In Vivo Mapping of Eukaryotic RNA Interactomes Reveals Principles of Higher-Order Organization and Regulation.

Identifying pairwise RNA-RNA interactions is key to understanding how RNAs fold and interact with other RNAs inside the cell. We present a high-throughput approach, sequencing of psoralen crosslinked, ligated, and selected hybrids (SPLASH), that maps pairwise RNA interactions in vivo with high sensitivity and specificity, genome-wide. Applying SPLASH to human and yeast transcriptomes revealed the diversity and dynamics of thousands of long-range intra- and intermolecular RNA-RNA interactions. Our analysis highlighted key structural features of RNA classes, including the modular organization of mRNAs, its impact on translation and decay, and the enrichment of long-range interactions in noncoding RNAs. Additionally, intermolecular mRNA interactions were organized into network clusters and were remodeled during cellular differentiation. We also identified hundreds of known and new snoRNA-rRNA binding sites, expanding our knowledge of rRNA biogenesis. These results highlight the underexplored complexity of RNA interactomes and pave the way to better understanding how RNA organization impacts biology.

The role of gelsolin domain 3 in familial amyloidosis (Finnish type).

In the disease familial amyloidosis, Finnish type (FAF), also known as AGel amyloidosis (AGel), the mechanism by which point mutations in the calcium-regulated actin-severing protein gelsolin lead to furin cleavage is not understood in the intact protein. Here, we provide a structural and biochemical characterization of the FAF variants. X-ray crystallography structures of the FAF mutant gelsolins demonstrate that the mutations do not significantly disrupt the calcium-free conformations of gelsolin. Small-angle X-ray-scattering (SAXS) studies indicate that the FAF calcium-binding site mutants are slower to activate, whereas G167R is as efficient as the wild type. Actin-regulating studies of the gelsolins at the furin cleavage pH (6.5) show that the mutant gelsolins are functional, suggesting that they also adopt relatively normal active conformations. Deletion of gelsolin domains leads to sensitization to furin cleavage, and nanobody-binding protects against furin cleavage. These data indicate instability in the second domain of gelsolin (G2), since loss or gain of G2-stabilizing interactions impacts the efficiency of cleavage by furin. To demonstrate this principle, we engineered non-FAF mutations in G3 that disrupt the G2-G3 interface in the calcium-activated structure. These mutants led to increased furin cleavage. We carried out molecular dynamics (MD) simulations on the FAF and non-FAF mutant G2-G3 fragments of gelsolin. All mutants showed an increase in the distance between the center of masses of the 2 domains (G2 and G3). Since G3 covers the furin cleavage site on G2 in calcium-activated gelsolin, this suggests that destabilization of this interface is a critical step in cleavage.

Topology independent comparison of RNA 3D structures using the CLICK algorithm.

RNA molecules are attractive therapeutic targets because non-coding RNA molecules have increasingly been found to play key regulatory roles in the cell. Comparing and classifying RNA 3D structures yields unique insights into RNA evolution and function. With the rapid increase in the number of atomic-resolution RNA structures, it is crucial to have effective tools to classify RNA structures and to investigate them for structural similarities at different resolutions. We previously developed the algorithm CLICK to superimpose a pair of protein 3D structures by clique matching and 3D least squares fitting. In this study, we extend and optimize the CLICK algorithm to superimpose pairs of RNA 3D structures and RNA-protein complexes, independent of the associated topologies. Benchmarking Rclick on four different datasets showed that it is either comparable to or better than other structural alignment methods in terms of the extent of structural overlaps. Rclick also recognizes conformational changes between RNA structures and produces complementary alignments to maximize the extent of detectable similarity. Applying Rclick to study Ribonuclease III protein correctly aligned the RNA binding sites of RNAse III with its substrate. Rclick can be further extended to identify ligand-binding pockets in RNA. A web server is developed at http://mspc.bii.a-star.edu.sg/minhn/rclick.html.

