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© 2014 American Chemical Society.Mercuric reductase, MerA, is a key enzyme in bacterial mercury resistance. This homodimeric enzyme captures and reduces toxic Hg2+ to Hg0, which is relatively unreactive and can exit the cell passively. Prior to reduction,

Mercury (Hg) is a heavy metal that exhibits high biological toxicity. Monomethylmercury and dimethylmercury are neurotoxins and a significant environmental concern as they bioaccumulate and biomagnify within the aquatic food web. Microbial Hg methylation involves two proteins, HgcA and HgcB. Here, we show that HgcA and HgcB can be heterologously coexpressed, and the HgcAB complex can be purified. We demonstrated that HgcA is a membrane-associated cobalamin-dependent methyltransferase and HgcB is a ferredoxin-like protein containing two [4Fe-4S] clusters. Further, spectroscopic and kinetic results demonstrate that S-adenosyl-L-methionine (SAM) donates the methyl group to Hg in a two-step reaction involving a methylcob(III)alamin intermediate including Co-thiolate ligation from a conserved Cys residue. Our findings uncover a biological role for SAM in microbial Hg methylation., Competing Interests: Competing interests statement:The authors declare no competing interest.

Less than 1% of native prairie lands remain in the United States. Located in eastern Washington, the rare habitat called Palouse prairie was largely converted to wheat monocropping. With this conversion came numerous physical, chemical, and biological changes to the soil that may ultimately contribute to reduced wheat yields. Here, we explored how wheat ( Tritcum aestivum L.) seedling establishment, plant size, and heading, signifying the developmental transition to flowering, were affected by being planted in prairie soil versus agricultural soils. We then sought to understand whether the observed effects were the result of changes to the soil microbiota due to agricultural intensification. We found that prairie soil enhanced both the probability of wheat seedling survival and heading compared to agricultural soil; however, wheat growth was largely unaffected by soil source. We did not detect effects on wheat developmental transitions or phenotype when inoculated with prairie microbes compared with agricultural microbes, but we did observe general antagonistic effects of microbes on plant size, regardless of soil source. This work indicates that agricultural intensification has affected soils in a way that changes early seedling establishment and the timing of heading for wheat, but these effects may not be caused by microbes, and instead may be caused by soil nutrient conditions., Competing Interests: The authors have no relevant financial or non-financial interests to disclose.

Pyridoxal 5'-phosphate (PLP), the biologically active form of vitamin B 6 , is an essential cofactor in many biosynthetic pathways. The emergence of PLP-dependent enzymes as drug targets and biocatalysts, such as tryptophan synthase (TS), has underlined the demand to understand PLP-dependent catalysis and reaction specificity. The ability of neutron diffraction to resolve the positions of hydrogen atoms makes it an ideal technique to understand how the electrostatic environment and selective protonation of PLP regulates PLP-dependent activities. Facilitated by microgravity crystallization of TS with the Toledo Crystallization Box, we report the 2.1 Å joint X-ray/neutron (XN) structure of TS with PLP in the internal aldimine form. Positions of hydrogens were directly determined in both the α- and β-active sites, including PLP cofactor. The joint XN structure thus provides insight into the selective protonation of the internal aldimine and the electrostatic environment of TS necessary to understand the overall catalytic mechanism., Competing Interests: DECLARATION OF INTERESTS The authors declare no competing interests.

Motivation: Sphagnum-dominated peatlands store a substantial amount of terrestrial carbon. The genus is undersampled and under-studied. No experimental crystal structure from any Sphagnum species exists in the Protein Data Bank and fewer than 200 Sphagnum-related genes have structural models available in the AlphaFold Protein Structure Database. Tools and resources are needed to help bridge these gaps, and to enable the analysis of other structural proteomes now made possible by accurate structure prediction., Results: We present the predicted structural proteome (25 134 primary transcripts) of Sphagnum divinum computed using AlphaFold, structural alignment results of all high-confidence models against an annotated nonredundant crystallographic database of over 90,000 structures, a structure-based classification of putative Enzyme Commission (EC) numbers across this proteome, and the computational method to perform this proteome-scale structure-based annotation., Availability and Implementation: All data and code are available in public repositories, detailed at https://github.com/BSDExabio/SAFA. The structural models of the S. divinum proteome have been deposited in the ModelArchive repository at https://modelarchive.org/doi/10.5452/ma-ornl-sphdiv., (© The Author(s) 2023. Published by Oxford University Press.)

Membrane efflux pumps play a major role in bacterial multidrug resistance. The tripartite multidrug efflux pump system from Escherichia coli, AcrAB-TolC, is a target for inhibition to lessen resistance development and restore antibiotic efficacy, with homologs in other ESKAPE pathogens. Here, we rationalize a mechanism of inhibition against the periplasmic adaptor protein, AcrA, using a combination of hydrogen/deuterium exchange mass spectrometry, cellular efflux assays, and molecular dynamics simulations. We define the structural dynamics of AcrA and find that an inhibitor can inflict long-range stabilisation across all four of its domains, whereas an interacting efflux substrate has minimal effect. Our results support a model where an inhibitor forms a molecular wedge within a cleft between the lipoyl and αβ barrel domains of AcrA, diminishing its conformational transmission of drug-evoked signals from AcrB to TolC. This work provides molecular insights into multidrug adaptor protein function which could be valuable for developing antimicrobial therapeutics., (© 2023. The Author(s).)

Background: In a previous paper, we classified populated HLA class I alleles into supertypes and subtypes based on the similarity of 3D landscape of peptide binding grooves, using newly defined structure distance metric and hierarchical clustering approach. Compared to other approaches, our method achieves higher correlation with peptide binding specificity, intra-cluster similarity (cohesion), and robustness. Here we introduce HLA-Clus, a Python package for clustering HLA Class I alleles using the method we developed recently and describe additional features including a new nearest neighbor clustering method that facilitates clustering based on user-defined criteria., Results: The HLA-Clus pipeline includes three stages: First, HLA Class I structural models are coarse grained and transformed into clouds of labeled points. Second, similarities between alleles are determined using a newly defined structure distance metric that accounts for spatial and physicochemical similarities. Finally, alleles are clustered via hierarchical or nearest-neighbor approaches. We also interfaced HLA-Clus with the peptide:HLA affinity predictor MHCnuggets. By using the nearest neighbor clustering method to select optimal allele-specific deep learning models in MHCnuggets, the average accuracy of peptide binding prediction of rare alleles was improved., Conclusions: The HLA-Clus package offers a solution for characterizing the peptide binding specificities of a large number of HLA alleles. This method can be applied in HLA functional studies, such as the development of peptide affinity predictors, disease association studies, and HLA matching for grafting. HLA-Clus is freely available at our GitHub repository ( https://github.com/yshen25/HLA-Clus )., (© 2023. The Author(s).)

