Discovery of NSD2 non-histone substrates and design of a super-substrate.

The human protein lysine methyltransferase NSD2 catalyzes dimethylation at H3K36. It has very important roles in development and disease but many mechanistic features and its full spectrum of substrate proteins are unclear. Using peptide SPOT array methylation assays, we investigate the substrate sequence specificity of NSD2 and discover strong readout of residues between G33 (-3) and P38 (+2) on H3K36. Unexpectedly, we observe that amino acid residues different from natural ones in H3K36 are preferred at some positions. Combining four preferred residues led to the development of a super-substrate which is methylated much faster by NSD2 at peptide and protein level. Molecular dynamics simulations demonstrate that this activity increase is caused by distinct hyperactive conformations of the enzyme-peptide complex. To investigate the substrate spectrum of NSD2, we conducted a proteome wide search for nuclear proteins matching the specificity profile and discovered 22 peptide substrates of NSD2. In protein methylation studies, we identify K1033 of ATRX and K819 of FANCM as NSD2 methylation sites and also demonstrate their methylation in human cells. Both these proteins have important roles in DNA repair strengthening the connection of NSD2 and H3K36 methylation to DNA repair.

Approaching the catalytic mechanism of protein lysine methyltransferases by biochemical and simulation techniques.

Protein lysine methyltransferases (PKMTs) transfer up to three methyl groups to the side chains of lysine residues in proteins and fulfill important regulatory functions by controlling protein stability, localization and protein/protein interactions. The methylation reactions are highly regulated, and aberrant methylation of proteins is associated with several types of diseases including neurologic disorders, cardiovascular diseases, and various types of cancer. This review describes novel insights into the catalytic machinery of various PKMTs achieved by the combined application of biochemical experiments and simulation approaches during the last years, focusing on clinically relevant and well-studied enzymes of this group like DOT1L, SMYD1-3, SET7/9, G9a/GLP, SETD2, SUV420H2, NSD1/2, different MLLs and EZH2. Biochemical experiments have unraveled many mechanistic features of PKMTs concerning their substrate and product specificity, processivity and the effects of somatic mutations observed in PKMTs in cancer cells. Structural data additionally provided information about the substrate recognition, enzyme-substrate complex formation, and allowed for simulations of the substrate peptide interaction and mechanism of PKMTs with atomistic resolution by molecular dynamics and hybrid quantum mechanics/molecular mechanics methods. These simulation technologies uncovered important mechanistic details of the PKMT reaction mechanism including the processes responsible for the deprotonation of the target lysine residue, essential conformational changes of the PKMT upon substrate binding, but also rationalized regulatory principles like PKMT autoinhibition. Further developments are discussed that could bring us closer to a mechanistic understanding of catalysis of this important class of enzymes in the near future. The results described here illustrate the power of the investigation of enzyme mechanisms by the combined application of biochemical experiments and simulation technologies.

The T1150A cancer mutant of the protein lysine dimethyltransferase NSD2 can introduce H3K36 trimethylation.

Protein lysine methyltransferases (PKMTs) play essential roles in gene expression regulation and cancer development. Somatic mutations in PKMTs are frequently observed in cancer cells. In biochemical experiments, we show here that the NSD1 mutations Y1971C, R2017Q, and R2017L observed mostly in solid cancers are catalytically inactive suggesting that NSD1 acts as a tumor suppressor gene in these tumors. In contrast, the frequently observed T1150A in NSD2 and its T2029A counterpart in NSD1, both observed in leukemia, are hyperactive and introduce up to three methyl groups in H3K36 in biochemical and cellular assays, while wildtype NSD2 and NSD1 only introduce up to two methyl groups. In Molecular Dynamics simulations, we determined key mechanistic and structural features controlling the product specificity of this class of enzymes. Simulations with NSD2 revealed that H3K36me3 formation is possible due to an enlarged active site pocket of T1150A and loss of direct contacts of T1150 to critical residues which regulate the product specificity of NSD2. Bioinformatic analyses of published data suggested that the generation of H3K36me3 by NSD2 T1150A could alter gene regulation by antagonizing H3K27me3 finally leading to the upregulation of oncogenes.

FAIR and scalable management of small-angle X-ray scattering data.

