Biology subjects

Kunka, A.

Publications and source records attributed to Kunka, A..

9 recordsLinked to original sources

bioRxiv2026

De novo Design of Polymorph-Specific Binders Targeting α-Synuclein Fibrils

Alpha-synuclein (aSyn) aggregation into amyloid fibrils is a hallmark of synucleinopathies, a group of neurodegenerative disorders that includes Parkinsons disease. Beyond the central role of fibrils in disease pathology and propagation, distinct aSyn fibril polymorphs have been associated with different synucleinopathies, presenting opportunities for differential diagnosis and structure-based disease-specific phenotyping. Here, we present AmyBind, a computational pipeline for the de novo design of mini-protein binders that target polymorph-specific structural features of amyloid fibrils. Using this approach, we developed two aSyn fibril-specific binders, one of which exhibited polymorph-specificity. Neither binder interfered with fibril elongation in vitro, consistent with their designed binding mode on lateral fibril surfaces. In cell-based models, both binders showed polymorph-specific colocalization but did not affect fibril uptake or seeding, indicating their utility as fibril-selective labeling agents in cellular contexts. These findings demonstrate the feasibility of structure-guided, polymorph-specific amyloid targeting and provide a foundation for developing early-stage diagnostics and therapeutics for synucleinopathies and other amyloid-related diseases.

bioengineering↗

bioRxiv2025

Probing the energy landscape of α-Synuclein amyloid fibril formation by systematic K-to-Q mutagenesis

The aggregation of natively disordered -Synuclein (Syn) into amyloid fibrils is a hallmark of Parkinsons and other neurodegenerative diseases. Understanding Syns pathological role remains a major challenge due to its complex, context-dependent energy landscape characterized by conformational plasticity and fibril polymorphism. Here, we present a systematic mutational analysis as a quantitative probe of the Syn energy landscape, focusing on electrostatic contributions to key aggregation pathways. We engineered Syn variants with one to eight lysine-to-glutamine substitutions and analyzed their aggregation under controlled conditions to delineate their effects on nucleation, elongation, seed amplification, fibril stability, and fibril polymorphism. We find that Syn aggregation from a homogenous solution can be modelled well using global properties, including protein concentration, charge, and ionic strength. Microscopic pathways and the resulting fibril polymorphs are instead modulated by sequence-specific effects. We identify mutations of residues found in fibril cores as perturbations that significantly modify the Syn free energy landscape, creating pathways and energy minima not accessible to the WT under the same experimental conditions. In contrast, mutations outside of the fibril core affect the magnitude of the relevant energy barriers whilst overall maintaining a WT-like free energy landscape. Our work outlines a scalable, quantitative framework that increases the informational output of the mutational studies of Syn using conventional assays. The approach can be extended by incorporating additional mutational and functional data to deepen our understanding of Syns energy landscape and its role in health and disease.

biophysics↗

bioRxiv2025

Mechanism-Guided Engineering of Fluorinase Unlocks EfficientNucleophilic Biofluorination

The fluorinase enzyme, the only known biocatalyst forming stable carbon-fluorine bonds, operates with extremely low efficiency, catalyzing one reaction every 2-12 minutes. This severely limits its utility for sustainable biofluorination, and its sluggish activity remains poorly understood. We suppressed its aggregation through directed mutagenesis and elucidated the kinetic mechanism using a novel mathematical framework that fits complex kinetic and oligomerization data. This analysis revealed that >80% of enzyme molecules are inactive under standard conditions due to two dead-end pathways. The designed W50F+A279R mutant preferentially formed hexamers and displayed enhanced catalytic efficiency in this oligomeric state. When coupled with mechanism-based optimization of the reaction medium, including enzymatic removal of the inhibitory product, the catalytic turnover rate reached 12.5 {+/-} 2.1 min-{superscript 1}, representing [~]60-fold increase compared with previously reported turnover rates of the wild-type enzyme. Our work provides a mechanistic blueprint for fluorinase enhancement and a generalizable mathematical framework for analyzing kinetics of multimeric enzymes.

