Biology subjects

Kubicek-Sutherland, J. Z.

Publications and source records attributed to Kubicek-Sutherland, J. Z..

5 recordsLinked to original sources

bioRxiv2025

Structure-Based Optimization of Pathogen Signal Sequences for Enhanced Antigen Expression in Humans for Vaccine Designs

Signal peptides (SPs) are short amino acid sequences found at the N-terminus of nascent polypeptides, which serve critical roles in trafficking, folding, and post-translational processing of mature proteins. Many sequence-based computational methods have been developed to predict and design optimal SPs for protein secretion in human cells. In this work, we introduce a structure-based workflow for identifying SPs and their regions, aiming to optimize SPs for protein secretion in human cells. Structural modeling of the SPs in complex with human signal recognition particle 54 kDa (SRP54), combined with hydrophobicity plots of the SPs and identification of the cleavage motif, can be used to detect SPs and SP regions. Afterwards, LigandMPNN is applied to redesign the SPs based on their structural complexes with SRP54. We employ our workflow to optimize the bacterial Yersinia pestis F1 SP, Lassa virus glycoprotein (GP) SP, and Venezuelan equine encephalitis virus (VEEV) E3 envelope protein for protein secretion in human cells to serve as vaccine candidates. By comparing the redesigned SPs with the original SPs, we propose that the binding affinity of SPs to SRP54 serve as the most important molecular determinant in the activity of the SPs. Notably, our experiments confirm that the structurally optimized SPs can express the Y. pestis F1 protein, Lassa GP, and VEEV GP in human cells. Overall, we demonstrate that structural modeling can serve as a valuable tool to predict the SPs and SP regions for vaccine antigens, predict whether the SPs can express mature proteins in humans, and optimize the SPs for the expression of mature proteins in humans.

biophysics↗

bioRxiv2025

SignalGen: A Protein Language Model Based AI Agent For Optimal Signal Peptide Prediction

Signal peptides are short amino acid sequences attached to the N-termini of mature proteins. They play determinant roles in protein expression as well as localization of mature proteins. While sequence-based machine learning (ML) models have been developed to identify the signal peptide sequences given the full or mature protein sequences, no model has been created to design optimal signal peptides with the localization of the mature proteins taken into account. Here, we develop a ML model that considers the mature protein sequence, organism, and localization as inputs, encodes and processes them through a Latent Residual Transformer (LRT), and outputs the optimal signal peptide sequences for enhanced expression of the mature proteins, regardless of whether the proteins are non-native to the organism or de novo. The model is trained using the latest data from the UniProt database up until July 2025. Benchmarking of our ML model shows good performance in predicting the signal peptides for both human and non-human proteins from the UniProt database. Furthermore, our ML model is implemented with an artificial intelligence (AI) agent to enhance accessibility for the general scientific community. Findings from this study provide a framework for predicting optimal signal peptides for non-native protein expression of viral and bacterial vaccine candidates in human cells and for enhanced expression of de novo proteins.

bioinformatics↗

bioRxiv2024

Diverse toxins exhibit a common binding mode to the Nicotinic Acetylcholine Receptors revealing a new molecular determinant

Nicotinic acetylcholine receptors (nAChRs) are critical ligand-gated ion channels in the human nervous system. They are targets for various neurotoxins produced by algae, plants, and animals. While there have been many structures of nAChRs bound by neurotoxins published, the binding mechanism of toxins to the nAChRs remains uncleared. In this work, we have performed extensive Gaussian accelerated molecular dynamics simulations on several Aplysia californica (AC) nAChRs in complex with -conotoxins, strychnine, and pinnatoxins, as well as human nAChRs in complex with -bungarotoxin and -conotoxin for a total of 60 s of simulation time to determine the binding and dissociation pathways of the toxins to the nAChRs and the associated effects. We uncovered two common binding and dissociation pathways shared by toxins and nAChRs. In the primary binding pathway, the toxins diffused from the bulk solvent to first bind a region near the extracellular pore before moving downwards along the nAChRs to the nAChR orthosteric pocket. The second binding pathway involved a direct diffusion of the toxins from the bulk solvent into the nAChR orthosteric pocket. The dissociation pathways were the reverse of the observed binding pathways. We also found that the toxins enacted their toxicity upon binding by restricting the necessary movements required by the nAChRs to open their extracellular and intracellular pores for the ions to pass through. Notably, the electrostatically bipolar interactions between nAChR orthosteric pocket and toxins provides a molecular level explanation for the common binding mode shared by diverse toxins and serve as a key determinant for toxicity.

