Protein Structure Modeling Research Articles

A Novel Variant in TUBB4B Causes Progressive Cone-Rod Dystrophy and Early Onset Sensorineural Hearing Loss.

Sensorineural hearing loss (SNHL) is a frequent manifestation of syndromic inherited retinal diseases (IRDs), exemplified by the very rare form of autosomal-dominant Leber congenital amaurosis with early onset deafness (LCAEOD; OMIM #617879). LCAEOD was first described in 2017 in four families segregating heterozygous missense mutations in TUBB4B, a gene encoding a β-tubulin isotype. To date, only eight more families with similar TUBB4B-associated sensorineural disease (SND) have been reported. Most cases harbored missense variants affecting the same amino acid (Arg391) and only three families segregated variants involving different residues (Tyr310, Arg390). We performed whole-exome sequencing and a full ophthalmological and audiological examination of the affected members in an Italian family segregating syndromic IRD with early onset deafness. We identified a novel, ultra-rare, disease-causing variant in TUBB4B (NM_006088.6:c.1049A>C) that replaces a highly conserved lysine with threonine at amino acid position 350. The functional impact of the Lys350Thr substitution was supported by protein structure modeling studies. The variant segregates in the family members presenting retinal disease with early onset SNHL. Detailed ophthalmological assessment of the affected subjects diagnosed a progressive cone-rod dystrophy. These findings expand the limited number of disease-causing TUBB4B variants, corroborating their association with SND forms, and suggest Lys350 is an important residue for β-tubulin function. Interestingly, our results demonstrate that TUBB4B mutations can cause cone-dominated retinal phenotypes.

Identification of AKNA Gene and Its Role for Genetic Susceptibility in Epithelial Ovarian Cancer

AKNA is identified as a gene that regulates inflammation, immune response, and Epithelial–Mesenchymal Transition (EMT), which plays an important role in the progression of epithelial ovarian cancer. In this study, we analyzed the genotype and allele distribution as well as 3D modeling of one of the AKNA rs10817595 (−1372 C>A). The distribution of genotypes and alleles was analyzed using the T-ARMS PCR method on 63 ovarian cancer samples and 65 controls. AKNA mRNA expression was analyzed using qRT-PCR on 35 low-grade and 28 high-grade samples. Fifteen low-grade and 12 high-grade samples were analyzed for AKNA protein levels using immunohistochemistry. A 3D model of protein structure was constructed using AlphaFold. Significant differences in AKNA protein levels were found. However, no significant correlation was found for relative AKNA mRNA expression with protein levels. This result is thought to be related to decreased immune system response, increased inflammation, and increased EMT in epithelial ovarian cancer. AKNA gene variant (−1372 C>A) can cause a decrease in mRNA and protein levels in the low-grade and high-grade groups, so it has the potential as a genetic susceptibility factor in epithelial ovarian cancer.

Conformationally adaptive therapeutic peptides for diseases caused by intrinsically disordered proteins (IDPs). New paradigm for drug discovery: Target the target, not the arrow.

The traditional model of protein structure determined by the amino acid sequence is today seriously challenged by the fact that approximately half of the human proteome is made up of proteins that do not have a stable 3D structure, either partially or in totality. These proteins, called intrinsically disordered proteins (IDPs), are involved in numerous physiological functions and are associated with severe pathologies, e.g. Alzheimer, Parkinson, Creutzfeldt-Jakob, amyotrophic lateral sclerosis (ALS), and type 2 diabetes. Targeting these proteins is challenging for two reasons: i) we need to preserve their physiological functions, and ii) drug design by molecular docking is not possible due to the lack of reliable starting conditions. Faced with this challenge, the solutions proposed by artificial intelligence (AI) such as AlphaFold are clearly unsuitable. Instead, we suggest an innovative approach consisting of mimicking, in short synthetic peptides, the conformational flexibility of IDPs. These peptides, which we call adaptive peptides, are derived from the domains of IDPs that become structured after interacting with a ligand. Adaptive peptides are designed with the aim of selectively antagonizing the harmful effects of IDPs, without targeting them directly but through selected ligands, without affecting their physiological properties. This "target the target, not the arrow" strategy is promised to open a new route to drug discovery for currently undruggable proteins.