Designing dual inhibitors of Mdm2/MdmX: Unexpected coupling of water with gatekeeper Y100/99.

Mdm2 and MdmX share high structural similarity in their N-terminal domains, yet dual inhibitors are challenging to design due to differences in the conformations of the binding pockets, and notably of the proposed gatekeeper residue, Y100/99. Analysis of crystal structures and molecular dynamics (MD) simulations of complexes of Mdm2 and MdmX resulted in the identification of a water molecule with a long residence time that appears to be modulated by the conformation of Y100/99. These observations lead us to speculate that dual inhibitors either (i) stabilize both Mdm2 and MdmX with Y100/99 in the open conformation typically seen in complexes of Mdm2 with p53, or (ii) the dual inhibitors are agnostic to the conformation of Y100/99. The recently developed potent dual inhibitory stapled peptide Atsp7041 appears to be agnostic to the conformation of the gatekeeper residue. Proteins 2017; 85:1493-1506. © 2017 Wiley Periodicals, Inc.

Tertiary Element Interaction in HIV-1 TAR.

HIV-1 replication requires binding to occur between Trans-activation Response Element (TAR) RNA and the TAT protein. This TAR-TAT binding depends on the conformation of TAR, and therapeutic development has attempted to exploit this dynamic behavior. Here we simulate TAR dynamics in the context of mutations inhibiting TAR binding. We find that two tertiary elements, the apical loop and the bulge, can interact directly, and this interaction may be linked to the affinity of TAR for TAT.

R248Q mutation--Beyond p53-DNA binding.

R248 in the DNA binding domain (DBD) of p53 interacts directly with the minor groove of DNA. Earlier nuclear magnetic resonance (NMR) studies indicated that the R248Q mutation resulted in conformation changes in parts of DBD far from the mutation site. However, how information propagates from the mutation site to the rest of the DBD is still not well understood. We performed a series of all-atom molecular dynamics (MD) simulations to dissect sterics and charge effects of R248 on p53-DBD conformation: (i) wild-type p53 DBD; (ii) p53 DBD with an electrically neutral arginine side-chain; (iii) p53 DBD with R248A; (iv) p53 DBD with R248W; and (v) p53 DBD with R248Q. Our results agree well with experimental observations of global conformational changes induced by the R248Q mutation. Our simulations suggest that both charge- and sterics are important in the dynamics of the loop (L3) where the mutation resides. We show that helix 2 (H2) dynamics is altered as a result of a change in the hydrogen bonding partner of D281. In turn, neighboring L1 dynamics is altered: in mutants, L1 predominantly adopts the recessed conformation and is unable to interact with the major groove of DNA. We focused our attention the R248Q mutant that is commonly found in a wide range of cancer and observed changes at the zinc-binding pocket that might account for the dominant negative effects of R248Q. Furthermore, in our simulations, the S6/S7 turn was more frequently solvent exposed in R248Q, suggesting that there is a greater tendency of R248Q to partially unfold and possibly lead to an increased aggregation propensity. Finally, based on the observations made in our simulations, we propose strategies for the rescue of R248Q mutants.

How does a hydrocarbon staple affect peptide hydrophobicity?

Water is essential for the proper folding of proteins and the assembly of protein-protein/ligand complexes. How water regulates complex formation depends on the chemical and topological details of the interface. The dynamics of water in the interdomain region between an E3 ubiquitin ligase (MDM2) and three different peptides derived from the tumor suppressor protein p53 are studied using molecular dynamics. The peptides show bimodal distributions of interdomain water densities across a range of distances. The addition of a hydrocarbon chain to rigidify the peptides (in a process known as stapling) results in an increase in average hydrophobicity of the peptide-protein interface. Additionally, the hydrophobic staple shields a network of water molecules, kinetically stabilizing a water chain hydrogen-bonded between the peptide and MDM2. These properties could result in a decrease in the energy barrier associated with dehydrating the peptide-protein interface, thereby regulating the kinetics of peptide binding.

