03 Fakultät Chemie

Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/4

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Author: search.filters.author.Pleiss, JürgenSubject: search.filters.subject.570

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    Visual analysis of large‐scale protein‐ligand interaction data
    (2021) Schatz, Karsten; Franco‐Moreno, Juan José; Schäfer, Marco; Rose, Alexander S.; Ferrario, Valerio; Pleiss, Jürgen; Vázquez, Pere‐Pau; Ertl, Thomas; Krone, Michael
    When studying protein‐ligand interactions, many different factors can influence the behaviour of the protein as well as the ligands. Molecular visualisation tools typically concentrate on the movement of single ligand molecules; however, viewing only one molecule can merely provide a hint of the overall behaviour of the system. To tackle this issue, we do not focus on the visualisation of the local actions of individual ligand molecules but on the influence of a protein and their overall movement. Since the simulations required to study these problems can have millions of time steps, our presented system decouples visualisation and data preprocessing: our preprocessing pipeline aggregates the movement of ligand molecules relative to a receptor protein. For data analysis, we present a web‐based visualisation application that combines multiple linked 2D and 3D views that display the previously calculated data The central view, a novel enhanced sequence diagram that shows the calculated values, is linked to a traditional surface visualisation of the protein. This results in an interactive visualisation that is independent of the size of the underlying data, since the memory footprint of the aggregated data for visualisation is constant and very low, even if the raw input consisted of several terabytes.
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    EnzymeML : a data exchange format for biocatalysis and enzymology
    (2021) Range, Jan; Halupczok, Colin; Lohmann, Jens; Swainston, Neil; Kettner, Carsten; Bergmann, Frank T.; Weidemann, Andreas; Wittig, Ulrike; Schnell, Santiago; Pleiss, Jürgen
    EnzymeML is an XML‐based data exchange format that supports the comprehensive documentation of enzymatic data by describing reaction conditions, time courses of substrate and product concentrations, the kinetic model, and the estimated kinetic constants. EnzymeML is based on the Systems Biology Markup Language, which was extended by implementing the STRENDA Guidelines. An EnzymeML document serves as a container to transfer data between experimental platforms, modeling tools, and databases. EnzymeML supports the scientific community by introducing a standardized data exchange format to make enzymatic data findable, accessible, interoperable, and reusable according to the FAIR data principles. An application programming interface in Python supports the integration of software tools for data acquisition, data analysis, and publication. The feasibility of a seamless data flow using EnzymeML is demonstrated by creating an EnzymeML document from a structured spreadsheet or from a STRENDA DB database entry, by kinetic modeling using the modeling platform COPASI, and by uploading to the enzymatic reaction kinetics database SABIO‐RK.
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    Plastics degradation by hydrolytic enzymes : the Plastics-Active Enzymes Database - PAZy
    (2022) Buchholz, Patrick C. F.; Feuerriegel, Golo; Zhang, Hongli; Perez‐Garcia, Pablo; Nover, Lena‐Luisa; Chow, Jennifer; Streit, Wolfgang R.; Pleiss, Jürgen
    Petroleum‐based plastics are durable and accumulate in all ecological niches. Knowledge on enzymatic degradation is sparse. Today, less than 50 verified plastics‐active enzymes are known. First examples of enzymes acting on the polymers polyethylene terephthalate (PET) and polyurethane (PUR) have been reported together with a detailed biochemical and structural description. Furthermore, very few polyamide (PA) oligomer active enzymes are known. In this article, the current known enzymes acting on the synthetic polymers PET and PUR are briefly summarized, their published activity data were collected and integrated into a comprehensive open access database. The Plastics‐Active Enzymes Database (PAZy) represents an inventory of known and experimentally verified enzymes that act on synthetic fossil fuel‐based polymers. Almost 3000 homologs of PET‐active enzymes were identified by profile hidden Markov models. Over 2000 homologs of PUR‐active enzymes were identified by BLAST. Based on multiple sequence alignments, conservation analysis identified the most conserved amino acids, and sequence motifs for PET‐ and PUR‐active enzymes were derived.
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    Expansin Engineering Database : a navigation and classification tool for expansins and homologues
    (2020) Lohoff, Caroline; Buchholz, Patrick C. F.; Le Roes‐Hill, Marilize; Pleiss, Jürgen
    Expansins have the remarkable ability to loosen plant cell walls and cellulose material without showing catalytic activity and therefore have potential applications in biomass degradation. To support the study of sequence‐structure‐function relationships and the search for novel expansins, the Expansin Engineering Database (ExED, https://exed.biocatnet.de) collected sequence and structure data on expansins from Bacteria, Fungi, and Viridiplantae, and expansin‐like homologues such as carbohydrate binding modules, glycoside hydrolases, loosenins, swollenins, cerato‐platanins, and EXPNs. Based on global sequence alignment and protein sequence network analysis, the sequences are highly diverse. However, many similarities were found between the expansin domains. Newly created profile hidden Markov models of the two expansin domains enable standard numbering schemes, comprehensive conservation analyses, and genome annotation. Conserved key amino acids in the expansin domains were identified, a refined classification of expansins and carbohydrate binding modules was proposed, and new sequence motifs facilitate the search of novel candidate genes and the engineering of expansins.