Reconstructing NOD-like receptor alleles with high internal conservation in Podospora anserina using long-read sequencing.

NOD-like receptors (NLRs) are intracellular immune receptors that detect pathogen-associated cues and trigger defense mechanisms, including regulated cell death. In filamentous fungi, some NLRs mediate heterokaryon incompatibility, a self/non-self recognition process that prevents the vegetative fusion of genetically distinct individuals, reducing the risk of parasitism. The het-d and het-e NLRs in Podospora anserina are highly polymorphic incompatibility genes (het genes) whose products recognize different alleles of the het-c gene via a sensor domain composed of WD40 repeats. These repeats display unusually high sequence identity maintained by concerted evolution. However, some sites within individual repeats are hypervariable and under diversifying selection. Despite extensive genetic studies, inconsistencies in the reported WD40 domain sequence have hindered functional and evolutionary analyses. Here we demonstrate that the WD40 domain can be accurately reconstructed from long-read sequencing (Oxford Nanopore and PacBio) data, but not from Illumina-based assemblies. Functional alleles are usually formed by 11 highly conserved repeats, with different repeat combinations underlying the same phenotypic het-d and het-e incompatibility reactions. Protein structure models suggest that their WD40 domain folds into two 7-blade β-propellers composed of the highly conserved repeats, as well as three cryptic divergent repeats at the C-terminus. We additionally show that one particular het-e allele does not have an incompatibility reaction with common het-c alleles, despite being 11-repeats long. Our findings provide a robust foundation for future research into the molecular mechanisms and evolutionary dynamics of het NLRs, while also highlighting both the fragility and the flexibility of β-propellers as immune sensor domains.

Rational Modification of a Cross-Linker for Improved Flexible Protein Structure Modeling.

Chemical cross-linking/mass spectrometry (XL-MS) has emerged as a complementary tool for mapping interaction sites within protein networks as well as gaining moderate-resolution native structural insight with minimal interference. XL-MS technology mostly relies on chemoselective reactions (cross-linking) between protein residues and a linker. DSSO represents a versatile cross-linker for protein structure investigation and in-cell XL-MS. However, our assessment of its shelf life and batch purity revealed decomposition of DSSO in anhydrous solution via a retro-Michael reaction, which may reduce the active ingredient down to below 90%. To mitigate the occurrence of this degradative mechanism, we report the rational design and synthesis of DSSO-carbamate, which contains an inserted nitrogen atom in the DSSO backbone structure. This modification to DSSO yielded remarkably favorable stability against such decomposition, which translated to higher cross-link and monolink recovery when performing XL-MS on monomeric flexible proteins. Recently, XL-MS has been leveraged against AlphaFold2 and other protein structure prediction algorithms for improved prediction of flexible monomeric multiconformational proteins. To this end, we demonstrate that our novel cross-linker, termed DSSO-carbamate, generated more accurate protein structure predictions when combined with AlphaFold2, on account of its increased recovery of cross-links and monolinks, compared to DSSO. As such, DSSO-carbamate represents a useful addition to the XL-MS community, particularly for protein structure prediction.

Secondary Structure in Free and Assisted Modeling of Proteins with the Coarse-Grained UNRES Force Field.

Secondary structure is a solid scaffold on which the three-dimensional structure of a protein is built. Therefore, care must be taken to reproduce the secondary structure as accurately as possible in the simulations of protein systems. In this chapter, we summarize the physics-based energy terms that govern secondary-structure formation, the auxiliary restraints on secondary structure derived from bioinformatics and from the experimental data, and the role of those in the modeling of protein structures, dynamics, and thermodynamics with the physics-based coarse-grained UNRES force field. Examples illustrating the methodology discussed and further directions of development are presented.

Hepatitis B virus genotypes A1 and A2 have distinct replication phenotypes due to polymorphisms in the HBx gene.