A modular research data management toolbox based on the programming language Python, the widely used computing platform Jupyter Notebook, the standardized data exchange format for analytical data (AnIML) and the generic repository Dataverse has been established and applied to analyze small-angle X-ray scattering (SAXS) data according to the FAIR data principles (findable, accessible, interoperable and reusable). The SAS-tools library is a community-driven effort to develop tools for data acquisition, analysis, visualization and publishing of SAXS data. Metadata from the experiment and the results of data analysis are stored as an AnIML document using the novel Python-native pyAnIML API. The AnIML document, measured raw data and plots resulting from the analysis are combined into an archive in OMEX format and uploaded to Dataverse using the novel easyDataverse API, which makes each data set accessible via a unique DOI and searchable via a structured metadata block. SAS-tools is applied to study the effects of alkyl chain length and counterions on the phase diagrams of alkyltrimethyl-ammonium surfactants in order to demonstrate the feasibility and usefulness of a scalable data management workflow for experiments in physical chemistry.

Bayesian estimation reveals that reproducible models in Systems Biology get more citations.

The Systems Biology community has taken numerous actions to develop data and modeling standards towards FAIR data and model handling. Nevertheless, the debate about incentives and rewards for individual researchers to make their results reproducible is ongoing. Here, we pose the specific question of whether reproducible models have a higher impact in terms of citations. Therefore, we statistically analyze 328 published models recently classified by Tiwari et al. based on their reproducibility. For hypothesis testing, we use a flexible Bayesian approach that provides complete distributional information for all quantities of interest and can handle outliers. The results show that in the period from 2013, i.e., 10 years after the introduction of SBML, to 2020, the group of reproducible models is significantly more cited than the non-reproducible group. We show that differences in journal impact factors do not explain this effect and that this effect increases with additional standardization of data and error model integration via PEtab. Overall, our statistical analysis demonstrates the long-term merits of reproducible modeling for the individual researcher in terms of citations. Moreover, it provides evidence for the increased use of reproducible models in the scientific community.

EnzymeML: seamless data flow and modeling of enzymatic data.

The design of biocatalytic reaction systems is highly complex owing to the dependency of the estimated kinetic parameters on the enzyme, the reaction conditions, and the modeling method. Consequently, reproducibility of enzymatic experiments and reusability of enzymatic data are challenging. We developed the XML-based markup language EnzymeML to enable storage and exchange of enzymatic data such as reaction conditions, the time course of the substrate and the product, kinetic parameters and the kinetic model, thus making enzymatic data findable, accessible, interoperable and reusable (FAIR). The feasibility and usefulness of the EnzymeML toolbox is demonstrated in six scenarios, for which data and metadata of different enzymatic reactions are collected and analyzed. EnzymeML serves as a seamless communication channel between experimental platforms, electronic lab notebooks, tools for modeling of enzyme kinetics, publication platforms and enzymatic reaction databases. EnzymeML is open and transparent, and invites the community to contribute. All documents and codes are freely available at https://enzymeml.org .

Processing of a plant peptide hormone precursor facilitated by posttranslational tyrosine sulfation.

Most peptide hormones and growth factors are matured from larger inactive precursor proteins by proteolytic processing and further posttranslational modification. Whether or how posttranslational modifications contribute to peptide bioactivity is still largely unknown. We address this question here for TWS1 (Twisted Seed 1), a peptide regulator of embryonic cuticle formation in Arabidopsis thaliana. Using synthetic peptides encompassing the N- and C-terminal processing sites and the recombinant TWS1 precursor as substrates, we show that the precursor is cleaved by the subtilase SBT1.8 at both the N and the C termini of TWS1. Recognition and correct processing at the N-terminal site depended on sulfation of an adjacent tyrosine residue. Arginine 302 of SBT1.8 was found to be required for sulfotyrosine binding and for accurate processing of the TWS1 precursor. The data reveal a critical role for posttranslational modification, here tyrosine sulfation of a plant peptide hormone precursor, in mediating processing specificity and peptide maturation.

Preferential Self-interaction of DNA Methyltransferase DNMT3A Subunits Containing the R882H Cancer Mutation Leads to Dominant Changes of Flanking Sequence Preferences.