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    Meta-analysis of viscosity of aqueous deep eutectic solvents and their components
    (2020) Gygli, Gudrun; Xu, Xinmeng; Pleiss, Jürgen
    Deep eutectic solvents (DES) formed by quaternary ammonium salts and hydrogen bond donors are a promising green alternative to organic solvents. Their high viscosity at ambient temperatures can limit biocatalytic applications and therefore requires fine-tuning by adjusting water content and temperature. Here, we performed a meta-analysis of the impact of water content and temperature on the viscosities of four deep eutectic solvents (glyceline, reline, N,N-diethylethanol ammonium chloride-glycerol, N,N-diethylethanol ammonium chloride-ethylene glycol), their components (choline chloride, urea, glycerol, ethylene glycol), methanol, and pure water. We analyzed the viscosity data by an automated workflow, using Arrhenius and Vogel-Fulcher-Tammann-Hesse models. The consistency and completeness of experimental data and metadata was used as an essential criterion of data quality. We found that viscosities were reported for different temperature ranges, half the time without specifying a method of desiccation, and in almost half of the reports without specifying experimental errors. We found that the viscosity of the pure components varied widely, but that all aqueous mixtures (except for reline) have similar excess activation energy of viscous flow Eexcessη= 3-5 kJ/mol, whereas reline had a negative excess activation energy (Eexcessη= - 19 kJ/mol). The data and workflows used are accessible at https://doi.org/10.15490/FAIRDOMHUB.1.STUDY.767.1.
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    Multicopper oxidases : modular structure, sequence space, and evolutionary relationships
    (2020) Gräff, Maike; Buchholz, Patrick C. F.; Le Roes‐Hill, Marilize; Pleiss, Jürgen
    Multicopper oxidases (MCOs) use copper ions as cofactors to oxidize a variety of substrates while reducing oxygen to water. MCOs have been identified in various taxa, with notable occurrences in fungi. The role of these fungal MCOs in lignin degradation sparked an interest due to their potential for application in biofuel production and various other industries. MCOs consist of different protein domains, which led to their classification into two‐, three‐, and six‐domain MCOs. The previously established Laccase and Multicopper Oxidase Engineering Database (https://lcced.biocatnet.de) was updated and now includes 51 058 sequences and 229 structures of MCOs. Sequences and structures of all MCOs were systematically compared. All MCOs consist of cupredoxin‐like domains. Two‐domain MCOs are formed by the N‐ and C‐terminal domain (domain N and C), while three‐domain MCOs have an additional domain (M) in between, homologous to domain C. The six‐domain MCOs consist of alternating domains N and C, each three times. Two standard numbering schemes were developed for the copper‐binding domains N and C, which facilitated the identification of conserved positions and a comparison to previously reported results from mutagenesis studies. Two sequence motifs for the copper binding sites were identified per domain. Their modularity, depending on the placement of the T1‐copper binding site, was demonstrated. Protein sequence networks showed relationships between two‐ and three‐domain MCOs, allowing for family‐specific annotation and inference of evolutionary relationships.
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    Mechanistic basis of the increased methylation activity of the SETD2 protein lysine methyltransferase towards a designed super-substrate peptide
    (2022) Schnee, Philipp; Choudalakis, Michel; Weirich, Sara; Khella, Mina S.; Carvalho, Henrique; Pleiss, Jürgen; Jeltsch, Albert
    Protein lysine methyltransferases have important regulatory functions in cells, but mechanisms determining their activity and specificity are incompletely understood. Naturally, SETD2 introduces H3K36me3, but previously an artificial super-substrate (ssK36) was identified, which is methylated >100-fold faster. The ssK36-SETD2 complex structure cannot fully explain this effect. We applied molecular dynamics (MD) simulations and biochemical experiments to unravel the mechanistic basis of the increased methylation of ssK36, considering peptide conformations in solution, association of peptide and enzyme, and formation of transition-state (TS) like conformations of the enzyme-peptide complex. We observed in MD and FRET experiments that ssK36 adopts a hairpin conformation in solution with V35 and K36 placed in the loop. The hairpin conformation has easier access into the active site of SETD2 and it unfolds during the association process. Peptide methylation experiments revealed that introducing a stable hairpin conformation in the H3K36 peptide increased its methylation by SETD2. In MD simulations of enzyme-peptide complexes, the ssK36 peptide approached TS-like structures more frequently than H3K36 and distinct, substrate-specific TS-like structures were observed. Hairpin association, hairpin unfolding during association, and substrate-specific catalytically competent conformations may also be relevant for other PKMTs and hairpins could represent a promising starting point for SETD2 inhibitor development.