HBV genotype A has two major subtypes, A1 (commonly in Africa) and A2 (commonly in Europe) with only 4% nucleotide differences. Individuals infected with these two subtypes appear to have different clinical manifestations and virologic features. Whether such a difference results from the virus or host has not been established. Using HBV generated from molecule clones of subtypes A1 and A2 in cell culture (HBVcc), we demonstrate that HBVcc of subtypes A1 and A2 can be passaged in vitro and in vivo and respond equally well to human IFN-α treatment. HBVcc passaged in human liver chimeric mice (HBVmp) infected human hepatocytes more efficiently than that of the original HBVcc. Subtype A2 showed a much higher viral replication level than that of subtype A1. Mechanistic investigations using constructs with chimeric A1/A2 sequences and specific mutations indicated that subtype A2 has an inherently higher replication phenotype due to specific polymorphisms in the HBx gene resulting in amino acid variations. Studies of HBx expression demonstrated that A1 HBx is expressed at a much lower level than that of A2 HBx. Mutagenesis studies identified two HBx amino acid variations responsible for the observed phenotypic difference. Using AlphaFold2, we generated structural models of HBx proteins of A1 and A2. Superposition of the two models reveal that the overall structural motifs are similarly aligned, except for the C-terminal peptides diverging between the A1 and A2 models, possibly explaining their functional difference. In conclusion, using various in vitro and in vivo models, here we show that subtype A2 has an inherently higher replication phenotype due to polymorphisms in HBx that result in possible differences in structure and expression level of the two subtype HBx proteins. This genotypic difference potentially explains the reported clinical differences between the two subtypes as well as providing a previously unrecognized association between viral sequence variations and clinical manifestations of HBV infection in humans.

Beyond AlphaFold2: The Impact of AI for the Further Improvement of Protein Structure Prediction.

Protein structure prediction is fundamental to molecular biology and has numerous applications in areas such as drug discovery and protein engineering. Machine learning techniques have greatly advanced protein 3D modeling in recent years, particularly with the development of AlphaFold2 (AF2), which can analyze sequences of amino acids and predict 3D structures with near experimental accuracy. Since the release of AF2, numerous studies have been conducted, either using AF2 directly for large-scale modeling or building upon the software for other use cases. Many reviews have been published discussing the impact of AF2 in the field of protein bioinformatics, particularly in relation to neural networks, which have highlighted what AF2 can and cannot do. It is evident that AF2 and similar approaches are open to further development and several new approaches have emerged, in addition to older refinement approaches, for improving the quality of predictions. Here we provide a brief overview, aimed at the general biologist, of how machine learning techniques have been used for improvement of 3D models of proteins following AF2, and we highlight the impacts of these approaches. In the most recent experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP15), the most successful groups all developed their own tools for protein structure modeling that were based at least in some part on AF2. This improvement involved employing techniques such as generative modeling, changing parameters such as dropout to generate more AF2 structures, and data-driven approaches including using alternative templates and MSAs.

Fish gut symbiotic bacterium Bacillus thuringiensis: RSM optimization for its extracellular lipase enzyme production, lipase-protein purification, characterization, and docking analysis.

Lipase enzymes play a vital role in digestion and nutrient metabolism in host organisms, with symbiotic bacteria producing abundant enzymes, carbohydrates, vitamins, and other nutrients. This study aimed to isolate, identify, and screen lipase-producing bacteria from the gut of Systomus sarana, optimize enzyme production using Response Surface Methodology (RSM), and characterize the extracted lipase protein. A total of 11 bacterial strains were isolated and identified through 16S rRNA sequencing. Among these, Bacillus thuringiensis (SS5) exhibited the highest enzyme index (5.46mm) and crude enzyme activity (109U/mL). Using RSM optimization, growth conditions were refined to pH7.5, temperature 35°C, incubation time 30 h, with 2.3% peptone and 2.34% lactose, resulting in enhanced lipase production of 210U/mL. The partially purified protein (~30kDa) was characterized by SDS-PAGE and FTIR spectroscopy, revealed functional groups such as acids, aliphatic amines, and aromatics. MALDI-TOF/MS analysis identified eight peptides, with one major peptide sequence (IYVYYSDIMHVMNTMGQR). The modelled protein structure based on 259 amino acids was validated through homology modeling. Molecular docking studies demonstrated strong binding affinities (-7.36 to -8.95kcal/mol) between the lipase protein and fatty acids (linoleic acid, linolenic acid, oleic acid, palmitic acid) as well as tripalmitin. These findings highlight the potential of fish gut-derived Bacillus thuringiensis as a valuable source of lipase enzymes for industrial applications such as bioremediation and biodiesel production. Further exploration of these bacterial enzymes within their native ecosystems is recommended to expand their biotechnological utility.