Somatic R882H DNMT3A mutations occur frequently in AML, but their pathogenic mechanism is unclear. As R882H mutations usually are heterozygous, wildtype (WT) and R882H subunits co-exist in affected cells. R882 is located in the RD interface of DNMT3A tetramers, which forms the DNA binding site. R882H causes strong changes in the flanking sequence preferences of DNMT3A. Here, we analyzed flanking sequence preferences for CGNNNN sites showing that most disfavored sites are methylated 4-5 fold slower by R882H than WT, while it methylates most preferred sites 2-fold faster. Overall, R882H was more active than WT at 13% and less active at 52% of all CGNNNN sites. We prepared mixed DNMT3A heterotetramers containing WT and R882H subunits and show that mixed complexes preferentially assemble with an R882H/R882H RD interface. Structural comparisons and MD simulations confirmed the conclusion that the R882H RD interface is more stable than that of WT, in part because H882 forms an inter-subunit contact in the RD interface, while R882 contacts the DNA. As the subunits at the RD interface contribute the two active centers to the DNMT3A tetramer, R882H characteristic flanking sequence preferences of DNMT3A were observed in mixed tetrameric complexes containing WT and R882H subunits, and they are not diluted by the "averaged" effects of mixed or WT interfaces. Hence, R882H has a dominant effect on the flanking sequence preferences and other catalytic properties of DNMT3A in samples containing WT and R882H subunits, which may explain its pathogenic effect in heterozygous state.

Plastics degradation by hydrolytic enzymes: The plastics-active enzymes database-PAZy.

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.

EnzymeML-a data exchange format for biocatalysis and enzymology.

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.

Mechanistic basis of the increased methylation activity of the SETD2 protein lysine methyltransferase towards a designed super-substrate peptide.

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.

Ancestral sequences of a large promiscuous enzyme family correspond to bridges in sequence space in a network representation.

Evolutionary relationships of protein families can be characterized either by networks or by trees. Whereas trees allow for hierarchical grouping and reconstruction of the most likely ancestral sequences, networks lack a time axis but allow for thresholds of pairwise sequence identity to be chosen and, therefore, the clustering of family members with presumably more similar functions. Here, we use the large family of arylsulfatases and phosphonate monoester hydrolases to investigate similarities, strengths and weaknesses in tree and network representations. For varying thresholds of pairwise sequence identity, values of betweenness centrality and clustering coefficients were derived for nodes of the reconstructed ancestors to measure the propensity to act as a bridge in a network. Based on these properties, ancestral protein sequences emerge as bridges in protein sequence networks. Interestingly, many ancestral protein sequences appear close to extant sequences. Therefore, reconstructed ancestor sequences might also be interpreted as yet-to-be-identified homologues. The concept of ancestor reconstruction is compared to consensus sequences, too. It was found that hub sequences in a network, e.g. reconstructed ancestral sequences that are connected to many neighbouring sequences, share closer similarity with derived consensus sequences. Therefore, some reconstructed ancestor sequences can also be interpreted as consensus sequences.

The GH19 Engineering Database: Sequence diversity, substrate scope, and evolution in glycoside hydrolase family 19.

The glycoside hydrolase 19 (GH19) is a bifunctional family of chitinases and endolysins, which have been studied for the control of plant fungal pests, the recycle of chitin biomass, and the treatment of multi-drug resistant bacteria. The GH19 domain-containing sequences (22,461) were divided into a chitinase and an endolysin subfamily by analyzing sequence networks, guided by taxonomy and the substrate specificity of characterized enzymes. The chitinase subfamily was split into seventeen groups, thus extending the previous classification. The endolysin subfamily is more diverse and consists of thirty-four groups. Despite their sequence diversity, twenty-six residues are conserved in chitinases and endolysins, which can be distinguished by two specific sequence patterns at six and four positions, respectively. Their location outside the catalytic cleft suggests a possible mechanism for substrate specificity that goes beyond the direct interaction with the substrate. The evolution of the GH19 catalytic domain was investigated by large-scale phylogeny. The inferred evolutionary history and putative horizontal gene transfer events differ from previous works. While no clear patterns were detected in endolysins, chitinases varied in sequence length by up to four loop insertions, causing at least eight distinct presence/absence loop combinations. The annotated GH19 sequences and structures are accessible via the GH19 Engineering Database (GH19ED, https://gh19ed.biocatnet.de). The GH19ED has been developed to support the prediction of substrate specificity and the search for novel GH19 enzymes from neglected taxonomic groups or in regions of the sequence space where few sequences have been described yet.

Molecular Mechanism of Methanol Inhibition in CALB-Catalyzed Alcoholysis: Analyzing Molecular Dynamics Simulations by a Markov State Model.

