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Abstract Visual pigments are essential for converting light into electrical signals during vision. Composed of an opsin protein and a retinal-based chromophore, pigments in vertebrate rods (Rh1) and cones (Rh2) have different spectral sensitivities, with distinct peak absorption wavelengths determined by the shape and composition of the chromophore binding pocket. Despite advances in understanding Rh1 pigments such as bovine rhodopsin, the molecular basis of spectral shifts in Rh2 cone opsins has been less studied, particularly the E122Q mutation, which accounts for about half of the observed spectral shift in these pigments. In this study, we employed molecular modeling and quantum mechanical techniques to investigate the molecular mechanisms behind the spectral difference in blue-shifted Rh2-1 (absorption peak = 467 nm, 122Q) and green-shifted Rh2-4 (absorption peak = 505 nm, 122E) zebrafish cone opsins. We modeled the pigments 3D structures based on their sequences and conducted all-atom molecular dynamics simulations totaling 2 microseconds. Distance analysis of the trajectories identified three key sites: E113, E181, and E122. The E122Q mutation, previously known, validates our findings, while E181 and E113 are newly identified contributors. Structural analysis revealed key features with differing values that explain the divergent spectral sensitivities of Rh2-1 and Rh2-4: 1) chromophore atom fluctuations and C5-C6 torsion angle, 2) binding pocket volume, 3) hydration patterns, and 4) E113-chromophore interaction stability. Quantum mechanics further confirms the critical role of residue E181 in Rh2-1 and E122 in Rh2-4 for their spectral behavior. Our study provides new insights into the molecular determinants of spectral shifts in cone opsins, and we anticipate that it will serve as a starting point for a broader understanding of the functional diversity of visual pigments. 

Catenanes are a family of mechanically interlocked molecules that consist of molecular rings that can be interlocked to give linear, radial, or cyclic structures. Although chemists have pursued extended linear poly[n]catenane architectures for many decades, there still exists a fundamental gap between the synthesis of well-defined, linear oligomers and that of disperse polymers that are often produced as a mixture of architectures. Here, we report two convergent one-pot syntheses that “zip-tie” together two pre-made [3]catenanes by first using orthogonal metal templation with phenanthroline (Cu(I)) and terpyridine (Fe(II)) ligands. These pre-catenate complexes were subjected to a ring-closing metathesis step to afford discrete, linear [7]- and [8]catenanes. The successful synthesis and isolation of the discrete [7]- and [8]catenanes were confirmed using multiple methods of characterization. Because these record-setting linear [n]catenanes possess open phenanthroline metal-binding sites at each end, further expansion to all-interlocked linear poly[n]catenanes is a realistic proposition. 

Low-energy electrons dissolved in liquid ammonia or aqueous media are powerful reducing agents that promote challenging reduction reactions, but can also cause radiation damage to biological tissue. Knowledge of the underlying mechanistic processes remains incomplete, in particular with respect to the details and energetics of the electron transfer steps. Here, we show how ultraviolet (UV) photoexcitation of metal-ammonia clusters could be used to generate tunable low-energy electrons in situ. Specifically, we identified UV light-induced generation of spin-paired solvated dielectrons and their subsequent relaxation by an unconventional electron-transfer-mediated decay as an efficient low-energy electron source. The process is robust and straightforward to induce, with the prospect of improving our understanding of radiation damage and fostering mechanistic studies of solvated electron reduction reactions. 

It has been 49 years since the last discovery of a new virus family in the model yeastSaccharomyces cerevisiae. A large-scale screen to determine the diversity of double-stranded RNA (dsRNA) viruses inS.cerevisiaehas identified multiple novel viruses from the familyPartitiviridaethat have been previously shown to infect plants, fungi, protozoans, and insects. MostS.cerevisiaepartitiviruses (ScPVs) are associated with strains of yeasts isolated from coffee and cacao beans. The presence of partitiviruses was confirmed by sequencing the viral dsRNAs and purifying and visualizing isometric, non-enveloped viral particles. ScPVs have a typical bipartite genome encoding an RNA-dependent RNA polymerase (RdRP) and a coat protein (CP). Phylogenetic analysis of ScPVs identified three species of ScPV, which are most closely related to viruses of the genusCryspovirusfrom the mammalian pathogenic protozoanCryptosporidium parvum. Molecular modeling of the ScPV RdRP revealed a conserved tertiary structure and catalytic site organization when compared to the RdRPs of thePicornaviridae. The ScPV CP is the smallest so far identified in thePartitiviridaeand has structural homology with the CP of other partitiviruses but likely lacks a protrusion domain that is a conspicuous feature of other partitivirus particles. ScPVs were stably maintained during laboratory growth and were successfully transferred to haploid progeny after sporulation, which provides future opportunities to study partitivirus-host interactions using the powerful genetic tools available for the model organismS.cerevisiae. 