The hgcAB gene pair encodes mercury (Hg) methylation capability in a diverse group of microorganisms, but its evolution and transcriptional regulation remain unknown. Working from the possibility that the evolutionary function of HgcAB may not be Hg methylation, we test a possible link to arsenic resistance. Using model Hg methylator Pseudodesulfovibrio mercurii ND132, we evaluated transcriptional control of hgcAB by a putative ArsR encoded upstream and cotranscribed with hgcAB . This regulator shares homology with ArsR repressors of arsenic resistance and S -adenosylhomocysteine (SAH)-responsive regulators of methionine biosynthesis but is distinct from other ArsR/SahR proteins in P. mercurii . Using quantitative PCR (qPCR) and RNA sequencing (RNA-seq) transcriptome analyses, we confirmed this ArsR regulates hgcAB transcription and is responsive to arsenic and SAH. Additionally, RNA-seq indicated a possible link between hgcAB activity and arsenic transformations, with significant upregulation of other ArsR-regulated arsenic resistance operons alongside hgcAB . Interestingly, wild-type ND132 was less sensitive to As(V) (but not As(III)) than an hgcAB knockout strain, supporting the idea that hgcAB may be linked to arsenic resistance. Arsenic significantly impacted rates of Hg methylation by ND132; however, responses varied with culture conditions. Differences in growth and metabolic activity did not account for arsenic impacts on methylation. While arsenic significantly increased hgcAB expression, hgcAB gene and transcript abundance was not a good predictor of Hg methylation rates. Taken together, these results support the idea that Hg and As cycling are linked in P. mercurii ND132. Our results may hold clues to the evolution of hgcAB and the controls on Hg methylation in nature. IMPORTANCE This work reveals a link between microbial mercury methylation and arsenic resistance and may hold clues to the evolution of mercury methylation genes ( hgcAB ). Microbes with hgcAB produce methylmercury, a strong neurotoxin that readily accumulates in the food web. This study addresses a critical gap in our understanding about the environmental factors that control hgcAB expression. We show that hgcAB expression is controlled by an ArsR-like regulator responsive to both arsenic and S -adenosylhomocysteine in our model organism, Pseudodesulfovibrio mercurii ND132. Exposure to arsenic also significantly impacted Pseudodesulfovibrio mercurii ND132 mercury methylation rates. However, expression of hgcAB was not always a good predictor of Hg methylation rates, highlighting the roles of Hg bioavailability and other biochemical mechanisms in methylmercury production. This study improves our understanding of the controls on hgcAB expression, which is needed to better predict environmental methylmercury production.

Direct-acting antivirals are needed to combat coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). The papain-like protease (PLpro) domain of Nsp3 from SARS-CoV-2 is essential for viral replication. In addition, PLpro dysregulates the host immune response by cleaving ubiquitin and interferon-stimulated gene 15 protein from host proteins. As a result, PLpro is a promising target for inhibition by small-molecule therapeutics. Here we design a series of covalent inhibitors by introducing a peptidomimetic linker and reactive electrophile onto analogs of the noncovalent PLpro inhibitor GRL0617. The most potent compound inhibits PLpro with k inact /K I  = 9,600 M -1 s -1 , achieves sub-μM EC 50 values against three SARS-CoV-2 variants in mammalian cell lines, and does not inhibit a panel of human deubiquitinases (DUBs) at >30 μM concentrations of inhibitor. An X-ray co-crystal structure of the compound bound to PLpro validates our design strategy and establishes the molecular basis for covalent inhibition and selectivity against structurally similar human DUBs. These findings present an opportunity for further development of covalent PLpro inhibitors., (© 2023. UT-Battelle, LLC.)

HLA class I proteins, a critical component in adaptive immunity, bind and present intracellular Ags to CD8+ T cells. The extreme polymorphism of HLA genes and associated peptide binding specificities leads to challenges in various endeavors, including neoantigen vaccine development, disease association studies, and HLA typing. Supertype classification, defined by clustering functionally similar HLA alleles, has proven helpful in reducing the complexity of distinguishing alleles. However, determining supertypes via experiments is impractical, and current in silico classification methods exhibit limitations in stability and functional relevance. In this study, by incorporating three-dimensional structures we present a method for classifying HLA class I molecules with improved breadth, accuracy, stability, and flexibility. Critical for these advances is our finding that structural similarity highly correlates with peptide binding specificity. The new classification should be broadly useful in peptide-based vaccine development and HLA-disease association studies., (Copyright © 2022 by The American Association of Immunologists, Inc.)

Optimization of compound permeation into Gram-negative bacteria is one of the most challenging tasks in the development of antibacterial agents. Two permeability barriers─the passive diffusion barrier of the outer membrane (OM) and active drug efflux─act synergistically to protect cells from the antibacterial action of compounds. In Escherichia coli ( E. coli ) and relatives, these two barriers sieve compounds based on different physicochemical properties that are defined by their interactions with OM porins and efflux pumps, respectively. In this study, we critically tested the hypothesis that the best substrates and inhibitors of efflux pumps are compounds that can effectively permeate the OM and are available at relatively high concentrations in the periplasm. For this purpose, we filtered a large subset of the ZINC15 database of commercially available compounds for compounds containing a primary amine, a chemical feature known to facilitate the uptake through E. coli general porins. The assembled library was screened by ensemble docking to AcrA, the periplasmic component of the AcrAB-TolC efflux pump, followed by experimental testing of the top predicted binders for antibacterial activities, efflux recognition, and inhibition. We found that the filtered primary amine library is a rich source of compounds with efflux-inhibiting activities and identified efflux pump inhibitors with novel chemical scaffolds effective against E. coli AcrAB-TolC and efflux pumps of multidrug-resistant clinical isolates of Acinetobacter baumannii . However, primary amines are not required for the recognition of compounds by efflux pumps and their efflux-inhibitory activities.

Pyridoxal 5'-phosphate (PLP)-dependent enzymes have been extensively studied for their ability to fine-tune PLP cofactor electronics to promote a wide array of chemistries. Neutron crystallography offers a straightforward approach to studying the electronic states of PLP and the electrostatics of enzyme active sites, responsible for the reaction specificities, by enabling direct visualization of hydrogen atom positions. Here we report a room-temperature joint X-ray/neutron structure of aspartate aminotransferase (AAT) with pyridoxamine 5'-phosphate (PMP), the cofactor product of the first half reaction catalyzed by the enzyme. Between PMP N SB and catalytic Lys258 Nζ amino groups an equally shared deuterium is observed in an apparent low-barrier hydrogen bond (LBHB). Density functional theory calculations were performed to provide further evidence of this LBHB interaction. The structural arrangement and the juxtaposition of PMP and Lys258, facilitated by the LBHB, suggests active site preorganization for the incoming ketoacid substrate that initiates the second half-reaction., Competing Interests: There are no conflicts of interest to declare., (This journal is © The Royal Society of Chemistry.)