biophysics↗

bioRxiv2022

Inferring pathways of oxidative folding from pre-folding free energy landscapes of disulfide-rich toxin

Short, cysteine-rich peptides can exist in stable or metastable structural ensembles due to the number of possible patterns of formation of their disulfide bonds. One interesting subset of this peptide group is the coonotoxins, which are produced by aquatic snails in the family Conidae. The {micro} conotoxins, which are antagonists and blockers of the voltage-gated sodium channel, exist in a folding spectrum: on one end of the spectrum are more hirudin-like folders, which form disulfide bonds and then reshuffle them, leading to an ensemble of kinetically trapped isomers-and on the other end are more BPTI-like folders-which form the native disulfide bonds one by one in a particular order, leading to a preponderance of conformations existing in a single stable state. In this article, we employ the composite diffusion map approach to study the unified free energy surface of pre-folding {micro}-conotoxin equilibrium. We identify the two most important nonlinear collective modes of the unified folding landscape and demonstrate that in the absence of their disulfides, the conotoxins can be thought of as largely disordered polymers. A small increase in the number of hydrophobic residues in the protein shifts the free energy landscape towards hydrophobically collapsed coil conformations responsible for cysteine proximity in hirudin-like folders, compared to semi-extended coil conformations with more distal cysteines in BPTI-like folders. Overall, this work sheds important light on the folding processes and free energy landscapes of cysteinerich peptides and demonstrates the extent to which sequence and length contribute to these landscapes.

biophysics↗

bioRxiv2022

Serum lipoproteins and lipoarabinomannan suppress the inflammatory response induced by the mycolactone toxin

Mycobacterium ulcerans is the causative agent of the chronic and debilitating neglected tropical disease Buruli ulcer (BU) which mostly affects children. The early detection and treatment of M. ulcerans infections can significantly minimize life-long disability resulting from surgical intervention. However, the disease is characterized by relatively few systemic systems as a result of complex host-pathogen interactions that have yet to be fully characterized, which has limited the development of both diagnostic and therapeutic approaches to treat BU. In this work, we study the interactions of the host immune system with two principle M. ulcerans virulence factors: mycolactone, an amphiphilic macrolide toxin, and lipoarabinomannan (LAM), a cell wall component of most mycobacterial pathogens. We observe that human lipoproteins have a profound effect on the interaction of both mycolactone and LAM with the immune system. Individually, both molecules are pro-inflammatory in the absence of serum and immunosuppressive in the presence of serum. When combined, mycolactone and LAM are immunosuppressive regardless of serum conditions. We also show that Toll-like receptor 2 (TLR2), a macrophage pathogen pattern recognition receptor, is critical for LAM immune stimulation but aids in mycolactone immunosuppression. These findings are a first step towards unraveling mycolactone-mediated immunosuppression during BU disease and may facilitate the development of effective diagnostics and therapeutics in the future. Author SummaryBuruli ulcer (BU) is a neglected tropical disease caused by the pathogen Mycobacterium ulcerans. The principal virulence factors associated with it are the macrolide toxin mycolactone and the major cell wall component lipoarabinomannan (LAM). Here, we examine the impact of the amphiphilic biochemistry of mycolactone and LAM on their interaction with the human immune system. We show that both mycolactone and LAM associate with serum lipoproteins, and that this association is critical for the immune evasion seen in early-stage M. ulcerans infections. In the absence of serum, mycolactone is pro-inflammatory. Immunosuppression occurs only in the presence of human serum lipoproteins. In the presence of LAM, mycolactone is immunosuppressive, regardless of serum conditions. Immunosuppression is a hallmark of BU disease, and understanding the mechanisms of this immunosuppression can support the development of effective diagnostic and therapeutic strategies.

microbiology↗