Biology subjects

Levitt, M.

Publications and source records attributed to Levitt, M..

8 recordsLinked to original sources

bioRxiv2026

Quasi-continuous cotranslational compaction and folding of a multidomain protein

Most proteins start to fold cotranslationally as they come off the ribosome. So far, studies of cotranslational folding have focused mainly on small, single-domain proteins. Here, we have used Force Profile Analysis to study the cotranslational folding of Firefly luciferase, a complex 550-residue protein composed of an N-terminal domain (NTD) encompassing two split Rossmann folds (RF-1, RF-2) and a {beta}-roll, and a flexibly attached C-terminal domain (CTD). The folding process is characterized by a quasi-continuous series of compaction/folding steps that generate intermediate-size pulling forces on the nascent chain, punctuated by a prominent high-force event that represents the folding of the RF-2 domain, and a few low-force instances that likely indicate the formation of distinct folding intermediates. Trigger Factor interacts extensively with the nascent chain when the central part of RF-2 and the early parts of the CTD are synthesized. Our analysis uncovers a cotranslational compaction/folding process that is rich in detail and not just a simple succession of a few distinct, cooperative folding transitions.

molecular biology↗

bioRxiv2026

Structure-aware Graph Learning Predicts RNA Editability Across Tissues and Species

Programmable A-to-I RNA editing using endogenous ADAR enzymes is emerging as a therapeutic strategy, but editability remains difficult to predict because ADAR recognition depends on double-stranded RNA geometry and stability rather than sequence alone. We present AdarEdit, a structure-explicit graph-attention framework that represents each dsRNA substrate as a nucleotide graph with backbone and base-pair edges. The framework includes a baseline model and a bio-aware model, with the latter augmenting this representation with typed interactions and a motif-sensitive sequence branch. We trained and evaluated both models on high-confidence inverted Alu duplexes (n = 884) with secondary structures predicted by RNAfold and editing levels measured across 8,603 GTEx RNA-seq samples spanning 47 tissues. Across five tissue contexts, the baseline and bio-aware models achieved strong held-out performance (test F1 = 0.814-0.869, AUROC = 0.869-0.933) and outperformed a matched structure-string baseline on the Liver split. The same graph representation retained predictive ability in evolutionarily distant non-Alu species (sea urchin, acorn worm, and octopus), suggesting conserved principles of ADAR substrate recognition. Finally, attention profiles and in silico mutagenesis recapitulated known biochemical constraints, including suppression by an upstream guanosine, and revealed longer-range asymmetric structural influences on editing. Because Alu duplexes are edited predominantly by ADAR1, AdarEdit is geared primarily to the ADAR1 regime. ADAR1 is particularly relevant to therapeutic editing given its broad tissue expression. The sources of this work are available at our repository: https://github.com/Scientific-Computing-Lab/AdarEdit

bioinformatics↗

bioRxiv2025

Dose Modeling for Mitochondrial Transplantation in Barrier-Limited Tissues

Mitochondrial transplantation is an emerging regenerative therapy aimed at preventing ischemia- reperfusion injury (IRI) by restoring oxidative metabolism in vulnerable tissues. While early clinical studies have demonstrated feasibility in pediatric myocardium and safety in adult stroke patients, dosing strategies remain undefined for barrier-limited organs where autoregulation, restricted perfusion, and anatomical constraints limit parenchymal uptake. We developed a physiologically grounded computational model to estimate route-specific input dose requirements for brain, spinal cord, and kidney. The model integrates organ-level parameters including tissue mass, regional perfusion or cerebrospinal flow, permeability-surface area product, and extraction efficiency. A benchmark dose of 2 x 106 mitochondria per gram, derived from validated cardiac protocols, was applied across delivery scenarios. Sensitivity analysis explored the effects of extraction fraction and tissue mass. Route-adjusted input requirements diverged quantitatively from cardiac-derived estimates, with up to 2-fold increases in central nervous system (CNS) targets and approximately 20% higher dosing required for the kidney. This framework provides a quantitative foundation for translational dose planning in IRI and related conditions.

pharmacology and toxicology↗

bioRxiv2025

Radiolabeling Isolated Mitochondria with Tc-99m: A First-in-Field Protocol and Early Feasibility Findings

