{"id":3099,"date":"2023-01-17T13:48:53","date_gmt":"2023-01-17T19:48:53","guid":{"rendered":"https:\/\/kermitmurray.com\/msblog\/?page_id=3099"},"modified":"2023-01-17T13:48:53","modified_gmt":"2023-01-17T19:48:53","slug":"biorxiv-biochemistry","status":"publish","type":"page","link":"https:\/\/kermitmurray.com\/msblog\/links\/journal-feeds\/biochemistry-journal-feeds\/biorxiv\/biorxiv-biochemistry\/","title":{"rendered":"BioRxiv Biochemistry"},"content":{"rendered":"\n<div class=\"wp-block-caxton-grid relative\"><div class=\"absolute absolute--fill\"><div class=\"absolute absolute--fill cover bg-center\" style=\"background-color:;background-image:linear-gradient( );\"><\/div><div class=\"absolute absolute--fill\" style=\"background-color:;background-image:linear-gradient( );opacity:1;\"><\/div><\/div><div class=\"relative caxton-columns caxton-grid-block\" style=\"padding-top:0;padding-left:0;padding-bottom:0;padding-right:0;grid-template-columns:repeat(12, 1fr)\" data-tablet-css=\"padding-left:em;padding-right:em;\" data-mobile-css=\"padding-left:em;padding-right:em;\">\n<div class=\"wp-block-caxton-section relative\" style=\"grid-area:span 1\/span 8\"><div class=\"absolute absolute--fill\"><div class=\"absolute absolute--fill cover bg-center\" style=\"background-color:;background-image:linear-gradient( );\"><\/div><div class=\"absolute absolute--fill\" style=\"background-color:;background-image:linear-gradient( );opacity:1;\"><\/div><\/div><div class=\"relative caxton-section-block\" style=\"padding-top:5px;padding-left:5px;padding-bottom:5px;padding-right:5px\" data-mobile-css=\"padding-left:1em;padding-right:1em;\" data-tablet-css=\"padding-left:1em;padding-right:1em;\">\n<p><strong><a href=\"https:\/\/www.biorxiv.org\/alertsrss\" target=\"_blank\" rel=\"noreferrer noopener\">Journal Home<\/a><\/strong><\/p>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-caxton-section relative\" style=\"grid-area:span 1\/span 4\"><div class=\"absolute absolute--fill\"><div class=\"absolute absolute--fill cover bg-center\" style=\"background-color:;background-image:linear-gradient( );\"><\/div><div class=\"absolute absolute--fill\" style=\"background-color:;background-image:linear-gradient( );opacity:1;\"><\/div><\/div><div class=\"relative caxton-section-block\" style=\"padding-top:5px;padding-left:5px;padding-bottom:5px;padding-right:5px\" data-mobile-css=\"padding-left:1em;padding-right:1em;\" data-tablet-css=\"padding-left:1em;padding-right:1em;\">\n<p><strong><a href=\"http:\/\/connect.biorxiv.org\/biorxiv_xml.php?subject=biochemistry\" target=\"_blank\" rel=\"noreferrer noopener\">RSS<\/a><\/strong><\/p>\n<\/div><\/div>\n<\/div><\/div>\n\n\n<ul class=\"has-dates has-authors has-excerpts wp-block-rss\"><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.07.10.737745v1?rss=1'>From biofilms to birth: Quantitative murburn rationale for hydrated polymer-centred biological transduction, coherence, and evolution of complex life<\/a><\/div><time datetime=\"2026-07-13T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">July 13, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Manoj, K. M., Jaeken, L., Tamagawa, H., Burra, V. L. S. P.<\/span><div class=\"wp-block-rss__item-excerpt\">Hydrated extracellular polymeric phases (such as mucus, biofilms, and extracellular matrices) have traditionally been viewed as passive barriers. We complement and extend this view by analysing these systems through the murburn framework and liquid-liquid phase separation (LLPS) biophysics. Using quantitative modeling, we first demonstrate how frothy mucus in amphibian egg-masses enhances oxygen delivery while buffering diffusible reactive species (DRS), leading to improved developmental synchrony. We then model the human cervical mucus system, showing its cycle-dependent transitions between coherent barriers (pregnancy), [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.07.10.737677v1?rss=1'>Molecular models for Gram-positive bacterial strains: Assessing membrane properties and small molecule interactions for S.aureus, S. epidermidis and N. lacusekhoensis<\/a><\/div><time datetime=\"2026-07-10T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">July 10, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Vaiwala, R., Christy, E., Waskar, M., Ayappa, K. G.<\/span><div class=\"wp-block-rss__item-excerpt\">We present a comparative study of the inner membrane of three Gram-positive bacterial strains, namely S. aureus, S. epidermidis and N. lacusekhoensis. A lipidomics study is used to obtain the lipid architecture and composition for S. epidermidis found in the skin microbiome and N. lacusekhoensis, an extremophile present in halophilic and alkophilic environments. Differences between the strains arise from both the lipid architecture and the cardiolipin content varying from 5% in S. aureus to 85% in N. lacusekhoensis. We develop [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.07.09.737478v1?rss=1'>Cell-type-resolved spatial proteogenomics from matched genome and proteome of the same cells<\/a><\/div><time datetime=\"2026-07-10T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">July 10, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Zwiebel, M., Wahle, M., Stadler, R., Levesque, M. P., Dummer, R., Nordmann, T. M., Mann, M.