20.500.12556/RUL-186519 De novo načrtovanje inhibitorja proteaze TEV Designing a de novo inhibitor of TEV protease Proteaza virusa jedkanja tobaka (TEVp) je pogosto uporabljeno biotehnološko orodje, za katero trenutno ne poznamo reverzibilnih proteinskih inhibitorjev. Razvoj specifičnega inhibitorja bi razširil nabor njenih aplikacij na področjih sintezne biologije in bionanotehnologije, vključno z razvojem molekularnih mehanosenzorjev. V magistrskem delu smo z uporabo orodij za napovedovanje in načrtovanje struktur, ki temeljijo na globokih nevronskih mrežah (RFdiffusion, ProteinMPNN in AlphaFold2) računalniško de novo zasnovali proteinske vezalce, ki delujejo kot inhibitorji TEVp. Pri načrtovanju smo izhajali iz strukturnih podatkov o interakciji med TEVp in njenim lastnim C-končnim delom, ki se naravno veže v aktivno mesto. Delovanje načrtovanih proteinov smo eksperimentalno ovrednotili z izražanjem v bakteriji E. coli, čiščenjem z afinitetno kromatografijo in kromatografijo z ločevanjem po velikosti ter z merjenjem encimske kinetike. Rezultati so pokazali, da najučinkoviteje delujejo inhibitorji, ki posnemajo vezavo C-končnega dela encima. Analiza s površinsko plazmonsko resonanco (SPR) je pokazala, da imajo najboljši kandidati disociacijske konstante (K$_D$) v nizkem nanomolarnem območju, pri čemer je bila za kandidata A8 določena vrednost K$_D$ 5,5 nM, kandidat A12 pa je izkazal najvišjo afiniteto z vrednostjo K$_D$ 1,75 nM. Z razvojem fuzijskih konstruktov, ki so namenjeni prenosu mehanske sile v bioloških mehanosenzorjih, smo dodatno ugotovili, da vnos specifičnih povezovalcev za preprečitev neželene proteolize nekoliko zmanjša afiniteto vezave v aktivno mesto, vendar proteini kljub temu ohranijo znatno inhibitorno aktivnost. Rezultati potrjujejo uspešnost računalniškega de novo načrtovanja pri razvoju funkcionalnih encimskih inhibitorjev. Tobacco etch virus protease (TEVp) is a prominent and widely used biotechnological tool for which no reversible protein inhibitors are currently known. Developing a specific inhibitor would broaden its applications in synthetic biology and bionanotechnology, notably in the design of molecular mechanosensors. In this master's thesis, we utilized state-of-the-art deep learning pipelines (RFdiffusion, ProteinMPNN, and AlphaFold2) to computationally design de novo protein binders that act as TEVp inhibitors. The design strategy was based on structural data of the interaction between TEVp and its own C-terminus, which naturally binds to the active site. The viability of the computationally designed proteins was experimentally evaluated through their expression in E. coli, purification via affinity and size-exclusion chromatography, and fluorimetric enzyme kinetics measurements. The results demonstrated that inhibitors mimicking the C-terminal binding mechanism of the enzyme were the most effective at reducing proteolytic activity. Furthermore, SPR analysis revealed low-nanomolar dissociation constants (K$_D$) for the top candidates, with A8 yielding a K$_D$ of 5.5 nM and A12 exhibiting the highest binding affinity with a K$_D$ of 1.75 nM. By developing fusion constructs intended for mechanical force transduction in biosensors, we observed that introducing specific linkers to prevent unwanted proteolysis slightly reduced the binding affinity to the active site; nevertheless, the constructs retained substantial inhibitory activity. These findings validate the efficacy of computational de novo design in developing functional enzyme inhibitors. proteaza TEV de novo načrtovanje proteinov inhibitor modeli umetne inteligence RFdiffusion ProteinMPNN in AlphaFold2 TEV protease de novo protein design enzyme inhibitor mechanosensor artificial intelligence models RFdiffusion ProteinMPNN and AlphaFold2 true false false Slovenski jezik Angleški jezik Magistrsko delo/naloga 2026-09-02 15:10:33 2026-09-02 15:10:50 2026-09-25 09:55:58 0000-00-00 00:00:00 2026 0 0 0000-00-00 NiDoloceno NiDoloceno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 2027-09-02 25480 292475651 Hafner_Luka_-_De_novo_nacrtovanje_inhibitorja_proteaze_TEV.pdf Hafner_Luka_-_De_novo_nacrtovanje_inhibitorja_proteaze_TEV.pdf 1 A693ADF5945A09E9B32BDD6D63B31731 d07c0be852ed83e446582e1056d2659fe844e2a217987aec6c6d5a9988fda2c8 4fd888ac-a6cf-11f1-9b0d-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=245791 Fakulteta za kemijo in kemijsko tehnologijo 0 0 0