Mitochondrial transplantation is a promising but still experimental strategy for treating ischemic and metabolic disorders. A key barrier to its advancement is the lack of scalable, non-invasive methods for tracking transplanted extracellular mitochondria in vivo. Technetium-99m (Tc-99m) radiopharmaceuticals, widely used in SPECT imaging, may offer a clinically compatible solution. Cryopreserved mitochondria derived from HEK-293 cells were incubated with Tc-99m sestamibi, tetrofosmin, pertechnetate, or control solutions. After brief incubation and washing, mitochondrial pellets were analyzed for retained radioactivity. ATP content was measured to assess metabolic function, and electron microscopy was used to evaluate ultrastructural integrity. Tc-99m sestamibi and tetrofosmin showed labeling efficiencies of 2.74% and 2.68%, respectively. Pertechnetate demonstrated minimal uptake (0.34%). Radiolabeled mitochondria retained ATP production comparable to controls. Electron microscopy showed preserved double membranes and cristae. Controls confirmed assay specificity and viability. To our knowledge, this is the first report of radiolabeling isolated mitochondria with clinically approved Tc-99m agents. This platform supports the development of SPECT-compatible protocols for visualizing viable transplanted mitochondria in recipient tissues.

cell biology↗

bioRxiv2025

PDBCleanV2: A Python Library for Generating Consistent Structure Datasets

The number of structures in the Protein Data Bank has grown rapidly in recent years. Nonetheless, comparing structures of a specific system often proves challenging due to variant nomenclature, origins from different species, presence of various ligands, and missing atoms or chains. To address these issues, we have developed PDBCleanV2, a Python package that enables users to create consistent datasets of structures, simplifying comparison among structures. This library generates individual files for each molecule in a structure file, corrects labeling errors, and standardizes chain names and numbering. Our aim is to provide researchers with consistent datasets that streamline their analysis. The source code, installation instructions, and tutorials can be found in PDBCleanV2s GitHub repository and Zenodo accessible at https://github.com/fatipardo/PDBClean-0.0.2/ and https://doi.org/10.5281/zenodo.14014241, respectively.

bioinformatics↗

bioRxiv2024

Single-residue effects on the behavior of a nascent polypeptide chain inside the ribosome exit tunnel

Nascent polypeptide chains (NCs) are extruded from the ribosome through an exit tunnel (ET) traversing the large ribosomal subunit. The ETs irregular and chemically complex wall allows for various NC-ET interactions. Translational arrest peptides (APs) bind in the ET to induce translational arrest, a property that can be exploited to study NC-ET interactions by Force Profile Analysis (FPA). We employed FPA and molecular dynamics (MD) simulations to investigate how individual residues within a glycine-serine repeat segment of an AP-stalled NC interact with the ET to exert a pulling force on the AP and release stalling. Our results indicate that large and hydrophobic residues generate a pulling force on the AP when placed {gtrsim}10 residues away from the peptidyl transfer center (PTC). An asparagine placed 12 residues from the PTC appears to form a specific stabilizing interaction with the tip of ribosomal protein uL22 that reduces the pulling force on the AP, whereas a lysine or leucine residue in the same position increases the pulling force. Finally, the MD simulations suggest how the Mannheimia succiniciproducens SecM AP interacts with the ET to promote translational stalling. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=102 SRC="FIGDIR/small/608737v2_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@d61d3forg.highwire.dtl.DTLVardef@11a3fa3org.highwire.dtl.DTLVardef@47e7ecorg.highwire.dtl.DTLVardef@cb4fb7_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2021

Probing interplays between human XBP1u translational arrest peptide and 80S ribosome

The ribosome stalling mechanism is a crucial biological process; yet its atomistic underpinning is still elusive. In this framework, the XBP1u translational arrest peptide (AP) plays a central role in regulating the Unfolded Protein Response (UPR) in eukaryotic cells. Here, we report multi-microseconds all atom molecular dynamics simulations designed to probe the interactions between the XBP1u AP and the mammalian ribosome exit tunnel, both for the wild type AP and for four mutant variants of different arrest potency. Enhanced sampling simulations allow investigating the AP release process of the different variants shedding light on this complex mechanism. The present outcomes are in qualitative/quantitative agreement with available experimental data. In conclusion, we provide an unprecedented atomistic picture of this biological process and clear-cut insights into the key AP-ribosome interactions.

molecular biology↗

bioRxiv2020

Insights on cross-species transmission of SARS-CoV-2 from structural modeling

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the ongoing global pandemic that has infected more than 14 million people in more than 180 countries worldwide. Like other coronaviruses, SARS-CoV-2 is thought to have been transmitted to humans from wild animals. Given the scale and widespread geographical distribution of the current pandemic, the question emerges whether human-to-animal transmission is possible and if so, which animal species are most at risk. Here, we investigated the structural properties of several ACE2 orthologs bound to the SARS-CoV-2 spike protein. We found that species known not to be susceptible to SARS-CoV-2 infection have non-conservative mutations in several ACE2 amino acid residues that disrupt key polar and charged contacts with the viral spike protein. Our models also predict affinity-enhancing mutations that could be used to design ACE2 variants for therapeutic purposes. Finally, our study provides a blueprint for modeling viral-host protein interactions and highlights several important considerations when designing these computational studies and analyzing their results.

bioinformatics↗