Mean-Field Coupling Between Local Interactions in Proteins in Relation to Chirality, Secondary, and Supersecondary Structure Formation, and Allostery.

Coarse graining is usually considered as a tool to extend the time and size scale of simulations. However, leaving out the atomistic details to keep their fingerprints in a coarse-grained model also enables us to understand better structure formation and dynamics. In this chapter, by using our scale-consistent theory of coarse graining, we demonstrate that the coarse-grained terms corresponding to the coupling between local conformational states of amino-acid residues explain secondary-structure propagation along polypeptide backbone to stabilize -helices and -strands in proteins and direct the loops preceding and following such segments of protein structure. These and related correlations are probably the still missing terms in both physics- and knowledge-based approaches to protein-structure modeling, including AlphaFold. We also show that the chirality of coarse-grained torsional potentials and, thereby, that of polypeptide backbone emerge from putting together achiral site-based torsional potentials given the phase shift due to residue chirality, and that the improper-torsional potentials that correspond to the coupling between local conformational states of the sites adjacent to a given -carbon atom enable us to model amino-acid-residue enantiomerization.

Clinical characteristics and genetic analysis of four pediatric patients with Kleefstra syndrome

BackgroundKleefstra syndrome spectrum (KLEFS) is an autosomal dominant disorder that can lead to intellectual disability and autism spectrum disorders. KLEFS encompasses Kleefstra syndrome-1 (KLEFS1) and Kleefstra syndrome-2 (KLEFS2), with KLEFS1 accounting for more than 75%. However, limited information is available regarding KLEFS2. KLEFS1 is caused by a subtelomeric chromosomal abnormality resulting in either deletion at the end of the long arm of chromosome 9, which contains the EHMT1 gene, or by variants in the EHMT1 gene and the KMT2C gene that cause KLEFS2.MethodsThis study was a retrospective analysis of clinical data from four patients with KLEFS. Exome sequencing (ES) and Sanger sequencing techniques were used to identify and validate the candidate variants, facilitating the analysis of genotype‒phenotype correlations of the EHMT1 and KMT2C genes. Protein structure modeling was performed to evaluate the effects of the variants on the protein’s three-dimensional structure. In addition, real-time quantitative reverse transcription‒polymerase chain reaction (RT‒qPCR) and western blotting were used to examine the protein and mRNA levels of the KMT2C gene.ResultsTwo patients with KLEFS1 were identified: one with a novel variant (c.2382 + 1G > T) and the other with a previously reported variant (c.2426 C > T, p.Pro809Leu) in the EHMT1 gene. A De novo deletion at the end of the long arm of chromosome 9 was also reported. Furthermore, a patient with KLEFS2 was identified with a novel variant in the KMT2C gene (c.568 C > T, p.Arg190Ter). The RT‒qPCR and western blot results revealed that the expression of the KMT2C gene was downregulated in the KLEFS2 sample.ConclusionThis study contributes to the understanding of both KLEFS1 and KLEFS2 by identifying novel variants in EHMT1 and KMT2C genes, thereby expanding the variant spectrum. Additionally, we provide the first evidence of how a KMT2C variant leads to decreased gene and protein expression, enhancing our understanding of the molecular mechanisms underlying KLEFS2. Based on these findings, children exhibiting developmental delay, hypotonia, distinctive facial features, and other neurodevelopmental abnormalities should be considered for ES to ensure early intervention and treatment.

Protein Structural Modeling and Transport Thermodynamics Reveal That Plant Cation-Chloride Cotransporters Mediate Potassium-Chloride Symport.