Modeling and design by hierarchical natural moves.

We develop a unique algorithm implemented in the program MOSAICS (Methodologies for Optimization and Sampling in Computational Studies) that is capable of nanoscale modeling without compromising the resolution of interest. This is achieved by modeling with customizable hierarchical degrees of freedom, thereby circumventing major limitations of conventional molecular modeling. With the emergence of RNA-based nanotechnology, large RNAs in all-atom representation are used here to benchmark our algorithm. Our method locates all favorable structural states of a model RNA of significant complexity while improving sampling accuracy and increasing speed many fold over existing all-atom RNA modeling methods. We also modeled the effects of sequence mutations on the structural building blocks of tRNA-based nanotechnology. With its flexibility in choosing arbitrary degrees of freedom as well as in allowing different all-atom energy functions, MOSAICS is an ideal tool to model and design biomolecules of the nanoscale.

Clustering to identify RNA conformations constrained by secondary structure.

RNA often folds hierarchically, so that its sequence defines its secondary structure (helical base-paired regions connected by single-stranded junctions), which subsequently defines its tertiary fold. To preserve base-pairing and chain connectivity, the three-dimensional conformations that RNA can explore are strongly confined compared to when secondary structure constraints are not enforced. Using three examples, we studied how secondary structure confines and dictates an RNA's preferred conformations. We made use of Macromolecular Conformations by SYMbolic programming (MC-Sym) fragment assembly to generate RNA conformations constrained by secondary structure. Then, to understand the correlations between different helix placements and orientations, we robustly clustered all RNA conformations by employing unique methods to remove outliers and estimate the best number of conformational clusters. We observed that the preferred conformation (as judged by largest cluster size) for each type of RNA junction molecule tested is consistent with its biological function. Further, the improved quality of models in our pruned datasets facilitates subsequent discrimination using scoring functions based either on statistical analysis (knowledge based) or experimental data.

Cluster-based radiomics reveal spatial heterogeneity of bevacizumab response for treatment of radiotherapy-induced cerebral necrosis.

Background: Bevacizumab is used in the treatment of radiation necrosis (RN), which is a debilitating toxicity following head and neck radiotherapy. However, there is no biomarker to predict if a patient would respond to bevacizumab. Purpose: We aimed to develop a cluster-based radiomics approach to characterize the spatial heterogeneity of RN and map their responses to bevacizumab. Methods: 118 consecutive nasopharyngeal carcinoma patients diagnosed with RN were enrolled. We divided 152 lesions from the patients into 101 for training, and 51 for validation. We extracted voxel-level radiomics features from each lesion segmented on T1-weighted+contrast and T2 FLAIR sequences of pre- and post-bevacizumab magnetic resonance images, followed by a three-step analysis involving individual- and population-level clustering, before delta-radiomics to derive five radiomics clusters within the lesions. We tested the association of each cluster with response to bevacizumab and developed a clinico-radiomics model using clinical predictors and cluster-specific features. Results: 71 (70.3%) and 34 (66.7%) lesions had responded to bevacizumab in the training and validation datasets, respectively. Two radiomics clusters were spatially mapped to the edema region, and the volume changes were significantly associated with bevacizumab response (OR:11.12 [95% CI: 2.54-73.47], P = 0.004; and 1.63[1.07-2.78], P = 0.042). The combined clinico-radiomics model based on textural features extracted from the most significant cluster improved the prediction of bevacizumab response, compared with a clinical-only model (AUC:0.755 [0.645-0.865] to 0.852 [0.764-0.940], training; 0.708 [0.554-0.861] to 0.816 [0.699-0.933], validation). Conclusion: Our radiomics approach yielded intralesional resolution, enabling a more refined feature selection for predicting bevacizumab efficacy in the treatment of RN.