The Plasminogen-Apple-Nematode (PAN) domain, with a core of four to six cysteine residues, is found in > 28,000 proteins across 959 genera. Still, its role in protein function is not fully understood. The PAN domain was initially characterized in numerous proteins, including HGF. Dysregulation of HGF-mediated signaling results in multiple deadly cancers. The binding of HGF to its cell surface receptor, c-MET, triggers all biological impacts. Here, we show that mutating four core cysteine residues in the HGF PAN domain reduces c-MET interaction, subsequent c-MET autophosphorylation, and phosphorylation of its downstream targets, perinuclear localization, cellular internalization of HGF, and its receptor, c-MET, and c-MET ubiquitination. Furthermore, transcriptional activation of HGF/c-MET signaling-related genes involved in cancer progression, invasion, metastasis, and cell survival were impaired. Thus, targeting the PAN domain of HGF may represent a mechanism for selectively regulating the binding and activation of the c-MET pathway., (© 2022. The Author(s).)

Summary: Easy-to-use, open-source, general-purpose programs for modeling a protein structure from inter-atomic distances are needed for modeling from experimental data and refinement of predicted protein structures. OpenMDlr is an open-source Python package for modeling protein structures from pairwise distances between any atoms, and optionally, dihedral angles. We provide a user-friendly input format for harnessing modern biomolecular force fields in an easy-to-install package that can efficiently make use of multiple compute cores., Availability and Implementation: OpenMDlr is available at https://github.com/BSDExabio/OpenMDlr-amber. The package is written in Python (versions 3.x). All dependencies are open-source and can be installed with the Conda package management system., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Two membrane cell envelopes act as selective permeability barriers in Gram-negative bacteria, protecting cells against antibiotics and other small molecules. Significant efforts are being directed toward understanding how small molecules permeate these barriers. In this study, we developed an approach to analyze the permeation of compounds into Gram-negative bacteria and applied it to Pseudomonas aeruginosa, an important human pathogen notorious for resistance to multiple antibiotics. The approach uses mass spectrometric measurements of accumulation of a library of structurally diverse compounds in four isogenic strains of P. aeruginosa with varied permeability barriers. We further developed a machine learning algorithm that generates a deterministic classification model with minimal synonymity between the descriptors. This model predicted good permeators into P. aeruginosa with an accuracy of 89% and precision above 58%. The good permeators are broadly distributed in the property space and can be mapped to six distinct regions representing diverse chemical scaffolds. We posit that this approach can be used for more detailed mapping of the property space and for rational design of compounds with high Gram-negative permeability., (© 2022. The Author(s).)

Inhibition of the SARS-CoV-2 main protease (M pro ) is a major focus of drug discovery efforts against COVID-19. Here we report a hit expansion of non-covalent inhibitors of M pro . Starting from a recently discovered scaffold (The COVID Moonshot Consortium. Open Science Discovery of Oral Non-Covalent SARS-CoV-2 Main Protease Inhibitor Therapeutics. bioRxiv 2020.10.29.339317) represented by an isoquinoline series, we searched a database of over a billion compounds using a cheminformatics molecular fingerprinting approach. We identified and tested 48 compounds in enzyme inhibition assays, of which 21 exhibited inhibitory activity above 50% at 20 μM. Among these, four compounds with IC 50 values around 1 μM were found. Interestingly, despite the large search space, the isoquinolone motif was conserved in each of these four strongest binders. Room-temperature X-ray structures of co-crystallized protein-inhibitor complexes were determined up to 1.9 Å resolution for two of these compounds as well as one of the stronger inhibitors in the original isoquinoline series, revealing essential interactions with the binding site and water molecules. Molecular dynamics simulations and quantum chemical calculations further elucidate the binding interactions as well as electrostatic effects on ligand binding. The results help explain the strength of this new non-covalent scaffold for M pro inhibition and inform lead optimization efforts for this series, while demonstrating the effectiveness of a high-throughput computational approach to expanding a pharmacophore library., Competing Interests: The authors declare no competing financial interest., (© 2022 American Chemical Society.)

Accurate descriptions of protein-protein interactions are essential for understanding biological systems. Remarkably accurate atomic structures have been recently computed for individual proteins by AlphaFold2 (AF2). Here, we demonstrate that the same neural network models from AF2 developed for single protein sequences can be adapted to predict the structures of multimeric protein complexes without retraining. In contrast to common approaches, our method, AF2Complex, does not require paired multiple sequence alignments. It achieves higher accuracy than some complex protein-protein docking strategies and provides a significant improvement over AF-Multimer, a development of AlphaFold for multimeric proteins. Moreover, we introduce metrics for predicting direct protein-protein interactions between arbitrary protein pairs and validate AF2Complex on some challenging benchmark sets and the E. coli proteome. Lastly, using the cytochrome c biogenesis system I as an example, we present high-confidence models of three sought-after assemblies formed by eight members of this system., (© 2022. The Author(s).)

The multidrug efflux pumps of Gram-negative bacteria are a class of complexes that span the periplasm, coupling both the inner and outer membranes to expel toxic molecules. The best-characterized example of these tripartite pumps is the AcrAB-TolC complex of Escherichia coli. However, how the complex interacts with the peptidoglycan (PG) cell wall, which is anchored to the outer membrane (OM) by Braun's lipoprotein (Lpp), is still largely unknown. In this work, we present molecular dynamics simulations of a complete, atomistic model of the AcrAB-TolC complex with the inner membrane, OM, and PG layers all present. We find that the PG localizes to the junction of AcrA and TolC, in agreement with recent cryo-tomography data. Free-energy calculations reveal that the positioning of PG is determined by the length and conformation of multiple Lpp copies anchoring it to the OM. The distance between the PG and OM measured in cryo-electron microscopy images of wild-type E. coli also agrees with the simulation-derived spacing. Sequence analysis of AcrA suggests a conserved role for interactions with PG in the assembly and stabilization of efflux pumps, one that may extend to other trans-envelope complexes as well., (Copyright © 2021 Biophysical Society. All rights reserved.)