<\/span><div class=\"wp-block-rss__item-excerpt\">The genome and proteome of the same cells are rarely measured together, which is especially consequential in cancer, where somatic mutations vary across clones and drive disease. We show that a single standard proteomics extraction tip can retain peptides on-tip after digestion while genomic DNA passes into the normally discarded flowthrough. Combined with Deep Visual Proteomics, flowthrough co-isolation enables cell-type-resolved spatial proteogenomics from archival FFPE tissue, demonstrated in melanoma.<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.07.09.736951v1?rss=1'>Hybrid quantum-classical de novo design of MHC-binding peptides<\/a><\/div><time datetime=\"2026-07-10T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">July 10, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Engdal, E. S., Funk, J., Bacarreza, O., Machado, L., Johansen, K. H., Kemming, J., Farnsworth, T., Brasas, V., Lefevre-Morand, R. Y. L., Slysz, M., Noerregaard, O. L., Sandberg, O. A. D. A., Makarovskiy, A., Lodahl, P., Acevedo-Rocha, C. G., Kurowski, K., Hadrup, S. R., Clements, W. R., Jenkins, T.<\/span><div class=\"wp-block-rss__item-excerpt\">Deep generative models have become a leading approach for designing therapeutic molecules, yet efficiently exploring vast biomolecular sequence spaces remains difficult, particularly for targets with limited training data. The prior distribution that seeds a generative model shapes which regions of sequence space it explores, and recent work suggests that non-classical distributions sampled from quantum processors can serve as a structured alternative to the factorised Gaussian priors used by default. Whether such priors help on complex biological design tasks has been [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.07.09.737429v1?rss=1'>Transposon end recognition and pairing by I-F3 CRISPR-associated transposase<\/a><\/div><time datetime=\"2026-07-10T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">July 10, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Truong, V., Miller, D., Fatma, S., Sheng, Y., Pindi, C., Ahsan, M., Palermo, G., Kellogg, E. H.<\/span><div class=\"wp-block-rss__item-excerpt\">To develop gene therapy tools based on CRISPR-associated transposons (CASTs), it is essential to define how transposon ends are recognized and paired during transposition. Tn7-like transposons typically contain asymmetric left- and right-end sequences that flank and define DNA cargo. However, how the transposase recognizes these different sequences and assembles them into a paired end complex for cut-and-paste transposition remains unknown. Here we present the cryo-EM structure of type I-F3 (VchCAST) CAST transposase TnsB in complex with transposon DNA ends and [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.07.08.737370v1?rss=1'>Denuded peptidoglycan oligosaccharides enable the biochemical investigation of bacterial cell wall recognition, modification, and degradation<\/a><\/div><time datetime=\"2026-07-10T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">July 10, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Emmanuel, B. G., DelMistro, G., Anderson, A. C., Vandenende, C., Clarke, A. J., Sychantha, D.<\/span><div class=\"wp-block-rss__item-excerpt\">Peptidoglycan is an essential component of the bacterial cell wall, providing mechanical strength and maintaining cell shape. It consists of glycan chains crosslinked by short peptide stems, resulting in a chemically heterogeneous macromolecule that remains challenging to study in a well-defined form. Access to discrete peptidoglycan fragments has therefore been critical for advancing biochemical and structural studies of cell wall-active enzymes. However, current synthetic, semi-synthetic, and cell wall extraction approaches remain limited by the complexity of carbohydrate chemistry and the [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.07.09.737422v1?rss=1'>The Shewanella oneidensis Fic enzyme SoFic targets the switch-Iregion of EF-Tu for AMPylation<\/a><\/div><time datetime=\"2026-07-10T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">July 10, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Runge, S., Pogenberg, V., Baumgart, A., Siebels, B., Schlueter, H., Hecht-Bucher, M., Itzen, A.