Fully differentiable coarse-grained and all-atom knowledge-based potentials for RNA structure evaluation.

RNA molecules play integral roles in gene regulation, and understanding their structures gives us important insights into their biological functions. Despite recent developments in template-based and parameterized energy functions, the structure of RNA--in particular the nonhelical regions--is still difficult to predict. Knowledge-based potentials have proven efficient in protein structure prediction. In this work, we describe two differentiable knowledge-based potentials derived from a curated data set of RNA structures, with all-atom or coarse-grained representation, respectively. We focus on one aspect of the prediction problem: the identification of native-like RNA conformations from a set of near-native models. Using a variety of near-native RNA models generated from three independent methods, we show that our potential is able to distinguish the native structure and identify native-like conformations, even at the coarse-grained level. The all-atom version of our knowledge-based potential performs better and appears to be more effective at discriminating near-native RNA conformations than one of the most highly regarded parameterized potential. The fully differentiable form of our potentials will additionally likely be useful for structure refinement and/or molecular dynamics simulations.

Electrostatics of nucleic acid folding under conformational constraint.

RNA folding is enabled by interactions between the nucleic acid and its ion atmosphere, the mobile sheath of aqueous ions that surrounds and stabilizes it. Understanding the ion atmosphere requires the interplay of experiment and theory. However, even an apparently simple experiment to probe the ion atmosphere, measuring the dependence of DNA duplex stability upon ion concentration and identity, suffers from substantial complexity, because the unfolded ensemble contains many conformational states that are difficult to treat accurately with theory. To minimize this limitation, we measured the unfolding equilibrium of a DNA hairpin using a single-molecule optical trapping assay, in which the unfolded state is constrained to a limited set of elongated conformations. The unfolding free energy increased linearly with the logarithm of monovalent cation concentration for several cations, such that smaller cations tended to favor the folded state. Mg(2+) stabilized the hairpin much more effectively at low concentrations than did any of the monovalent cations. Poisson-Boltzmann theory captured trends in hairpin stability measured for the monovalent cation titrations with reasonable accuracy, but failed to do so for the Mg(2+) titrations. This finding is consistent with previous work, suggesting that Poisson-Boltzmann and other mean-field theories fail for higher valency cations where ion-ion correlation effects may become significant. The high-resolution data herein, because of the straightforward nature of both the folded and the unfolded states, should serve as benchmarks for the development of more accurate electrostatic theories that will be needed for a more quantitative and predictive understanding of nucleic acid folding.

Dissecting electrostatic screening, specific ion binding, and ligand binding in an energetic model for glycine riboswitch folding.

Riboswitches are gene-regulating RNAs that are usually found in the 5'-untranslated regions of messenger RNA. As the sugar-phosphate backbone of RNA is highly negatively charged, the folding and ligand-binding interactions of riboswitches are strongly dependent on the presence of cations. Using small angle X-ray scattering (SAXS) and hydroxyl radical footprinting, we examined the cation dependence of the different folding stages of the glycine-binding riboswitch from Vibrio cholerae. We found that the partial folding of the tandem aptamer of this riboswitch in the absence of glycine is supported by all tested mono- and divalent ions, suggesting that this transition is mediated by nonspecific electrostatic screening. Poisson-Boltzmann calculations using SAXS-derived low-resolution structural models allowed us to perform an energetic dissection of this process. The results showed that a model with a constant favorable contribution to folding that is opposed by an unfavorable electrostatic term that varies with ion concentration and valency provides a reasonable quantitative description of the observed folding behavior. Glycine binding, on the other hand, requires specific divalent ions binding based on the observation that Mg(2+), Ca(2+), and Mn(2+) facilitated glycine binding, whereas other divalent cations did not. The results provide a case study of how ion-dependent electrostatic relaxation, specific ion binding, and ligand binding can be coupled to shape the energetic landscape of a riboswitch and can begin to be quantitatively dissected.

