Investigations into Simplified Analogues of the Herbicidal Natural Product (+)-Cornexistin.

We report the design, synthesis and biological evaluation of simplified analogues of the herbicidal natural product (+)-cornexistin. Guided by an X-Ray co-crystal structure of cornexistin bound to transketolase from Zea mays, we attempted to identify the key interactions that are necessary for cornexistin to maintain its herbicidal profile. This resulted in the preparation of three novel analogues investigating the importance of substituents that are located on the nine-membered ring of cornexistin. One analogue maintained a good level of biological activity and could provide researchers insights in how to further optimize the structure of cornexistin for commercialization in the future.

Identification of a 1-deoxy-D-xylulose-5-phosphate synthase (DXS) mutant with improved crystallographic properties.

In this report, we describe a truncated Deinococcus radiodurans 1-deoxy-D-xylulose-5-phosphate synthase (DXS) protein that retains enzymatic activity, while slowing protein degradation and showing improved crystallization properties. With modern drug-design approaches relying heavily on the elucidation of atomic interactions of potential new drugs with their targets, the need for co-crystal structures with the compounds of interest is high. DXS itself is a promising drug target, as it catalyzes the first reaction in the 2-C-methyl-D-erythritol 4-phosphate (MEP)-pathway for the biosynthesis of the universal precursors of terpenes, which are essential secondary metabolites. In contrast to many bacteria and pathogens, which employ the MEP pathway, mammals use the distinct mevalonate-pathway for the biosynthesis of these precursors, which makes all enzymes of the MEP-pathway potential new targets for the development of anti-infectives. However, crystallization of DXS has proven to be challenging: while the first X-ray structures from Escherichia coli and D. radiodurans were solved in 2004, since then only two additions have been made in 2019 that were obtained under anoxic conditions. The presented site of truncation can potentially also be transferred to other homologues, opening up the possibility for the determination of crystal structures from pathogenic species, which until now could not be crystallized. This manuscript also provides a further example that truncation of a variable region of a protein can lead to improved structural data.

Tetrahydroquinolinyl phosphinamidates and phosphonamidates enhancing tolerance towards drought stress in crops via interaction with ABA receptor proteins.

New phosphorous-containing lead structures against drought stress in crops interacting with RCAR/(PYR/PYL) receptor proteins were identified starting from in-depth SAR studies of related sulfonamide lead structures and protein docking studies. A converging 6-step synthesis via phosphinic chlorides and phosphono chloridates as key intermediates afforded envisaged tetrahydroquinolinyl phosphinamidates and phosphonamidates. Whilst tetrahydroquinolinyl phosphonamidates 13a,b exhibited low to moderate target affinities, the corresponding tetrahydroquinolinyl phosphinamidates 12a,b revealed confirmed strong affinities for RCAR/ (PYR/PYL) receptor proteins in Arabidopsis thaliana on the same level as essential plant hormone abscisic acid (ABA) combined with promising efficacy against drought stress in vivo (broad-acre crops wheat and canola).

Identifying new lead structures to enhance tolerance towards drought stress via high-throughput screening giving crops a quantum of solace.

Novel synthetic lead structures interacting with RCAR/(PYR/PYL) receptor proteins were identified based on the results of a high-throughput screening campaign of a large compound library followed by focused SAR studies of the three most promising hit clusters. Whilst indolinylmethyl sulfonamides 8y,z and phenylsulfonyl ethylenediamines 9y,z showed strong affinities for RCAR/ (PYR/PYL) receptor proteins in wheat, thiotriazolyl acetamides 7f,s exhibited promising efficacy against drought stress in vivo (wheat, corn and canola) combined with confirmed target interaction in wheat and arabidopsis thaliana. Remarkably, binding affinities of several representatives of 8 and 9 were on the same level or even better than the essential plant hormone abscisic acid (ABA).

Placement of Water Molecules in Protein Structures: From Large-Scale Evaluations to Single-Case Examples.

Water molecules are of great importance for the correct representation of ligand binding interactions. Throughout the last years, water molecules and their integration into drug design strategies have received increasing attention. Nowadays a variety of tools are available to place and score water molecules. However, the most frequently applied software solutions require substantial computational resources. In addition, none of the existing methods has been rigorously evaluated on the basis of a large number of diverse protein complexes. Therefore, we present a novel method for placing water molecules, called WarPP, based on interaction geometries previously derived from protein crystal structures. Using a large, previously compiled, high-quality validation set of almost 1500 protein-ligand complexes containing almost 20 000 crystallographically observed water molecules in their active sites, we validated our placement strategy. We correctly placed 80% of the water molecules within 1.0 Šof a crystallographically observed one.