Plant cation-chloride cotransporters (CCCs) are proposed to be Na+-K+-2Cl- transporting membrane proteins, although evolutionarily, they associate more closely with K+-Cl- cotransporters (KCCs). Here, we investigated grapevine (Vitis vinifera L.) VvCCC using 3D protein modeling, bioinformatics, and electrophysiology with a heterologously expressed protein. The 3D protein modeling revealed that the signatures of ion binding sites in plant CCCs resembled those of animal KCCs, which was supported by phylogenomic analyses and ancestral sequence reconstruction. The conserved features of plant CCCs and animal KCCs included predicted K+ and Cl--binding sites and the absence of a Na+-binding site. Measurements with VvCCC-injected Xenopus laevis oocytes with VvCCC localizing to plasma membranes indicated that the oocytes had depleted intracellular Cl- and net 86Rb fluxes, which agreed with thermodynamic predictions for KCC cotransport. The 86Rb uptake by VvCCC-injected oocytes was Cl--dependent, did not require external Na+, and was partially inhibited by the non-specific CCC-blocker bumetanide, implying that these properties are typical of KCC transporters. A loop diuretic-insensitive Na+ conductance in VvCCC-injected oocytes may account for earlier observations of Na+ uptake by plant CCC proteins expressed in oocytes. Our data suggest plant CCC membrane proteins are likely to function as K+-Cl- cotransporters, which opens the avenues to define their biophysical properties and roles in plant physiology.

Dominance of dengue virus serotype-2 in Pakistan (2023-2024): Molecular characterization of the envelope gene and exploration of antiviral targets.

Dengue virus infection, caused by a single positive-stranded RNA virus from the Flaviviridae family, represents a significant public health challenge in tropical and subtropical regions. This virus has four serotypes (DENV-1, 2, 3, and 4), primarily transmitted by Aedes mosquitoes. Despite extensive research, effective antiviral treatments and vaccines remain elusive due to the viral diversity and the complex mechanisms such as antibody-dependent enhancement (ADE). In the current study, NS1-positive serum samples from dengue cases in Pakistan (2023-2024), were analyzed to determine the predominant serotype and characterize the envelope (E) gene for further exploration of antiviral targets. Out of 100 samples, 63 (63%) tested positive for DENV-2, indicating its predominance during this period, while two samples showed mixed infections with DENV-2 and DENV-3. The envelope gene was successfully amplified using nested PCR, validated through gel electrophoresis and sanger sequencing. Phylogenetic analysis revealed high similarity of the DENV-2 isolates to strains from China and India. Computational modeling of the envelope protein structure identified potential antiviral binding sites and further molecular docking studies suggested that specific antiviral compounds like Arbidol and Quercetin can inhibit early steps in viral infection. Additionally, BepiPred-3.0 predicted several B-cell epitopes, which could be useful for vaccine development. These findings enhance our understanding of dengue epidemiology in Pakistan and contribute to the development of targeted antiviral therapies, potentially informing future vaccination strategies and outbreak management.

Updated resources for exploring experimentally-determined PDB structures and Computed Structure Models at the RCSB Protein Data Bank.

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB, RCSB.org), the US Worldwide Protein Data Bank (wwPDB, wwPDB.org) data center for the global PDB archive, provides access to the PDB data via its RCSB.org research-focused web portal. We report substantial additions to the tools and visualization features available at RCSB.org, which now delivers more than 227000 experimentally determined atomic-level three-dimensional (3D) biostructures stored in the global PDB archive alongside more than 1 million Computed Structure Models (CSMs) of proteins (including models for human, model organisms, select human pathogens, crop plants and organisms important for addressing climate change). In addition to providing support for 3D structure motif searches with user-provided coordinates, new features highlighted herein include query results organized by redundancy-reduced Groups and summary pages that facilitate exploration of groups of similar proteins. Newly released programmatic tools are also described, as are enhanced training opportunities.

Packaging "vegetable oils": Insights into plant lipid droplet proteins.