NEAR trial: A single-arm phase II trial of neoadjuvant apalutamide monotherapy and radical prostatectomy in intermediate- and high-risk prostate cancer.

OBJECTIVE: Treatment efficacy of androgen deprivation therapy with radical prostatectomy for intermediate- to high-risk prostate cancer is less well-studied. The NEAR trial is a single-arm, phase II investigation of neoadjuvant apalutamide monotherapy and radical prostatectomy (RP) in the treatment of D'Amico intermediate- and high-risk prostate cancer (NCT03124433). MATERIALS AND METHODS: Patients with histologically-proven, D'Amico intermediate- to high-risk prostate adenocarcinoma received apalutamide 240 mg once-daily for 12 weeks followed by RP + /-lymphadenectomy. Primary outcome was pathological complete response (pCR) rate. Secondary outcomes included rate of biochemical response (defined by PSA < 0.03 ng/mL at week 24 from starting apalutamide without subsequent PSA relapse), treatment-related adverse events, and RP complication rates. Correlative biomarker analyses were performed to examine for molecular predictors of treatment responses. RESULTS: From 2017 to 2019, 30 patients were recruited, of which 20 and 10 were high and intermediate risk, respectively; 25 completed treatment as per-protocol. We did not observe any pCR on trial; median reduction of cancer burden was 41.7% (IQR: 33.3%-60.0%). 18 out of 25 patients were classified as having a biochemical response (4 did not achieve PSA of <0.03 ng/mL at week 24 and 3 developed PSA relapse subsequently). Dry skin (N = 16; 53.3%), fatigue (N = 10; 33.3%) and skin rash (N = 9; 30.0%) were the most common adverse events, and there was no major peri-operative complication. We observed an association between tumours of low androgen receptor activity and PAM50 basal status with biochemical non-responders, albeit these molecular phenotypes were not associated with pathological response. CONCLUSIONS: A 12-week course of neoadjuvant apalutamide prior to RP did not meet the primary endpoint of pCR in this trial. Tumours with low androgen receptor activity or of the PAM50 basal subtype may have a reduced response to apalutamide.

Meta-GWAS identifies the heritability of acute radiation-induced toxicities in head and neck cancer.

BACKGROUND AND PURPOSE: We aimed to the genetic components and susceptibility variants associated with acute radiation-induced toxicities (RITs) in patients with head and neck cancer (HNC). MATERIALS AND METHODS: We performed the largest meta-GWAS of seven European cohorts (n = 4,042). Patients were scored weekly during radiotherapy for acute RITs including dysphagia, mucositis, and xerostomia. We analyzed the effect of variants on the average burden (measured as area under curve, AUC) per each RIT, and standardized total average acute toxicity (STATacute) score using a multivariate linear regression. We tested suggestive variants (p < 1.0x10-5) in discovery set (three cohorts; n = 2,640) in a replication set (four cohorts; n = 1,402). We meta-analysed all cohorts to calculate RITs specific SNP-based heritability, and effect of polygenic risk scores (PRSs), and genetic correlations among RITS. RESULTS: From 393 suggestive SNPs identified in discovery set; 37 were nominally significant (preplication < 0.05) in replication set, but none reached genome-wide significance (pcombined < 5 × 10-8). In-silico functional analyses identified "3'-5'-exoribonuclease activity" (FDR = 1.6e-10) for dysphagia, "inositol phosphate-mediated signalling" for mucositis (FDR = 2.20e-09), and "drug catabolic process" for STATacute (FDR = 3.57e-12) as the most enriched pathways by the RIT specific suggestive genes. The SNP-based heritability (±standard error) was 29 ± 0.08 % for dysphagia, 9 ± 0.12 % (mucositis) and 27 ± 0.09 % (STATacute). Positive genetic correlation was rg = 0.65 (p = 0.048) between dysphagia and STATacute. PRSs explained limited variation of dysphagia (3 %), mucositis (2.5 %), and STATacute (0.4 %). CONCLUSION: In HNC patients, acute RITs are modestly heritable, sharing 10 % genetic susceptibility, when PRS explains < 3 % of their variance. We identified numerus suggestive SNPs, which remain to be replicated in larger studies.