Antibiotic resistance poses an immediate and growing threat to human health. Multidrug efflux pumps are promising targets for overcoming antibiotic resistance with small-molecule therapeutics. Previously, we identified a diaminoquinoline acrylamide, NSC-33353, as a potent inhibitor of the AcrAB-TolC efflux pump in Escherichia coli . This inhibitor potentiates the antibacterial activities of novobiocin and erythromycin upon binding to the membrane fusion protein AcrA. It is also a substrate for efflux and lacks appreciable intrinsic antibacterial activity of its own in wild-type cells. Here, we have modified the substituents of the cinnamoyl group of NSC-33353, giving rise to analogs that retain the ability to inhibit efflux, lost the features of the efflux substrates, and gained antibacterial activity in wild-type cells. The replacement of the cinnamoyl group with naphthyl isosteres generated compounds that lack antibacterial activity but are both excellent efflux pump inhibitors and substrates. Surprisingly, these inhibitors potentiate the antibacterial activity of novobiocin but not erythromycin. Surface plasmon resonance experiments and molecular docking suggest that the replacement of the cinnamoyl group with naphthyl shifts the affinity of the compounds away from AcrA to the AcrB transporter, making them better efflux substrates and changing their mechanism of inhibition. These results provide new insights into the duality of efflux substrate/inhibitor features in chemical scaffolds that will facilitate the development of new efflux pump inhibitors.

Mercury (Hg) pollution is a global environmental problem. The abiotic formation of dimethylmercury (DMeHg) from monomethylmercury (MMeHg) may account for a large portion of DMeHg in oceans. Previous experimental work has shown that abiotic formation of DMeHg from MMeHg can be facilitated by reduced sulfur groups on sulfide mineral surfaces. In that work, a mechanism was proposed in which neighboring MMeHg moieties bound to sulfide sites on a mineral surface react through an S N 2-type mechanism to form DMeHg and incorporate the remaining Hg atoms into the mineral surface. Here, we perform density functional theory calculations to explore the mechanisms of DMeHg formation on the 110 surface of a CdS(s) (hawleyite) nanoparticle. We show that coordination of MMeHg substituents to adjacent reduced sulfur groups protruding from the surface indeed facilitates DMeHg formation and that the reaction proceeds through direct transmethylation from one MMeHg substituent to another. Coordination of Hg by multiple S atoms provides a transition-state stabilization and activates a C-Hg bond for methyl transfer. In addition, solvation effects play an important role in the surface reconstruction of the nanoparticle and in decreasing the energetic barrier for DMeHg formation relative to the corresponding reaction in vacuo.

Protein-protein interactions play a key role in mediating numerous biological functions, with more than half the proteins in living organisms existing as either homo- or hetero-oligomeric assemblies. Protein subunits that form oligomers minimize the free energy of the complex, but exhaustive computational search-based docking methods have not comprehensively addressed the challenge of distinguishing a natively bound complex from non-native forms. Current protein docking approaches address this problem by sampling multiple binding modes in proteins and scoring each mode, with the lowest-energy (or highest scoring) binding mode being regarded as a near-native complex. However, high-scoring modes often match poorly with the true bound form, suggesting a need for improvement of the scoring function. In this study, we propose a scoring function, KFC-E, that accounts for both conservation and coevolution of putative binding hotspot residues at protein-protein interfaces. We tested KFC-E on four benchmark sets of unbound examples and two benchmark sets of bound examples, with the results demonstrating a clear improvement over scores that examine conservation and coevolution across the entire interface.

SARS-CoV and SARS-CoV-2 bind to the human ACE2 receptor in practically identical conformations, although several residues of the receptor-binding domain (RBD) differ between them. Herein, we have used molecular dynamics (MD) simulations, machine learning (ML), and free-energy perturbation (FEP) calculations to elucidate the differences in binding by the two viruses. Although only subtle differences were observed from the initial MD simulations of the two RBD-ACE2 complexes, ML identified the individual residues with the most distinctive ACE2 interactions, many of which have been highlighted in previous experimental studies. FEP calculations quantified the corresponding differences in binding free energies to ACE2, and examination of MD trajectories provided structural explanations for these differences. Lastly, the energetics of emerging SARS-CoV-2 mutations were studied, showing that the affinity of the RBD for ACE2 is increased by N501Y and E484K mutations but is slightly decreased by K417N.

Pancreatic ductal adenocarcinoma (PDAC) is the third leading cause of cancer death in the United States. Pancreatic tumors are minimally infiltrated by T cells and are largely refractory to immunotherapy. Accordingly, the role of T-cell immunity in pancreatic cancer has been somewhat overlooked. Here, we hypothesized that immune resistance in pancreatic cancer was induced in response to antitumor T-cell immune responses and that understanding how pancreatic tumors respond to immune attack may facilitate the development of more effective therapeutic strategies. We now provide evidence that T-cell-dependent host immune responses induce a PDAC-derived myeloid mimicry phenomenon and stimulate immune resistance. Three KPC mouse models of pancreatic cancer were used: the mT3-2D (Kras +/LSL-G12D ; Trp53 +/LSL-R172H ; Pdx1-Cre) subcutaneous and orthotopic models, as well as the KP1 (p48- CRE / LSL - Kras /Trp53 flox/flox ) subcutaneous model. KPC cancer cells were grown in immunocompetent and immunodeficient C57BL/6 mice and analyzed to determine the impact of adaptive immunity on malignant epithelial cells, as well as on whole tumors. We found that induced T-cell antitumor immunity, via signal transducer and activator of transcription 1 (STAT1), stimulated malignant epithelial pancreatic cells to induce the expression of genes typically expressed by myeloid cells and altered intratumoral immunosuppressive myeloid cell profiles. Targeting the Janus Kinase (JAK)/STAT signaling pathway using the FDA-approved drug ruxolitinib overcame these tumor-protective responses and improved anti-PD-1 therapeutic efficacy. These findings provide future directions for treatments that specifically disable this mechanism of resistance in PDAC., (©2021 American Association for Cancer Research.)

Predicting the range of substrates accepted by an enzyme from its amino acid sequence is challenging. Although sequence- and structure-based annotation approaches are often accurate for predicting broad categories of substrate specificity, they generally cannot predict which specific molecules will be accepted as substrates for a given enzyme, particularly within a class of closely related molecules. Combining targeted experimental activity data with structural modeling, ligand docking, and physicochemical properties of proteins and ligands with various machine learning models provides complementary information that can lead to accurate predictions of substrate scope for related enzymes. Here we describe such an approach that can predict the substrate scope of bacterial nitrilases, which catalyze the hydrolysis of nitrile compounds to the corresponding carboxylic acids and ammonia. Each of the four machine learning models (logistic regression, random forest, gradient-boosted decision trees, and support vector machines) performed similarly (average ROC = 0.9, average accuracy = ~82%) for predicting substrate scope for this dataset, although random forest offers some advantages. This approach is intended to be highly modular with respect to physicochemical property calculations and software used for structural modeling and docking., (© 2020 Wiley Periodicals LLC.)