biochemistry↗

bioRxiv2024

Thermodynamic Stability Modulates Chaperone-Mediated Disaggregation of α-Synuclein Fibrils

The aggregation of the intrinsically disordered protein alpha-synuclein into amyloid fibrils and their subsequent intracellular accumulation are characteristic features of several neurodegenerative disorders, such as Parkinsons disease. Currently, there are no curative treatment options available. In this study, we demonstrate that the thermodynamic stability of alpha-synuclein fibrils is a crucial factor influencing the efficiency with which they are disaggregated by the human chaperone system comprising HSP70, DNAJB1, and Apg2. We quantify the increasing stability of alpha-synuclein fibrils formed under four different solution conditions over a three-month incubation period. The chaperone system effectively disaggregates three out of the four fibril types, with varying efficiencies that correlate with their thermodynamic stability. The fibrils exhibit differential sensitivities to chaperone-mediated depolymerization, suggesting that both structural features and thermodynamic stability contribute to the susceptibility of alpha-synuclein fibrils to chaperone disaggregation. Our findings thus reveal a connection between the thermodynamic stability of fibrils and their susceptibility to chaperone-mediated disaggregation.

biophysics↗

bioRxiv2024

Divergent effects of pathological α-synuclein truncations and mutations on phase separation

Phase separated condensates can accelerate -synuclein (-Syn) amyloid fibril formation implicated in Parkinsons disease pathogenesis. The effects of pathological modifications, i.e., truncations and familial mutations on the thermodynamics, material properties, and the extent of amyloid aggregation within -Syn condensates remain elusive. Here, we quantitatively demonstrate that terminal truncations significantly alter -Syn phase separation, while familial mutations impart minimal effects. Spontaneous sol-gel phase transitions of the truncated -Syn variants could give rise to amyloid fibrils almost instantly within condensates, suggesting similarities between molecular interactions driving both processes. Extending our study to model coacervate and condensate systems where -Syn acts as a client, we find -Syn can dissolve coacervates and form Pickering clusters on condensate surfaces--regulating their size. Additionally, the C-terminal region of -Syn modulates nucleic acid sequestration within condensates. Together, our findings reveal diverse effects of -Syn modifications on phase separation, both in pathological and physiological contexts. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=151 SRC="FIGDIR/small/624073v1_ufig1.gif" ALT="Figure 1"> View larger version (52K): org.highwire.dtl.DTLVardef@1760f9dorg.highwire.dtl.DTLVardef@1fb155forg.highwire.dtl.DTLVardef@138402dorg.highwire.dtl.DTLVardef@1fd5229_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2024

Prediction of Aggregation Prone Regions in Proteins Using Deep Neural Networks and Their Suppression by Computational Design

Identification of aggregation-prone regions in proteins and their suppression through mutations is a powerful strategy to enhance protein solubility and yield, significantly expanding their application potential. Here, we developed a deep neural network-based predictor AggreProt, that generates a residue-level aggregation profile for protein sequences. The model outperformed or matched current state-of-the-art algorithms, as validated on two independent datasets comprising hexapeptides and full-length proteins with annotated aggregation-prone regions. We further validated the model experimentally using a set of 34 hexapeptides identified in the model protein haloalkane dehalogenase LinB, along with seven proteins from the AmyPro database. Experimental results agreed with our predictions in 79% of cases and also revealed inaccuracies in some database annotations. Finally, the algorithms utility was demonstrated by identifying aggregation-prone regions in the LinB enzyme and designing mutations to suppress aggregation in its exposed regions. The resulting variants exhibited reduced aggregation propensity, improved solubility, and up to a 100% increase in yield compared to the wild type. AggreProt is freely available to the scientific community via a user- friendly web server: https://loschmidt.chemi.muni.cz/aggreprot.

bioinformatics↗

bioRxiv2023

Effects of Alzheimer's Disease Drug Candidates on Disordered Aβ42 Dissected by Comparative Markov State Analysis (CoVAMPnet)