Dynamic charge interactions create surprising rigidity in the ER/K alpha-helical protein motif.

Protein alpha-helices are ubiquitous secondary structural elements, seldom considered to be stable without tertiary contacts. However, amino acid sequences in proteins that are based on alternating repeats of four glutamic acid (E) residues and four positively charged residues, a combination of arginine (R) and lysine (K), have been shown to form stable alpha-helices in a few proteins, in the absence of tertiary interactions. Here, we find that this ER/K motif is more prevalent than previously reported, being represented in proteins of diverse function from archaea to humans. By using molecular dynamics (MD) simulations, we characterize a dynamic pattern of side-chain interactions that extends along the backbone of ER/K alpha-helices. A simplified model predicts that side-chain interactions alone contribute substantial bending rigidity (0.5 pN/nm) to ER/K alpha-helices. Results of small-angle x-ray scattering (SAXS) and single-molecule optical-trap analyses are consistent with the high bending rigidity predicted by our model. Thus, the ER/K alpha-helix is an isolated secondary structural element that can efficiently span long distances in proteins, making it a promising tool in designing synthetic proteins. We propose that the significant rigidity of the ER/K alpha-helix can help regulate protein function, as a force transducer between protein subdomains.

Development of a risk classification system combining TN-categories and circulating EBV DNA for non-metastatic NPC in 10,149 endemic cases.

BACKGROUND: The objective of this study was to construct a risk classification system integrating cell-free Epstein-Barr virus (cfEBV) DNA with T- and N- categories for better prognostication in nasopharyngeal carcinoma (NPC). METHODS: Clinical records of 10,149 biopsy-proven, non-metastatic NPC were identified from two cancer centers; this comprised a training (N = 9,259) and two validation cohorts (N = 890; including one randomized controlled phase 3 trial cohort). Adjusted hazard ratio (AHR) method using a two-tiered stratification by cfEBV DNA and TN-categories was applied to generate the risk model. Primary clinical endpoint was overall survival (OS). Performances of the models were compared against American Joint Committee on Cancer/Union for International Cancer Control (AJCC/UICC) 8th edition TNM-stage classification and two published recursive partitioning analysis (RPA) models, and were validated in the validation cohorts. RESULTS: We chose a cfEBV DNA cutoff of ⩾2,000 copies for optimal risk discretization of OS, disease-free survival (DFS) and distant metastasis-free survival (DMFS) in the training cohort. AHR modeling method divided NPC into six risk groups with significantly disparate survival (p < 0.001 for all): AHR1, T1N0; AHR2A, T1N1/T2-3N0 cfEBV DNA < 2,000 (EBVlow); AHR2B, T1N1/T2-3N0 cfEBV DNA ⩾ 2,000 (EBVhigh) and T1-2N2/T2-3N1 EBVlow; AHR3, T1-2N2/T2-3N1 EBVhigh and T3N2/T4N0 EBVlow; AHR4, T3N2/T4 N0-1 EBVhigh and T1-3N3/T4N1-3 EBVlow; AHR5, T1-3N3/T4 N2-3 EBVhigh. Our AHR model outperformed the published RPA models and TNM stage with better hazard consistency (1.35 versus 3.98-12.67), hazard discrimination (5.29 versus 6.69-13.35), explained variation (0.248 versus 0.164-0.225), balance (0.385 versus 0.438-0.749) and C-index (0.707 versus 0.662-0.700). In addition, our AHR model was superior to the TNM stage for risk stratification of OS in two validation cohorts (p < 0.001 for both). CONCLUSION: Herein, we developed and validated a risk classification system that combines the AJCC/UICC 8th edition TN-stage classification and cfEBV DNA for non-metastatic NPC. Our new clinicomolecular model provides improved OS prediction over the current staging system.