Antibiotics are miracle drugs that can cure infectious bacterial diseases. However, their utility is challenged by antibiotic-resistant bacteria emerging in clinics and straining modern medicine and our ways of life. Certain bacteria such as Gram-negative (Gram(-)) and Mycobacteriales species are intrinsically resistant to most clinical antibiotics and can further gain multidrug resistance through mutations and plasmid acquisition. These species stand out by the presence of an additional external lipidic membrane, the outer membrane (OM), that is composed of unique glycolipids. Although formidable, the OM is a passive permeability barrier that can reduce penetration of antibiotics but cannot affect intracellular steady-state concentrations of drugs. The two-membrane envelopes are further reinforced by active efflux transporters that expel antibiotics from cells against their concentration gradients. The major mechanism of antibiotic resistance in Gram(-) pathogens is the active efflux of drugs, which acts synergistically with the low permeability barrier of the OM and other mutational and plasmid-borne mechanisms of antibiotic resistance.The synergy between active efflux and slow uptake offers Gram(-) bacteria an impressive degree of protection from potentially harmful chemicals, but it is also their Achilles heel. Kinetic studies have revealed that even small changes in the efficiency of either of the two factors can have dramatic effects on drug penetration into the cell. In line with these expectations, two major approaches to overcome this antibiotic resistance mechanism are currently being explored: (1) facilitation of antibiotic penetration across the outer membranes and (2) avoidance and inhibition of clinically relevant multidrug efflux pumps. Herein we summarize the progress in the latter approach with a focus on efflux pumps from the resistance-nodulation-division (RND) superfamily. The ability to export various substrates across the OM at the expense of the proton-motive force acting on the inner membrane and the engagement of accessory proteins for their functions are the major mechanistic advantages of these pumps. Both the RND transporters and their accessory proteins are being targeted in the discovery of efflux pump inhibitors, which in combination with antibiotics can potentiate antibacterial activities. We discuss intriguing relationships between substrates and inhibitors of efflux pumps, as these two types of ligands face similar barriers and binding sites in the transporters and accessory proteins and both types of activities often occur with the same chemical scaffold. Several distinct chemical classes of efflux inhibitors have been discovered that are as structurally diverse as the substrates of efflux pumps. Recent mechanistic insights, both empirical and computational, have led to the identification of features that distinguish OM permeators and efflux pump avoiders as well as efflux inhibitors from substrates. These findings suggest a path forward for optimizing the OM permeation and efflux-inhibitory activities in antibiotics and other chemically diverse compounds.

Gram-negative bacteria have a cell envelope that comprises an outer membrane (OM), a peptidoglycan (PG) layer and an inner membrane (IM) 1 . The OM and PG are load-bearing, selectively permeable structures that are stabilized by cooperative interactions between IM and OM proteins 2,3 . In Escherichia coli, Braun's lipoprotein (Lpp) forms the only covalent tether between the OM and PG and is crucial for cell envelope stability 4 ; however, most other Gram-negative bacteria lack Lpp so it has been assumed that alternative mechanisms of OM stabilization are present 5 . We used a glycoproteomic analysis of PG to show that β-barrel OM proteins are covalently attached to PG in several Gram-negative species, including Coxiella burnetii, Agrobacterium tumefaciens and Legionella pneumophila. In C. burnetii, we found that four different types of covalent attachments occur between OM proteins and PG, with tethering of the β-barrel OM protein BbpA becoming most abundant in the stationary phase and tethering of the lipoprotein LimB similar throughout the cell cycle. Using a genetic approach, we demonstrate that the cell cycle-dependent tethering of BbpA is partly dependent on a developmentally regulated L,D-transpeptidase (Ldt). We use our findings to propose a model of Gram-negative cell envelope stabilization that includes cell cycle control and an expanded role for Ldts in covalently attaching surface proteins to PG.

We present a supercomputer-driven pipeline for in silico drug discovery using enhanced sampling molecular dynamics (MD) and ensemble docking. Ensemble docking makes use of MD results by docking compound databases into representative protein binding-site conformations, thus taking into account the dynamic properties of the binding sites. We also describe preliminary results obtained for 24 systems involving eight proteins of the proteome of SARS-CoV-2. The MD involves temperature replica exchange enhanced sampling, making use of massively parallel supercomputing to quickly sample the configurational space of protein drug targets. Using the Summit supercomputer at the Oak Ridge National Laboratory, more than 1 ms of enhanced sampling MD can be generated per day. We have ensemble docked repurposing databases to 10 configurations of each of the 24 SARS-CoV-2 systems using AutoDock Vina. Comparison to experiment demonstrates remarkably high hit rates for the top scoring tranches of compounds identified by our ensemble approach. We also demonstrate that, using Autodock-GPU on Summit, it is possible to perform exhaustive docking of one billion compounds in under 24 h. Finally, we discuss preliminary results and planned improvements to the pipeline, including the use of quantum mechanical (QM), machine learning, and artificial intelligence (AI) methods to cluster MD trajectories and rescore docking poses.

The main protease (M pro ) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an attractive target for antiviral therapeutics. Recently, many high-resolution apo and inhibitor-bound structures of M pro , a cysteine protease, have been determined, facilitating structure-based drug design. M pro plays a central role in the viral life cycle by catalyzing the cleavage of SARS-CoV-2 polyproteins. In addition to the catalytic dyad His41-Cys145, M pro contains multiple histidines including His163, His164, and His172. The protonation states of these histidines and the catalytic nucleophile Cys145 have been debated in previous studies of SARS-CoV M pro , but have yet to be investigated for SARS-CoV-2. In this work we have used molecular dynamics simulations to determine the structural stability of SARS-CoV-2 M pro as a function of the protonation assignments for these residues. We simulated both the apo and inhibitor-bound enzyme and found that the conformational stability of the binding site, bound inhibitors, and the hydrogen bond networks of M pro are highly sensitive to these assignments. Additionally, the two inhibitors studied, the peptidomimetic N3 and an α-ketoamide, display distinct His41/His164 protonation-state-dependent stabilities. While the apo and the N3-bound systems favored N δ (HD) and N ϵ (HE) protonation of His41 and His164, respectively, the α-ketoamide was not stably bound in this state. Our results illustrate the importance of using appropriate histidine protonation states to accurately model the structure and dynamics of SARS-CoV-2 M pro in both the apo and inhibitor-bound states, a necessary prerequisite for drug-design efforts., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

Dissolved organic matter (DOM) plays a significant role in the transport and transformation of pollutants in the aquatic environment. However, the experimental characterization of DOM has been limited mainly to bulk properties, and the molecular-level interactions among various components of DOM remain to be fully characterized. Here, we use molecular dynamics (MD) simulations to probe the structural properties of model DOM systems at atomic detail. The 200 ns simulations, validated by available experimental data, reveal processes and mechanisms by which chemical species (cations, peptides, lipids, lignin, carbohydrates, and some low-molecular-weight aliphatic and aromatic compounds) aggregate to form complex DOM. The DOM aggregates are dynamic, consisting of a hydrophobic core and amphiphilic exterior. The lipid tails and other hydrophobic fragments form the core, with hydrophilic and amphiphilic groups exposed to water, making DOM accessible to both polar and nonpolar species. Thus, the lipid component acts as a nucleator, whereas cations (especially Ca 2+ ) connect the molecular fragments on the surface by coordinating with the O-containing functional groups of DOM. The structural details revealed here provide new insights including surface accessible atoms, overall assemblage, and interactions among the molecules of DOM for understanding the kinetics and mechanisms through which DOM interacts with metal and other contaminants.