Computational study of the effect of drug candidates on intrinsically disordered biomolecules is challenging due to their vast and complex conformational space. Here we developed a Comparative Markov State Analysis (CoVAMPnet) framework to quantify changes in the conformational distribution and dynamics of a disordered biomolecule in the presence and absence of small organic drug candidate molecules. First, molecular dynamics trajectories are generated using enhanced sampling, in the presence and absence of small molecule drug candidates, and ensembles of soft Markov state models (MSMs) are learned for each system using unsupervised machine learning. Second, these ensembles of learned MSMs are aligned across different systems based on a solution to an optimal transport problem. Third, the directional importance of inter-residue distances for the assignment to different conformational states is assessed by a discriminative analysis of aggregated neural network gradients. This final step provides interpretability and biophysical context to the learned MSMs. We applied this novel computational framework to assess the effects of ongoing phase 3 therapeutics tramiprosate (TMP) and its metabolite 3-sulfopropanoic acid (SPA) on the disordered A{beta}42 peptide involved in Alzheimers disease. Based on adaptive sampling molecular dynamics and CoVAMPnet analysis, we observed that both TMP and SPA preserved more structured conformations of A{beta}42 by interacting non-specifically with charged residues. SPA impacted A{beta}42 more than TMP, protecting -helices and suppressing the formation of aggregation-prone {beta}-strands. Experimental biophysical analyses showed only mild effects of TMP/SPA on A{beta}42, and activity enhancement by the endogenous metabolization of TMP into SPA. Our data suggest that TMP/SPA may also target other biomolecules than A{beta} peptides. The CoVAMPnet method is broadly applicable to study the effects of drug candidates on the conformational behavior of intrinsically disordered biomolecules. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=109 SRC="FIGDIR/small/523007v2_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@13eea16org.highwire.dtl.DTLVardef@17a6bd1org.highwire.dtl.DTLVardef@3c6b33org.highwire.dtl.DTLVardef@a20444_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2022

Domino-like Effect of C112R Mutation on APOE4 Aggregation and Its Suppression by Alzheimer's Disease Drug Candidate

BackgroundApolipoprotein E (ApoE) {varepsilon}4 genotype is the most prevalent risk factor for late-onset Alzheimers Disease (AD). Although ApoE4 differs from its non-pathological ApoE3 isoform only by the C112R mutation, the molecular mechanism of its proteinopathy is unknown. MethodsHere, we reveal the molecular mechanism of ApoE4 aggregation using a combination of experimental and computational techniques, including X-ray crystallography, site-directed mutagenesis, hydrogen-deuterium mass spectrometry (HDX-MS), static light scattering and molecular dynamics simulations. Treatment of ApoE {varepsilon}3/{varepsilon}3 and {varepsilon}4/{varepsilon}4 cerebral organoids with tramiprosate was used to compare the effect of tramiprosate on ApoE4 aggregation at the cellular level. ResultsWe found that C112R substitution in ApoE4 induces long-distance (>15 [A]) conformational changes leading to the formation of a V-shaped dimeric unit that is geometrically different and more aggregation-prone than the ApoE3 structure. AD drug candidate tramiprosate and its metabolite 3-sulfopropanoic acid induce ApoE3-like conformational behavior in ApoE4 and reduce its aggregation propensity. Analysis of ApoE {varepsilon}4/{varepsilon}4 cerebral organoids treated with tramiprosate revealed its effect on cholesteryl esters, the storage products of excess cholesterol. ConclusionsOur results connect the ApoE4 structure with its aggregation propensity, providing a new druggable target for neurodegeneration and ageing.

neuroscience↗

bioRxiv2017

Computer-Assisted Engineering of Hyperstable Fibroblast Growth Factor 2

Fibroblast growth factors (FGFs) play numerous regulatory functions in complex organisms, and their corresponding therapeutic potential is of growing interest to academics and industrial researchers alike. However, applications of these proteins are limited due to their low stability in vivo and in vitro. Here we tackle this problem using a generalizable computer-assisted protein engineering strategy to create a unique modified FGF2 with nine mutations displaying unprecedented stability and uncompromised biological function.

bioengineering↗