is on the treatment of the interface. The method is an extension of conventional methods used in continuum protein electrostatics, and can be used to estimate changes in the static dielectric response of the liquid as it adapts to charge redistribution within the solute. This is most relevant in the context of polarizable force fields, during electron structure optimization in quantum chemical calculations, or upon charge transfer. The method is computationally efficient and well suited for code parallelization, and can be used for on-the-fly calculations of the local permittivity in dynamics simulations of systems with large and heterogeneous charge distributions, such as proteins, nucleic acids, and polyelectrolytes. Numerical calculation of the system free energy is discussed for the general case of a liquid with field-dependent dielectric response.

A filarial parasite-encoded human IL-10 receptor antagonist reveals a novel strategy to modulate host responses.

Interleukin (IL)-10 is the primary cytokine driving the modulation of the host response in filarial infections. We performed binding assays with Brugia malayi antigen extracts and human IL-10R1. Bm5539 was the top-binding hit. We identified a short sequence, termed truncated Bm5339, that has structural similarities to the human IL-10 functional dimer. Sequence comparisons revealed that other filarial parasites possess Bm5539 orthologues. Using recombinant Bm5539 in a modified Luciferase Immunoprecipitation System assay, we confirmed that both the truncated and full-length forms of the protein can bind to human IL-10R1. Truncated Bm5539 could inhibit human IL-10-driven phosphorylation of STAT3, thereby demonstrating that Bm5539 acts as an IL-10 antagonist, most likely through competitive binding to the receptor. We provide a structural basis for these observations using computational modeling and simulations. This parasite-encoded cytokine receptor antagonist provides an additional lens through which parasite-induced modulation of the host immune response can be examined.

Plasticity in structure and assembly of SARS-CoV-2 nucleocapsid protein.

Worldwide SARS-CoV-2 sequencing efforts track emerging mutations in its spike protein, as well as characteristic mutations in other viral proteins. Besides their epidemiological importance, the observed SARS-CoV-2 sequences present an ensemble of viable protein variants, and thereby a source of information on viral protein structure and function. Charting the mutational landscape of the nucleocapsid (N) protein that facilitates viral assembly, we observe variability exceeding that of the spike protein, with more than 86% of residues that can be substituted, on average by three to four different amino acids. However, mutations exhibit an uneven distribution that tracks known structural features but also reveals highly protected stretches of unknown function. One of these conserved regions is in the central disordered linker proximal to the N-G215C mutation that has become dominant in the Delta variant, outcompeting G215 variants without further spike or N-protein substitutions. Structural models suggest that the G215C mutation stabilizes conserved transient helices in the disordered linker serving as protein-protein interaction interfaces. Comparing Delta variant N-protein to its ancestral version in biophysical experiments, we find a significantly more compact and less disordered structure. N-G215C exhibits substantially stronger self-association, shifting the unliganded protein from a dimeric to a tetrameric oligomeric state, which leads to enhanced coassembly with nucleic acids. This suggests that the sequence variability of N-protein is mirrored by high plasticity of N-protein biophysical properties, which we hypothesize can be exploited by SARS-CoV-2 to achieve greater efficiency of viral assembly, and thereby enhanced infectivity.

Plasticity in structure and assembly of SARS-CoV-2 nucleocapsid protein.

Worldwide SARS-CoV-2 sequencing efforts track emerging mutations in its spike protein, as well as characteristic mutations in other viral proteins. Besides their epidemiological importance, the observed SARS-CoV-2 sequences present an ensemble of viable protein variants, and thereby a source of information on viral protein structure and function. Charting the mutational landscape of the nucleocapsid (N) protein that facilitates viral assembly, we observe variability exceeding that of the spike protein, with more than 86% of residues that can be substituted, on average by 3-4 different amino acids. However, mutations exhibit an uneven distribution that tracks known structural features but also reveals highly protected stretches of unknown function. One of these conserved regions is in the central disordered linker proximal to the N-G215C mutation that has become dominant in the Delta variant, outcompeting G215 variants without further spike or N-protein substitutions. Structural models suggest that the G215C mutation stabilizes conserved transient helices in the disordered linker serving as protein-protein interaction interfaces. Comparing Delta variant N-protein to its ancestral version in biophysical experiments, we find a significantly more compact and less disordered structure. N-G215C exhibits substantially stronger self-association, shifting the unliganded protein from a dimeric to a tetrameric oligomeric state, which leads to enhanced co-assembly with nucleic acids. This suggests that the sequence variability of N-protein is mirrored by high plasticity of N-protein biophysical properties, which we hypothesize can be exploited by SARS-CoV-2 to achieve greater efficiency of viral assembly, and thereby enhanced infectivity.

Synthesis, Biological Evaluation, and Molecular Modeling Studies of 3,4-Diarylpyrazoline Series of Compounds as Potent, Nonbrain Penetrant Antagonists of Cannabinoid-1 (CB1R) Receptor with Reduced Lipophilicity.

In the present report, we describe the synthesis and structure-activity relationships of novel "four-arm" dihydropyrazoline compounds designed as peripherally restricted antagonists of cannabinoid-1 receptor (CB1R). A series of racemic 3,4-diarylpyrazolines were synthesized and evaluated initially in CB1 receptor binding assays. The novel compounds, designed to limit brain penetrance and decreased lipophilicity, showed high affinity for CB1R and potent in vitro CB1R antagonist activities. Promising compounds with potent CB1R activity were evaluated in tissue distribution studies. Compounds 6a, 6f, and 7c showed limited brain penetrance attesting to its peripheral restriction. The 4S-enantiomer of these compounds further showed a stereoselective affinity for the CB1 receptor and behaved as inverse agonists. In vivo studies on food intake and body weight reduction in diet-induced obese (DIO) mice showed that these compounds could serve as potential leads for the development of selective CB1R antagonists with improved potency and peripheral restriction.

Microscopic mechanism of nanocrystal formation from solution by cluster aggregation and coalescence.

Solute-cluster aggregation and particle fusion have recently been suggested as alternative routes to the classical mechanism of nucleation from solution. The role of both processes in the crystallization of an aqueous electrolyte under controlled salt addition is here elucidated by molecular dynamics simulation. The time scale of the simulation allows direct observation of the entire crystallization pathway, from early events in the prenucleation stage to the formation of a nanocrystal in equilibrium with concentrated solution. The precursor originates in a small amorphous aggregate stabilized by hydration forces. The core of the nucleus becomes crystalline over time and grows by coalescence of the amorphous phase deposited at the surface. Imperfections of ion packing during coalescence promote growth of two conjoint crystallites. A parameter of order and calculated cohesive energies reflect the increasing crystalline order and stress relief at the grain boundary. Cluster aggregation plays a major role both in the formation of the nucleus and in the early stages of postnucleation growth. The mechanism identified shares common features with nucleation of solids from the melt and of liquid droplets from the vapor.