<\/span><div class=\"wp-block-rss__item-excerpt\">Fic enzymes mediate diverse post-translational modifications, including adenosine monophosphate (AMP) transfer and removal, referred to as AMPylation and deAMPylation, respectively. We identified the prokaryotic translation elongation factor Tu (EF-Tu) as an AMPylation target of the Fic enzyme SoFic. SoFic can constitutively reverse EF-Tu modification via deAMPylation whereas AMPylation depends on SoFic homodimerization. The complex crystal structure between SoFic and EF-Tu confirms a conserved target binding mode across evolutionary distant Fic enzymes. AMPylation disrupts EF-Tu&#039;s regulatory switch-I region, causing translational inhibition. [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.07.09.737552v1?rss=1'>Structural and Energetic Determinants of Monobody Recognition of Oncogenic KRAS Variants<\/a><\/div><time datetime=\"2026-07-10T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">July 10, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Kumar, A., Huang, Y.-m. M.<\/span><div class=\"wp-block-rss__item-excerpt\">Monobodies are engineered binding proteins that recognize extended protein surfaces and offer advantages over small-molecule inhibitors for targeting challenging KRAS oncoproteins. Monobody 12D4 exhibits high affinity and selectivity for the oncogenic KRAS(G12D) mutant, but the molecular determinants governing its recognition and the basis for its mutant selectivity remain poorly understood. Here, we combined molecular dynamics simulations and energy calculations to characterize the interactions between monobody 12D4 and WT KRAS as well as four clinically relevant oncogenic variants (G12C, G12D, G12V, [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.07.10.737215v1?rss=1'>Targeted mining of plastic-associated metagenomes uncovers a novel thermostable PETase expanding scaffold space for engineering<\/a><\/div><time datetime=\"2026-07-10T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">July 10, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Rigkos, K., Bezantakou, D., Antoniadis, K., Antonopoulou, I., Zarafeta, D., Skretas, G.<\/span><div class=\"wp-block-rss__item-excerpt\">Enzymatic depolymerization of polyethylene terephthalate (PET) has advanced rapidly, alongside a growing volume of publicly available metagenomic data from microbial communities under sustained selective pressure from plastic exposure. Reasoning that such environments may harbor underexplored polyester-active enzymes, we developed a targeted mining workflow that screens exclusively plastic-associated datasets through multi-step bioinformatic filtering&#8211;integrating catalytic-motif screening, disulfide-topology validation, structural-similarity scoring, and phylogenetic profiling&#8211;to recover high-confidence PETase candidates. Applied to 271 plastic-associated metagenomes, the pipeline yielded 21 non-redundant candidates, several of which combine [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.07.08.735634v1?rss=1'>Coated Bacterial Enzymes: A one-step approach for enzymatic purification and immobilization<\/a><\/div><time datetime=\"2026-07-09T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">July 9, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Ramirez Gutierrez, A. C., Harguindeguy, I., Homse, M. S., Sabetta, A. E., Cavalitto, S. F., Ortiz, G. E.<\/span><div class=\"wp-block-rss__item-excerpt\">The purification of industrial enzymes typically relies on costly, multi-step chromatographic protocols. To address this, we developed a novel platform termed Coated Bacterial Enzymes (CBEs), which enables one-step purification and immobilization of recombinant proteins fused to the SlpA cell wall binding domain. As a proof of concept, we used a {beta}-galactosidase from Bifidobacterium bifidum of dairy relevance. The chimeric enzyme BbgII-SlpA was expressed in Escherichia coli and captured from crude lysate onto glutaraldehyde-inactivated Bacillus subtilis cells via SlpA domain. Binding [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.07.08.737074v1?rss=1'>Variational Autoencoder-enabled High-throughput Drug Screening for HIV Latency Modulators predicted through Noise in Gene Expression<\/a><\/div><time datetime=\"2026-07-09T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">July 9, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Shukla, D., Lu, Y., Horne, J. R., Mi, X., Nag, S., Dash, S., Dar, R. D.<\/span><div class=\"wp-block-rss__item-excerpt\">Due to its ability to establish a pool of undetectable and latently infected cells that can initiate viral production through random reactivation, a cure to human immunodeficiency virus (HIV) infections has remained elusive. Many approaches have been proposed, including the &quot;shock and kill&quot; method where latency reversing agents (LRAs) are administered to reactivate latently infected cells out of latency and remove them through immune targeting and clearance, and the &quot;block and lock&quot; method where latency promoting agents (LPAs) are administered [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.07.08.737297v1?rss=1'>Measurement of a panel of 21 steroids in a quantitative assay in human plasma, adipose tissue, and fecal samples using ultra-high-performance liquid chromatography-tandem mass spectrometry<\/a><\/div><time datetime=\"2026-07-09T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">July 9, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Evstafev, I., Krakstrom, M., Saarinen-Aaltonen, N., Hakkarainen, J., Hakkinen, M. R., Auriola, S., Bostrom, P. J., Poutanen, M., Oresic, M., Dickens, A. M.