Plant neutral lipids, also known as "vegetable oils", are synthesized within the endoplasmic reticulum (ER) membrane and packaged into subcellular compartments called lipid droplets (LDs) for stable storage in the cytoplasm. The biogenesis, modulation, and degradation of cytoplasmic LDs in plant cells are orchestrated by a variety of proteins localized to the ER, LDs, and peroxisomes. Recent studies of these LD-related proteins have greatly advanced our understanding of LDs not only as steady oil depots in seeds but also as dynamic cell organelles involved in numerous physiological processes in different tissues and developmental stages of plants. In the past 2 decades, technology advances in proteomics, transcriptomics, genome sequencing, cellular imaging and protein structural modeling have markedly expanded the inventory of LD-related proteins, provided unprecedented structural and functional insights into the protein machinery modulating LDs in plant cells, and shed new light on the functions of LDs in nonseed plant tissues as well as in unicellular algae. Here, we review critical advances in revealing new LD proteins in various plant tissues, point out structural and mechanistic insights into key proteins in LD biogenesis and dynamic modulation, and discuss future perspectives on bridging our knowledge gaps in plant LD biology.

Structural Evaluation of Interleukin-19 Cytokine and Interleukin-19-Bound Receptor Complex Using Computational Immuno-Engineering Approach

Interleukin 19 (IL-19) is an anti-inflammatory cytokine that belongs to the IL-10 family, where IL-20 and IL-24 also exist. While IL-19 and IL-20 share some comparable structural folds, there are certain structural divergences in their N-terminal ends. To date, there are no reported IL-19 receptors; although, it has been suggested in the literature that IL-19 would bind to lL-20 receptor (IL-20R) and trigger the JAK-STAT signaling pathways. The present report examines the structure of the IL-19 cytokine and its receptor complex using a computational approach. Specifically, the postulated modes of interactions for IL-20R as an IL-19 receptor are examined on the basis of a set of computational findings. The author has used molecular docking and molecular dynamics simulation to generate a 3D model for the IL-19 complex with IL-20R. When a protein’s crystal structure is not available in the literature, predictive modeling is often employed to determine the protein’s 3D structure. The model assessment can be based on various factors, which include stability analysis using RMSD calculations, tracking changes in time-based secondary structures and the associated Gibbs energies, ΔG. Since one model complex (referred to as model A throughout this paper) can be used as a working hypothesis for future experiments, this structure has been explored here in detail to check its stability, subunit interfaces, and binding residues. The information gathered in this approach can potentially help to design specific experiments to test the validity of the model protein structure. Additionally, the results of this research should be relevant for understanding anti-inflammatory mechanisms and, eventually, could contribute to the efforts for therapeutic developments and targeted therapy.

Identifying the minimal sets of distance restraints for FRET-assisted protein structural modeling.

Proteins naturally occur in crowded cellular environments and interact with other proteins, nucleic acids, and organelles. Since most previous experimental protein structure determination techniques require that proteins occur in idealized, non-physiological environments, the effects of realistic cellular environments on protein structure are largely unexplored. Recently, Förster resonance energy transfer (FRET) has been shown to be an effective experimental method for investigating protein structure in vivo. Inter-residue distances measured in vivo can be incorporated as restraints in molecular dynamics (MD) simulations to model protein structural dynamics in vivo. Since most FRET studies only obtain inter-residue separations for a small number of amino acid pairs, it is important to determine the minimum number of restraints in the MD simulations that are required to achieve a given root-mean-square deviation (RMSD) from the experimental structural ensemble. Further, what is the optimal method for selecting these inter-residue restraints? Here, we implement several methods for selecting the most important FRET pairs and determine the number of pairs that are needed to induce conformational changes in proteins between two experimentally determined structures. We find that enforcing only a small fraction of restraints, , where is the number of amino acids, can induce the conformational changes. These results establish the efficacy of FRET-assisted MD simulations for atomic scale structural modeling of proteins in vivo.