Lactate dehydrogenase kinetics predict chemotherapy response in recurrent metastatic nasopharyngeal carcinoma.

BACKGROUND: Lactate dehydrogenase (LDH) is a known prognostic biomarker for the endemic variant of nasopharyngeal carcinoma (NPC). Here, we investigate whether serial changes in LDH level between chemotherapy (CT) cycles are associated with tumour response to CT. METHODS: Patients with biopsy-proven, recurrent or treatment-naïve metastatic NPC (mNPC) were recruited. All patients had received at least two cycles of platinum-based doublet or triplet CT, with serial assessment of LDH prior to every cycle of chemotherapy (CT1-6). Patients harbouring conditions that affect LDH levels (IU/L) were excluded. Tumour response was assessed after every two cycles of CT by RECIST v1.1. RESULTS: A total of 158 patients were analysed, including 77 with recurrent and 81 with treatment-naïve mNPC. High pre-CT LDH was associated with an inferior overall survival [hazard ratio 1.93 for ⩾240 versus <240 (1.34-2.77), p < 0.001], which is consistent with published literature. We found that both absolute LDH levels and LDH ratios (LDHCTn: LDHCTn-1) were associated with tumour response [partial response versus progressive disease: median value across CT1-6 = 168-190 versus 222-398 (absolute); 0.738-0.988 versus 1.039-1.406 (ratio)], albeit LDH ratio had a tighter variance between patients. Finally, we showed that an LDH ratio cut-off of 1.0 at CT1, CT3 and CT5 was predictive of progressive disease at CT2, CT4, CT6 [area under the curve of 0.73 (0.65-0.80)]. CONCLUSION: Herein, we characterised the longitudinal variation of LDH in response to CT in mNPC. Our findings suggest the potential utility of interval LDH ratio to predict subsequent tumour response to CT.

Mixing and matching detergents for membrane protein NMR structure determination.

One major obstacle to membrane protein structure determination is the selection of a detergent micelle that mimics the native lipid bilayer. Currently, detergents are selected by exhaustive screening because the effects of protein-detergent interactions on protein structure are poorly understood. In this study, the structure and dynamics of an integral membrane protein in different detergents is investigated by nuclear magnetic resonance (NMR) and electron paramagnetic resonance (EPR) spectroscopy and small-angle X-ray scattering (SAXS). The results suggest that matching of the micelle dimensions to the protein's hydrophobic surface avoids exchange processes that reduce the completeness of the NMR observations. Based on these dimensions, several mixed micelles were designed that improved the completeness of NMR observations. These findings provide a basis for the rational design of mixed micelles that may advance membrane protein structure determination by NMR.

Mechanism of Enhanced Immature Dengue Virus Attachment to Endosomal Membrane Induced by prM Antibody.

Dengue virus (DENV) particles are released from cells in different maturation states. Fully immature DENV (immDENV) is generally non-infectious, but can become infectious when complexed with anti-precursor membrane (prM) protein antibodies. It is unknown how anti-prM antibody-coated particles can undergo membrane fusion since the prM caps the envelope (E) protein fusion loop. Here, we determined cryoelectron microscopy (cryo-EM) maps of the immDENV:anti-prM complex at different pH values, mimicking the extracellular (pH 8.0) or endosomal (pH 5.0) environments. At pH 5.0, there are two structural classes with fewer antibodies bound than at pH 8.0. These classes may represent different maturation states. Molecular simulations, together with the measured high-affinity pr:antibody interaction (versus the weak pr:E interaction) and also the low pH cryo-EM structures, suggest how antibody:pr complex can dislodge from the E protein at low pH. This exposes the E protein fusion loop enhancing virus interaction with endosomes.