The reaction mechanism of biomass decomposition by xylanases remains the subject of debate. To clarify the mechanism we investigated the glycosylation step of GH11 xylanase, an enzyme that catalyzes the hydrolysis of lignocellulosic hemicellulose (xylan). Making use of a recent neutron crystal structure, which revealed the protonation states of relevant residues, we used ab initio quantum mechanics/molecular mechanics (QM/MM) calculations to determine the detailed reaction mechanism of the glycosylation step. In particular, our focus is on the controversial question of whether or not an oxocarbenium ion intermediate is formed on the reaction pathway. The calculations support the validity of a basic retaining mechanism within a double-displacement scheme. The estimated free energy barrier of this reaction is ∼18 kcal/mol with QM/MM-CCSD(T)/6-31(+)G**//MP2/6-31+G**/AMBER calculations, and the rate-determining step of the glycosylation is scission of the glycosidic bond after proton transfer from the acidic Glu177. The estimated lifetime of the oxocarbenium ion intermediate (on the order of tens of ps) and the secondary kinetic isotope effect suggest that there is no accumulation of this intermediate on the reaction path, although the intermediate can be transiently formed. In the enzyme-substrate (ES) complex, the carbohydrate structure of the xylose residue at the -1 subsite has a rather distorted (skewed) geometry, and this xylose unit at the active site has an apparent half-chair conformation when the oxocarbenium ion intermediate is formed. The major catalytic role of the protein environment is to orient residues that take part in the initial proton transfer. Because of a fine alignment of catalytic residues, the enzyme can accelerate the glycosylation reaction without paying a reorganization energy penalty.

The reliable prediction of the affinity of candidate peptides for the MHC is important for predicting their potential antigenicity and thus influences medical applications, such as decisions on their inclusion in T cell-based vaccines. In this study, we present a rapid, predictive computational approach that combines a popular, sequence-based artificial neural network method, NetMHCpan 4.0, with three-dimensional structural modeling. We find that the ensembles of bound peptide conformations generated by the programs MODELLER and Rosetta FlexPepDock are less variable in geometry for strong binders than for low-affinity peptides. In tests on 1271 peptide sequences for which the experimental dissociation constants of binding to the well-characterized murine MHC allele H-2D b are known, by applying thresholds for geometric fluctuations the structure-based approach in a standalone manner drastically improves the statistical specificity, reducing the number of false positives. Furthermore, filtering candidates generated with NetMHCpan 4.0 with the structure-based predictor led to an increase in the positive predictive value (PPV) of the peptides correctly predicted to bind very strongly (i.e., K d < 100 nM) from 40 to 52% ( p = 0.027). The combined method also significantly improved the PPV when tested on five human alleles, including some with limited data for training. Overall, an average increase of 10% in the PPV was found over the standalone sequence-based method. The combined method should be useful in the rapid design of effective T cell-based vaccines., (Copyright © 2020 by The American Association of Immunologists, Inc.)

Bacteria and archaea possessing the hgcAB gene pair methylate inorganic mercury (Hg) to form highly toxic methylmercury. HgcA consists of a corrinoid binding domain and a transmembrane domain, and HgcB is a dicluster ferredoxin. However, their detailed structure and function have not been thoroughly characterized. We modeled the HgcAB complex by combining metagenome sequence data mining, coevolution analysis, and Rosetta structure calculations. In addition, we overexpressed HgcA and HgcB in Escherichia coli, confirmed spectroscopically that they bind cobalamin and [4Fe-4S] clusters, respectively, and incorporated these cofactors into the structural model. Surprisingly, the two domains of HgcA do not interact with each other, but HgcB forms extensive contacts with both domains. The model suggests that conserved cysteines in HgcB are involved in shuttling Hg II , methylmercury, or both. These findings refine our understanding of the mechanism of Hg methylation and expand the known repertoire of corrinoid methyltransferases in nature.

Multidrug efflux is a major contributor to antibiotic resistance in Gram-negative bacterial pathogens. Inhibition of multidrug efflux pumps is a promising approach for reviving the efficacy of existing antibiotics. Previously, inhibitors targeting both the efflux transporter AcrB and the membrane fusion protein AcrA in the Escherichia coli AcrAB-TolC efflux pump were identified. Here we use existing physicochemical property guidelines to generate a filtered library of compounds for computational docking. We then experimentally test the top candidate coumpounds using in vitro binding assays and in vivo potentiation assays in bacterial strains with controllable permeability barriers. We thus identify a new class of inhibitors of E. coli AcrAB-TolC. Six molecules with a shared scaffold were found to potentiate the antimicrobial activity of erythromycin and novobiocin in hyperporinated E. coli cells. Importantly, these six molecules were also active in wild-type strains of both Acinetobacter baumannii and Klebsiella pneumoniae, potentiating the activity of erythromycin and novobiocin up to 8-fold., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

The mer operon in bacteria encodes a set of proteins and enzymes that impart resistance to environmental mercury toxicity by importing Hg 2+ and reducing it to volatile Hg(0). Because the reduction occurs in the cytoplasm, mercuric ions must first be transported across the cytoplasmic membrane by one of a few known transporters. MerF is the smallest of these, containing only two transmembrane helices and two pairs of vicinal cysteines that coordinate mercuric ions. In this work, we use molecular dynamics simulations to characterize the dynamics of MerF in its apo and Hg 2+ -bound states. We find that the apo state positions one of the cysteine pairs closer to the periplasmic side of the membrane, while in the bound state the same pair approaches the cytoplasmic side. This finding is consistent with the functional requirement of accepting Hg 2+ from the periplasmic space, sequestering it on acceptance, and transferring it to the cytoplasm. Conformational changes in the TM helices facilitate the functional interaction of the two cysteine pairs. Free-energy calculations provide a barrier of 16 kcal/mol for the association of the periplasmic Hg 2+ -bound protein MerP with MerF and 7 kcal/mol for the subsequent association of MerF's two cysteine pairs. Despite the significant conformational changes required to move the binding site across the membrane, coarse-grained simulations of multiple copies of MerF support the expectation that it functions as a monomer. Our results demonstrate how conformational changes and binding thermodynamics could lead to such a small membrane protein acting as an ion transporter. Published 2019. This article is a U.S. Government work and is in the public domain in the USA., (Published 2019. This article is a U.S. Government work and is in the public domain in the USA.)