Lipases are widely used enzymes that catalyze hydrolysis and alcoholysis of fatty acid esters. At high concentrations of small alcohols such as methanol or ethanol, many lipases are inhibited by the substrate. The molecular basis of the inhibition of Candida antarctica lipase B (CALB) by methanol was investigated by unbiased molecular dynamics (MD) simulations, and the substrate binding kinetics was analyzed by Markov state models (MSMs). The modeled fluxes of productive methanol binding at concentrations between 50 mM and 5.5 M were in good agreement with the experimental activity profile of CALB, with a peak at 300 mM. The kinetic and structural analysis uncovered the molecular basis of CALB inhibition. Beyond 300 mM, the kinetic bottleneck results from crowding of methanol in the substrate access channel, which is caused by the gradual formation of methanol patches close to Leu140 (helix α5), Leu278, and Ile285 (helix α10) at a distance of 4-5 Å from the active site. Our findings demonstrate the usefulness of unbiased MD simulations to study enzyme-substrate interactions at realistic substrate concentrations and the feasibility of scale-bridging by an MSM analysis to derive kinetic information.

Inverting the Stereoselectivity of an NADH-Dependent Imine-Reductase Variant.

Imine reductases (IREDs) offer biocatalytic routes to chiral amines and have a natural preference for the NADPH cofactor. In previous work, we reported enzyme engineering of the (R)-selective IRED from Myxococcus stipitatus (NADH-IRED-Ms) yielding a NADH-dependent variant with high catalytic efficiency. However, no IRED with NADH specificity and (S)-selectivity in asymmetric reductions has yet been reported. Herein, we applied semi-rational enzyme engineering to switch the selectivity of NADH-IRED-Ms. The quintuple variant A241V/H242Y/N243D/V244Y/A245L showed reverse stereopreference in the reduction of the cyclic imine 2-methylpyrroline compared to the wild-type and afforded the (S)-amine product with >99 % conversion and 91 % enantiomeric excess. We also report the crystal-structures of the NADPH-dependent (R)-IRED-Ms wild-type enzyme and the NADH-dependent NADH-IRED-Ms variant and molecular dynamics (MD) simulations to rationalize the inverted stereoselectivity of the quintuple variant.

Expansin Engineering Database: A navigation and classification tool for expansins and homologues.

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.

Meta-analysis of viscosity of aqueous deep eutectic solvents and their components.

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 [Formula: see text]= 3-5 kJ/mol, whereas reline had a negative excess activation energy ([Formula: see text]= - 19 kJ/mol). The data and workflows used are accessible at  https://doi.org/10.15490/FAIRDOMHUB.1.STUDY.767.1 .

Engineering of Thermostable ß-Hydroxyacid Dehydrogenase for the Asymmetric Reduction of Imines.

The ß-hydroxyacid dehydrogenase from Thermocrinus albus (Ta-ßHAD), which catalyzes the NADP+ -dependent oxidation of ß-hydroxyacids, was engineered to accept imines as substrates. The catalytic activity of the proton-donor variant K189D was further increased by the introduction of two nonpolar flanking residues (N192 L, N193 L). Engineering the putative alternative proton donor (D258S) and the gate-keeping residue (F250 A) led to a switched substrate specificity as compared to the single and triple variants. The two most active Ta-ßHAD variants were applied to biocatalytic asymmetric reductions of imines at elevated temperatures and enabled enhanced product formation at a reaction temperature of 50 °C.

Multicopper oxidases: modular structure, sequence space, and evolutionary relationships.

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.

Systematic Evaluation of Imine-Reducing Enzymes: Common Principles in Imine Reductases, ß-Hydroxy Acid Dehydrogenases, and Short-Chain Dehydrogenases/ Reductases.

The enzymatic, asymmetric reduction of imines is catalyzed by imine reductases (IREDs), members of the short-chain dehydrogenase/reductase (SDR) family, and ß-hydroxy acid dehydrogenase (ßHAD) variants. Systematic evaluation of the structures and substrate-binding sites of the three enzyme families has revealed four common principles for imine reduction: structurally conserved cofactor-binding domains; tyrosine, aspartate, or glutamate as proton donor; at least four characteristic flanking residues that adapt the donor's pKa and polarize the substrate; and a negative electrostatic potential in the substrate-binding site to stabilize the transition state. As additional catalytically relevant positions, we propose alternative proton donors in IREDs and ßHADs as well as proton relays in IREDs, ßHADs, and SDRs. The functional role of flanking residues was experimentally confirmed by alanine scanning of the imine-reducing SDR from Zephyranthes treatiae. Mutating the "gatekeeping" phenylalanine at standard position 200 resulted in a tenfold increase in imine-reducing activity.