Salmonids are ideal models as many species follow a distinct developmental program from demersal eggs and a large yolk sac to hatching at an advanced developmental stage. Further, these economically important teleosts inhabit both marine- and freshwaters and experience diverse light environments during their life histories. At a genome level, salmonids have undergone a salmonid-specific fourth whole genome duplication event (Ss4R) compared to other teleosts that are already more genetically diverse compared to many non-teleost vertebrates. Thus, salmonids display phenotypically plastic visual systems that appear to be closely related to their anadromous migration patterns. This is most likely due to a complex interplay between their larger, more gene-rich genomes and broad spectrally enriched habitats; however, the molecular basis and functional consequences for such diversity is not fully understood. This study used advances in genome sequencing to identify the repertoire and genome organization of visual opsin genes (those primarily expressed in retinal photoreceptors) from six different salmonids [Atlantic salmon ( Salmo salar ), brown trout ( Salmo trutta ), Chinook salmon ( Oncorhynchus tshawytcha ), coho salmon ( Oncorhynchus kisutch ), rainbow trout ( Oncorhynchus mykiss ), and sockeye salmon ( Oncorhynchus nerka )] compared to the northern pike ( Esox lucius ), a closely related non-salmonid species. Results identified multiple orthologues for all five visual opsin classes, except for presence of a single short-wavelength-sensitive-2 opsin gene. Several visual opsin genes were not retained after the Ss4R duplication event, which is consistent with the concept of salmonid rediploidization. Developmentally, transcriptomic analyzes of Atlantic salmon revealed differential expression within each opsin class, with two of the long-wavelength-sensitive opsins not being expressed before first feeding. Also, early opsin expression in the retina was located centrally, expanding dorsally and ventrally as eye development progressed, with rod opsin being the dominant visual opsin post-hatching. Modeling by spectral tuning analysis and atomistic molecular simulation, predicted the greatest variation in the spectral peak of absorbance to be within the Rh2 class, with a ∼40 nm difference in λ max values between the four medium-wavelength-sensitive photopigments. Overall, it appears that opsin duplication and expression, and their respective spectral tuning profiles, evolved to maximize specialist color vision throughout an anadromous lifecycle, with some visual opsin genes being lost to tailor marine-based vision. 

For many species, vision is one of the most important sensory modalities for mediating essential tasks that include navigation, predation and foraging, predator avoidance, and numerous social behaviors. The vertebrate visual process begins when photons of the light interact with rod and cone photoreceptors that are present in the neural retina. Vertebrate visual photopigments are housed within these photoreceptor cells and are sensitive to a wide range of wavelengths that peak within the light spectrum, the latter of which is a function of the type of chromophore used and how it interacts with specific amino acid residues found within the opsin protein sequence. Minor differences in the amino acid sequences of the opsins are known to lead to large differences in the spectral peak of absorbance (i.e. the λmax value). In our prior studies, we developed a new approach that combined homology modeling and molecular dynamics simulations to gather structural information associated with chromophore conformation, then used it to generate statistical models for the accurate prediction of λmax values for photopigments derived from Rh1 and Rh2 amino acid sequences. In the present study, we test our novel approach to predict the λmax of phylogenetically distant Sws2 cone opsins. To build a model that can predict the λmax using our approach presented in our prior studies, we selected a spectrally-diverse set of 11 teleost Sws2 photopigments for which both amino acid sequence information and experimentally measured λmax values are known. The final first-order regression model, consisting of three terms associated with chromophore conformation, was sufficient to predict the λmax of Sws2 photopigments with high accuracy. This study further highlights the breadth of our approach in reliably predicting λmax values of Sws2 cone photopigments, evolutionary-more distant from template bovine RH1, and provided mechanistic insights into the role of known spectral tuning sites 

A growing number of computational tools have been developed to accurately and rapidly predict the impact of amino acid mutations on protein-protein relative binding affinities. Such tools have many applications, for example, designing new drugs and studying evolutionary mechanisms. In the search for accuracy, many of these methods employ expensive yet rigorous molecular dynamics simulations. By contrast, non-rigorous methods use less exhaustive statistical mechanics, allowing for more efficient calculations. However, it is unclear if such methods retain enough accuracy to replace rigorous methods in binding affinity calculations. This trade-off between accuracy and computational expense makes it difficult to determine the best method for a particular system or study. Here, eight non-rigorous computational methods were assessed using eight antibody-antigen and eight non-antibody-antigen complexes for their ability to accurately predict relative binding affinities (ΔΔG) for 654 single mutations. In addition to assessing accuracy, we analyzed the CPU cost and performance for each method using a variety of physico-chemical structural features. This allowed us to posit scenarios in which each method may be best utilized. Most methods performed worse when applied to antibody-antigen complexes compared to non-antibody-antigen complexes. Rosetta-based JayZ and EasyE methods classified mutations as destabilizing (ΔΔG < -0.5 kcal/mol) with high (83–98%) accuracy and a relatively low computational cost for non-antibody-antigen complexes. Some of the most accurate results for antibody-antigen systems came from combining molecular dynamics with FoldX with a correlation coefficient (r) of 0.46, but this was also the most computationally expensive method. Overall, our results suggest these methods can be used to quickly and accurately predict stabilizing versus destabilizing mutations but are less accurate at predicting actual binding affinities. This study highlights the need for continued development of reliable, accessible, and reproducible methods for predicting binding affinities in antibody-antigen proteins and provides a recipe for using current methods.