To assess the chemical reactivity, toxicity, and mobility of pollutants in the environment, knowledge of their species distributions is critical. Because their direct measurement is often infeasible, speciation modeling is widely adopted. Mercury (Hg) is a representative pollutant for which study of its speciation benefits from modeling. However, Hg speciation modeling is often hindered by a lack of reliable thermodynamic constants. Although computational chemistry (e.g., density functional theory [DFT]) can generate these constants, methods for directly coupling DFT and speciation modeling are not available. Here, we combine computational chemistry and continuum-scale modeling with curated online databases to ameliorate the problem of unreliable inputs to Hg speciation modeling. Our AQUA-MER databases and web server (https://aquamer.ornl.gov) provides direct speciation results by combining web-based interfaces to a speciation calculator, databases of thermodynamic constants, and a computational chemistry toolkit to estimate missing constants. Although Hg is presented as a concrete use case, AQUA-MER can also be readily applied to other elements. © 2019 Wiley Periodicals, Inc., (© 2019 Wiley Periodicals, Inc.)

A microbe's ecological niche and biotechnological utility are determined by its specific set of co-evolved metabolic pathways. The acquisition of new pathways, through horizontal gene transfer or genetic engineering, can have unpredictable consequences. Here we show that two different pathways for coumarate catabolism failed to function when initially transferred into Escherichia coli. Using laboratory evolution, we elucidated the factors limiting activity of the newly acquired pathways and the modifications required to overcome these limitations. Both pathways required host mutations to enable effective growth with coumarate, but the necessary mutations differed. In one case, a pathway intermediate inhibited purine nucleotide biosynthesis, and this inhibition was relieved by single amino acid replacements in IMP dehydrogenase. A strain that natively contains this coumarate catabolism pathway, Acinetobacter baumannii, is resistant to inhibition by the relevant intermediate, suggesting that natural pathway transfers have faced and overcome similar challenges. Molecular dynamics simulation of the wild type and a representative single-residue mutant provide insight into the structural and dynamic changes that relieve inhibition. These results demonstrate how deleterious interactions can limit pathway transfer, that these interactions can be traced to specific molecular interactions between host and pathway, and how evolution or engineering can alleviate these limitations., (© 2019 John Wiley & Sons Ltd.)

Multidrug efflux pumps of pathogenic, Gram-negative bacteria comprise an innate resistance mechanism and are key contributors to the emerging global pandemic of antibiotic resistance. Several increasingly detailed cryo-electron microscopy maps have been resolved of an entire efflux pump complex, AcrAB-TolC, resulting in atomistic structural models. Using a recent model, we have carried out nearly 40 μs of molecular dynamics simulations to study one of the key components of the protein complex AcrA, the membrane fusion protein that connects the inner-membrane-bound AcrB to the outer-membrane-bound TolC. We determined a three-dimensional potential of mean force (PMF) for AcrA, which displays two main conformational basins representing assembly competent and incompetent states. Corresponding experiments show that stabilizing mutations at an interdomain interface shift the dynamic equilibrium between these states to the incompetent one, disrupting pump assembly and function and resensitizing bacteria to existing antibiotics. The modulation of AcrA dynamics through pharmacological intervention therefore presents a promising route for the development of new antibiotics.

Most microorganisms from all taxonomic levels are uncultured. Single-cell genomes and metagenomes continue to increase the known diversity of Bacteria and Archaea; however, while 'omics can be used to infer physiological or ecological roles for species in a community, most of these hypothetical roles remain unvalidated. Here, we report an approach to capture specific microorganisms from complex communities into pure cultures using genome-informed antibody engineering. We apply our reverse genomics approach to isolate and sequence single cells and to cultivate three different species-level lineages of human oral Saccharibacteria (TM7). Using our pure cultures, we show that all three Saccharibacteria species are epibionts of diverse Actinobacteria. We also isolate and cultivate human oral SR1 bacteria, which are members of a lineage of previously uncultured bacteria. Reverse-genomics-enabled cultivation of microorganisms can be applied to any species from any environment and has the potential to unlock the isolation, cultivation and characterization of species from as-yet-uncultured branches of the microbial tree of life.

Sodium ions have long been known to reduce the binding of agonists in many class-A GPCRs while having little effect on antagonist binding. Here, using long-time scale classical all-atom molecular dynamics simulations, we explore, in atomic detail, the motion of sodium ions within the ligand-binding pocket of the A 2A adenosine receptor (A2A-AR) both in the presence and absence of ligands and in the active and inactive state. We identify novel secondary ion binding sites within the pocket and find that the types of ion motions within the pocket are highly dependent on the presence and type of ligand within the pocket. Our results provide a first step toward developing a molecular understanding of the impact of sodium ions on class-A GPCRs.

Methylmercury (MeHg) is a potent bioaccumulative neurotoxin that is produced by certain anaerobic bacteria and archaea. Mercury (Hg) methylation has been linked to the gene pair hgcAB , which encodes a membrane-associated corrinoid protein and a ferredoxin. Although microbial Hg methylation has been characterized in vivo , the cellular biochemistry and the specific roles of the gene products HgcA and HgcB in Hg methylation are not well understood. Here, we report the kinetics of Hg methylation in cell lysates of Desulfovibrio desulfuricans ND132 at nanomolar Hg concentrations. The enzymatic Hg methylation mediated by HgcAB is highly oxygen sensitive, irreversible, and follows Michaelis-Menten kinetics, with an apparent K m of 3.2 nM and V max of 19.7 fmol · min -1 · mg -1 total protein for the substrate Hg(II). Although the abundance of HgcAB in the cell lysates is extremely low, Hg(II) was quantitatively converted to MeHg at subnanomolar substrate concentrations. Interestingly, increasing thiol/Hg(II) ratios did not impact Hg methylation rates, which suggests that HgcAB-mediated Hg methylation effectively competes with cellular thiols for Hg(II), consistent with the low apparent K m Supplementation of 5-methyltetrahydrofolate or pyruvate did not enhance MeHg production, while both ATP and a nonhydrolyzable ATP analog decreased Hg methylation rates in cell lysates under the experimental conditions. These studies provide insights into the biomolecular processes associated with Hg methylation in anaerobic bacteria. IMPORTANCE The concentration of Hg in the biosphere has increased dramatically over the last century as a result of industrial activities. The microbial conversion of inorganic Hg to MeHg is a global public health concern due to bioaccumulation and biomagnification of MeHg in food webs. Exposure to neurotoxic MeHg through the consumption of fish represents a significant risk to human health and can result in neuropathies and developmental disorders. Anaerobic microbial communities in sediments and periphyton biofilms have been identified as sources of MeHg in aquatic systems, but the associated biomolecular mechanisms are not fully understood. In the present study, we investigate the biochemical mechanisms and kinetics of MeHg formation by HgcAB in sulfate-reducing bacteria. These findings advance our understanding of microbial MeHg production and may help inform strategies to limit the formation of MeHg in the environment., (Copyright © 2019 American Society for Microbiology.)