<\/span><div class=\"wp-block-rss__item-excerpt\">Comprehensive detection of steroids, beyond the limited panels typically analyzed in clinical chemistry laboratories, has become increasingly important given their pivotal roles in diverse biological processes. However, steroid quantification poses several analytical challenges, including differences in ionization efficiency and structural similarities across the entire steroid metabolic network. To address these challenges, we developed a targeted ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS\/MS) assay to analyze 21 steroids using reverse-phase chromatography combined with rapid polarity switching. Mass spectrometry (MS) analysis was performed [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.07.08.737270v1?rss=1'>Improving coral oxidative stress assessments through compartment-specific lipid peroxidation measurements and increased methodological standardization<\/a><\/div><time datetime=\"2026-07-09T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">July 9, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Mastorakos, S. W., Kruger, A. J., Roger, L. M., Carbonne, C., Sawall, Y.<\/span><div class=\"wp-block-rss__item-excerpt\">Lipid peroxidation (LPO) is widely used as a biomarker of oxidative stress in coral bleaching research, yet its measurement remains poorly standardized across the field. A systematic review of the coral LPO literature reveals substantial variation in methodological approaches, including tissue fraction analysis, lysis protocols, assay choice, and normalization metrics, confounding cross-study comparison and obscuring the biological interpretation of results. We experimentally investigate two key sources of variation: the use of bulk holobiont vs separated host and algal symbiont fractions, [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.07.08.737278v1?rss=1'>Directed evolution of the Fe-nitrogenase for CO2 reduction to hydrocarbons<\/a><\/div><time datetime=\"2026-07-09T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">July 9, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Oehlmann, N. N., Schmidt, F. V., Chen, J., Prinz, S., Zarzycki, J., Claus, P., Kahnt, J., Erb, T. J., Rebelein, J. G.<\/span><div class=\"wp-block-rss__item-excerpt\">The iron (Fe) nitrogenase drives bacterial methane (CH4) formation by converting carbon dioxide (CO2) to CH4 in a single enzymatic step. Enhancing the initial CH4 formation activity of Fe-nitrogenase and expanding the product spectrum to hydrocarbon chains could lead to a route for sustainable feedstock chemicals. Here, we performed the first directed evolution campaign on the Fe-nitrogenase aimed at optimizing the hydrocarbon production. We achieved an [~]8-fold increase in CH4 formation by Fe-nitrogenase expressing Rhodobacter capsulatus cultures in three rounds [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.07.07.737131v1?rss=1'>Computational Lead Optimization on BACE1: Relative Binding Free Energy Perturbation as the Terminal Refinement Layer<\/a><\/div><time datetime=\"2026-07-08T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">July 8, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Alejo, K., Korban, C., Chung, C.<\/span><div class=\"wp-block-rss__item-excerpt\">Structure-based drug discovery is known to apply computational methods in a tiered hierarchy, with each layer narrowing the candidate set and refining the binding picture before committing to the next, more expensive step. We present a four-tiered computational benchmarking study evaluating five engines against a panel of 36 compounds targeting {beta}-secretase 1 (BACE1), a validated Alzheimers disease target with extensive co-crystal ground truth. This study evaluates Flexible Docking and Boltz2 Cofolding as the primary tier, followed by Ensemble Docking, and [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.07.07.737046v1?rss=1'>Hepatic stearoyl-CoA desaturase deficiency ameliorates hyperglycemia through bile acid signaling in an insulin-independent manner<\/a><\/div><time datetime=\"2026-07-08T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">July 8, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Kalyesubula, M., Kim, D., Kim, W. S., Wicker, N. B., Williams, J., Christofi, V. P., Anderson, E., Miller, J. R., Cootway, D., Groppel, K., Bergman, D., Chaudhari, S. N., Ntambi, J. M.