Identification of novel ABCB4 variants and genotype-phenotype correlation in progressive familial intrahepatic cholestasis type 3

Progressive familial intrahepatic cholestasis type 3 (PFIC3) is a severe hepatic disorder characterized by cholestasis. Elucidating the genotype-phenotype correlations and expanding the mutational spectrum of the ABCB4 gene are crucial for enhancing diagnostic accuracy and therapeutic strategies.Clinical and genetic data from 2 original PFIC3 patients from our institution, along with 118 additional cases identified through a comprehensive literature review, were integrated for a comprehensive analysis. The study included statistical analysis of clinical information, genetic analysis, multi-species sequence alignment, protein structure modeling, and pathogenicity assessment. Machine learning techniques were applied to identify genotype-phenotype relationships. We identified three novel ABCB4 mutations: two missense mutations (c.904G > T and c.2493G > C) and one splicing mutation (c.1230 + 1G > A). Homozygous mutations were associated with significantly earlier disease onset compared to compound heterozygous mutations (p < 0.0001). Missense mutations were predominant (76.9%), with Exon 7 being the most frequently affected region. A random forest model indicated that Exon 10 had the highest feature importance score (9.9%). Liver transplantation remains the most effective treatment modality for PFIC3. This investigation broadens the known mutation spectrum of the ABCB4 gene and identifies key variant sites associated with clinical manifestations. These insights lay a foundation for early diagnosis, optimal treatment selection, and further research into PFIC3.

Structural Model of Bacteriophage P22 Scaffolding Protein in a Procapsid by Magic-Angle Spinning NMR.

Icosahedral dsDNA viruses such as the tailed bacteriophages and herpesviruses have a conserved pathway to virion assembly that is initiated from a scaffolding protein driven procapsid formation. The dsDNA is actively packaged into procapsids, which undergo complex maturation reactions to form infectious virions. In bacteriophage P22, scaffolding protein (SP) directs the assembly of coat proteins into procapsids that have a T=7 icosahedral arrangement, en route to the formation of the mature P22 capsid. Other than the C-terminal helix-turn-helix involved in interaction with coat protein, the structure of the P22 303 amino acid scaffolding protein within the procapsid is not understood. Here, we present a structural model of P22 scaffolding protein encapsulated within the 23 MDa procapsid determined by magic angle spinning NMR spectroscopy. We took advantage of the 10-fold sensitivity gains afforded by the novel CPMAS CryoProbe to establish the secondary structure of P22 scaffolding protein and employed 19 F MAS NMR experiments to probe its oligomeric state in the procapsid. Our results indicate that the scaffolding protein has both α-helical and disordered segments and forms a trimer of dimers when bound to the procapsid lattice. This work provides the first structural information for P22 SP beyond the C-terminal helix-turn-helix and demonstrates the power of MAS NMR to understand higher-order viral protein assemblies involving structural components that are inaccessible to other structural biology techniques.

Jumping through hoops: Structural rearrangements and accelerated mutation rates on Dendrodorididae (Mollusca: Nudibranchia) mitogenomes rumble their evolution

The systematics of the family Dendrodorididae, with only three valid genera, is a challenge for integrative taxonomists. Its members lack hard structures for morphological comparisons and their mitochondrial and nuclear markers provide contradictory phylogenetic signals, making phylogenetic reconstructions difficult. This molecular discordance has been hypothesized to be the result of nuclear pseudogenes or exogenous contamination. However, these hypotheses have not been tested. Here, we assembled the first genome drafts of seven Dendrodorididae species to investigate the evolutionary processes of this family. Two of the mitogenomes displayed an identical structural rearrangement involving the translocation of three coding genes and five tRNAs, described for the first time in nudibranchs. In addition, we found particularly high dN and dN/dS values and multiple insertions and deletions on the mitochondrial genes of smooth Dendrodoris. In contrast, nuclear single-copy ortholog genes showed no such mutational differences. Models of protein structures from mitochondrial genes are conserved, suggesting conserved functionality. Phylogenies using mitogenomic and nuclear data showed that species with rearranged mitogenomes form a clade, although Dendrodorididae relationships remained unresolved. The present study provides novel evidence for accelerated mutation rates in the mitogenomes of Dendrodorididae, which presumably have implications on respiratory adaptation, and highlights the importance of using genomic data to unveil rare evolutionary processes, crucial for correctly inferring phylogenies.