Recent studies have identified HgcAB proteins as being responsible for mercury [Hg(II)] methylation by certain anaerobic microorganisms. However, it remains controversial whether microbes take up Hg(II) passively or actively. Here, we examine the dynamics of concurrent Hg(II) adsorption, uptake, and methylation by both viable and inactivated cells (heat-killed or starved) or spheroplasts of the sulfate-reducing bacterium Desulfovibrio desulfuricans ND132 in laboratory incubations. We show that, without addition of thiols, >60% of the added Hg(II) (25 nM) was taken up passively in 48 h by live and inactivated cells and also by cells treated with the proton gradient uncoupler, carbonylcyanide-3-chlorophenylhydrazone (CCCP). Inactivation abolished Hg(II) methylation, but the cells continued taking up Hg(II), likely through competitive binding or ligand exchange of Hg(II) by intracellular proteins or thiol-containing cellular components. Similarly, treatment with CCCP impaired the ability of spheroplasts to methylate Hg(II) but did not stop Hg(II) uptake. Spheroplasts showed a greater capacity to adsorb Hg(II) than whole cells, and the level of cytoplasmic membrane-bound Hg(II) correlated well with MeHg production, as Hg(II) methylation is associated with cytoplasmic HgcAB. Our results indicate that active metabolism is not required for cellular Hg(II) uptake, thereby providing an improved understanding of Hg(II) bioavailability for methylation.

Balancing the potential for durable remissions with autoimmune-like toxicities is a key clinical challenge in the use of immune checkpoint inhibitors (ICI). Certain toxicities are associated with an increased response rate; however, the molecular underpinnings of this association are poorly understood. Here, we report a patient with wide spread uveal melanoma who had an exceptional response to treatment with ipilimumab and nivolumab, but suffered severe immune-related sequelae, including central serous retinopathy with retinal detachment, tinnitus, and vitiligo resembling Vogt-Koyanagi-Harada disease, and refractory enteritis. TCR-sequencing of the primary tumor, a hepatic metastasis, duodenal biopsy and peripheral blood mononuclear cells, identified the identical T cell clone in all four tissues. This case provides preliminary evidence for cross-reactivity as a mechanism for the association between effect and toxicity of ICIs.

Mercury (Hg) is a global environmental contaminant. Major anthropogenic sources of Hg emission include gold mining and the burning of fossil fuels. Once deposited in aquatic environments, Hg can undergo redox reactions, form complexes with ligands, and adsorb onto particles. It can also be methylated by microorganisms. Mercury, especially its methylated form methylmercury, can be taken up by organisms, where it bioaccumulates and biomagnifies in the food chain, leading to detrimental effects on ecosystem and human health. In support of the recently enforced Minamata Convention on Mercury, a legally binding international convention aimed at reducing the anthropogenic emission of-and human exposure to-Hg, its global biogeochemical cycle must be understood. Thus, a detailed understanding of the molecular-level interactions of Hg is crucial. The ongoing rapid development of hardware and methods has brought computational chemistry to a point that it can usefully inform environmental science. This is particularly true for Hg, which is difficult to handle experimentally due to its ultratrace concentrations in the environment and its toxicity. The current account provides a synopsis of the application of computational chemistry to filling several major knowledge gaps in environmental Hg chemistry that have not been adequately addressed experimentally. Environmental Hg chemistry requires defining the factors that determine the relative affinities of different ligands for Hg species, as they are critical for understanding its speciation, transformation and bioaccumulation in the environment. Formation constants and the nature of bonding have been determined computationally for environmentally relevant Hg(II) complexes such as chlorides, hydroxides, sulfides and selenides, in various physical phases. Quantum chemistry has been used to determine the driving forces behind the speciation of Hg with hydrochalcogenide and halide ligands. Of particular importance is the detailed characterization of solvation effects. Indeed, the aqueous phase reverses trends in affinities found computationally in the gas phase. Computation has also been used to investigate complexes of methylmercury with (seleno)amino acids, providing a molecular-level understanding of the toxicological antagonism between Hg and selenium (Se). Furthermore, evidence is emerging that ice surfaces play an important role in Hg transport and transformation in polar and alpine regions. Therefore, the diffusion of Hg and its ions through an idealized ice surface has been characterized. Microorganisms are major players in environmental mercury cycling. Some methylate inorganic Hg species, whereas others demethylate methylmercury. Quantum chemistry has been used to investigate catalytic mechanisms of enzymatic Hg methylation and demethylation. The complex interplay between the myriad chemical reactions and transport properties both in and outside microbial cells determines net biogeochemical cycling. Prospects for scaling up molecular work to obtain a mechanistic understanding of Hg cycling with comprehensive multiscale biogeochemical modeling are also discussed.

The overexpression of multidrug efflux pumps is an important mechanism of clinical resistance in Gram-negative bacteria. Recently, four small molecules were discovered that inhibit efflux in Escherichia coli and interact with the AcrAB-TolC efflux pump component AcrA. However, the binding site(s) for these molecules was not determined. Here, we combine ensemble docking and molecular dynamics simulations with tryptophan fluorescence spectroscopy, site-directed mutagenesis, and antibiotic susceptibility assays to probe binding sites and effects of binding of these molecules. We conclude that clorobiocin and SLU-258 likely bind at a site located between the lipoyl and β-barrel domains of AcrA., (Copyright © 2019 Biophysical Society. Published by Elsevier Inc. All rights reserved.)

The cell envelope in Gram-negative bacteria comprises two distinct membranes with a cell wall between them. There has been a growing interest in understanding the mechanical adaptation of this cell envelope to the osmotic pressure (or turgor pressure), which is generated by the difference in the concentration of solutes between the cytoplasm and the external environment. However, it remains unexplored how the cell wall, the inner membrane (IM), and the outer membrane (OM) effectively protect the cell from this pressure by bearing the resulting surface tension, thus preventing the formation of inner membrane bulges, abnormal cell morphology, spheroplasts and cell lysis. In this study, we have used molecular dynamics (MD) simulations combined with experiments to resolve how and to what extent models of the IM, OM, and cell wall respond to changes in surface tension. We calculated the area compressibility modulus of all three components in simulations from tension-area isotherms. Experiments on monolayers mimicking individual leaflets of the IM and OM were also used to characterize their compressibility. While the membranes become softer as they expand, the cell wall exhibits significant strain stiffening at moderate to high tensions. We integrate these results into a model of the cell envelope in which the OM and cell wall share the tension at low turgor pressure (0.3 atm) but the tension in the cell wall dominates at high values (>1 atm)., (Copyright © 2018 Elsevier B.V. All rights reserved.)