<\/span><div class=\"wp-block-rss__item-excerpt\">Hyperglycemia in Type 1 Diabetes (T1D) is managed almost exclusively via exogenous insulin therapy, an approach restricted by significant glycemic fluctuations, long-term side effects such as weight gain, and high economic burden. Identifying physiological pathways capable of clearing blood glucose independent of insulin is therefore of paramount clinical importance. Here, we demonstrate that liver-specific stearoyl-CoA desaturase-1 (SCD1) deficiency protects against diabetic hyperglycemia and hepatic steatosis in an insulin-independent manner. SCD1 ablation decreases cellular oleate availability, altering lipid flux and redirecting [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.07.08.737148v1?rss=1'>The immunosuppressant tacrolimus (FK506) inhibits C. glabrata Cdr1 efflux pump function by stabilizing the inward-facing conformation.<\/a><\/div><time datetime=\"2026-07-08T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">July 8, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Baccouch, R., Benefice, T., Zarkadas, E., Samrouth, N., Pata, J., Magnard, S., Di Meo, F., Terreux, R., Aguero, S., Boumendjel, A., Schoehn, G., Lamping, E., Falson, P., Chaptal, V.<\/span><div class=\"wp-block-rss__item-excerpt\">The pathogenic yeast Candida glabrata is intrinsically resistant to azole antifungals through the overexpression of the multidrug transporter Cdr1. CgCdr1 detoxifies the yeast by expelling azoles out of the cell, thereby decreasing their intracellular concentration. Tacrolimus (FK506), one of the most widely used immunosuppressant medications used world-wide, has been identified as a broad-spectrum inhibitor of Cdr1 homologs in several Candida species. However, its mechanism of action remains unknown. We solved the cryoEM structure of CgCdr1 in complex with FK506, with [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.07.08.737142v1?rss=1'>Screening Lipid Nanoparticles through Structure-Ratio Alignment<\/a><\/div><time datetime=\"2026-07-08T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">July 8, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Lee, Y., Oh, Y., Choi, H., Park, C.<\/span><div class=\"wp-block-rss__item-excerpt\">Lipid Nanoparticles (LNPs) are widely used as delivery systems for nucleic acid therapeutics, where transfection efficiency is determined by both the identities of constituent lipid components and their composition ratios. While prior studies have focused on learning molecular representations for individual components, modeling how multiple components and their ratios jointly influence LNP performance remains underexplored. In this work, we propose STRATA, a framework that models molecule interaction between LNP components, which is known to contribute to LNP transfection efficiency. Our [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.07.07.737042v1?rss=1'>Dithionite quenching of NBD-labeled lipids reveals artificial lipid droplet purity and neutral lipid surface accessibility<\/a><\/div><time datetime=\"2026-07-08T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">July 8, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Chai, J., Wu, L., Choi, Y. M., Gao, S., Canals, D., Thiam, A. R., London, E., Airola, M. V.<\/span><div class=\"wp-block-rss__item-excerpt\">Artificial lipid droplets (aLDs) provide a controllable platform for studying lipid biochemistry, but their use is limited by contamination with other membrane structures and the lack of quantitative methods to assess sample purity. Here, we establish dithionite quenching of NBD-labeled lipids as a simple approach to evaluate aLD purity. The approach relies on dithionites ability to selectively quench NBD fluorophores exposed in the phospholipid monolayer of aLDs and in the outer leaflet of liposome bilayers, but not those protected within [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.07.07.736967v1?rss=1'>Interface swapping orchestrates carbon transfer in the archaeal acetyl-CoA decarbonylase\/synthase<\/a><\/div><time datetime=\"2026-07-08T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">July 8, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Zimmer, E., Reif-Trauttmansdorff, T., Ciancone, A., Appelgren, S., Kahnt, J., Deobald, D., Abendroth, F., Vazquez, O., Hochberg, G. K. A., Schuller, J. M.<\/span><div class=\"wp-block-rss__item-excerpt\">The Wood-Ljungdahl pathway is one of biologys most ancient routes for carbon fixation and energy metabolism, used by organisms such as methanogenic archaea. One of its central metabolic complexes is the acetyl-CoA decarbonylase\/synthase (ACDS) complex, catalyzing acetyl-CoA synthesis and cleavage through the co-ordinated action of carbon monoxide dehydrogenase (CODH), acetyl-CoA synthase (ACS), and corrinoid iron-sulfur protein (CoFeSP). 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