Prediction of protein mutation effects based on dehydration and hydrogen bonding - A large-scale study.

Reliable computational prediction of protein side chain conformations and the energetic impact of amino acid mutations are the key aspects for the optimization of biotechnologically relevant enzymatic reactions using structure-based design. By improving the protein stability, higher yields can be achieved. In addition, tuning the substrate selectivity of an enzymatic reaction by directed mutagenesis can lead to higher turnover rates. This work presents a novel approach to predict the conformation of a side chain mutation along with the energetic effect on the protein structure. The HYDE scoring concept applied here describes the molecular interactions primarily by evaluating the effect of dehydration and hydrogen bonding on molecular structures in aqueous solution. Here, we evaluate its capability of side-chain conformation prediction in classic remutation experiments. Furthermore, we present a new data set for evaluating "cross-mutations," a new experiment that resembles real-world application scenarios more closely. This data set consists of protein pairs with up to five point mutations. Thus, structural changes are attributed to point mutations only. In the cross-mutation experiment, the original protein structure is mutated with the aim to predict the structure of the side chain as in the paired mutated structure. The comparison of side chain conformation prediction ("remutation") showed that the performance of HYDEprotein is qualitatively comparable to state-of-the art methods. The ability of HYDEprotein to predict the energetic effect of a mutation is evaluated in the third experiment. Herein, the effect on protein stability is predicted correctly in 70% of the evaluated cases. Proteins 2017; 85:1550-1566. © 2017 Wiley Periodicals, Inc.

Multi-Site Clinical Assessment of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (MCAM): Design and Implementation of a Prospective/Retrospective Rolling Cohort Study.

In the Multi-Site Clinical Assessment of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (MCAM), we relied on expert clinician diagnoses to enroll patients from 7 specialty clinics in the United States in order to perform a systematic collection of data on measures of myalgic encephalomyelitis (ME)/chronic fatigue syndrome (CFS). Healthy persons and those with other illnesses that share some features with ME/CFS were enrolled in comparison groups. The major objectives were to: 1) use standardized questionnaires to measure illness domains of ME/CFS and to evaluate patient heterogeneity overall and between clinics; 2) describe the course of illness, identify the measures that best correlate with meaningful clinical differences, and assess the performances of questionnaires as patient/person-reported outcome measures; 3) describe prescribed medications, orders for laboratory and other tests, and management tools used by expert clinicians to care for persons with ME/CFS; 4) collect biospecimens for future hypothesis testing and for evaluation of morning cortisol profiles; and 5) identify measures that best distinguish persons with ME/CFS from those in the comparison groups and detect subgroups of persons with ME/CFS who may have different underlying causes. Enrollment began in 2012 and is planned to continue in multiple stages through 2017. We present the MCAM methods in detail, along with an initial description of the 471 patients with ME/CFS who were enrolled in stage 1.

Estimating Electron Density Support for Individual Atoms and Molecular Fragments in X-ray Structures.

Macromolecular structures resolved by X-ray crystallography are essential for life science research. While some methods exist to automatically quantify the quality of the electron density fit, none of them is without flaws. Especially the question of how well individual parts like atoms, small fragments, or molecules are supported by electron density is difficult to quantify. While taking experimental uncertainties correctly into account, they do not offer an answer on how reliable an individual atom position is. A rapid quantification of this atomic position reliability would be highly valuable in structure-based molecular design. To overcome this limitation, we introduce the electron density score EDIA for individual atoms and molecular fragments. EDIA assesses rapidly, automatically, and intuitively the fit of individual as well as multiple atoms (EDIAm) into electron density accompanied by an integrated error analysis. The computation is based on the standard 2fo - fc electron density map in combination with the model of the molecular structure. For evaluating partial structures, EDIAm shows significant advantages compared to the real-space R correlation coefficient (RSCC) and the real-space difference density Z score (RSZD) from the molecular modeler's point of view. Thus, EDIA abolishes the time-consuming step of visually inspecting the electron density during structure selection and curation. It supports daily modeling tasks of medicinal and computational chemists and enables a fully automated assembly of large-scale, high-quality structure data sets. Furthermore, EDIA scores can be applied for model validation and method development in computer-aided molecular design. In contrast to measuring the deviation from the structure model by root-mean-squared deviation, EDIA scores allow comparison to the underlying experimental data taking its uncertainty into account.

Salivary Mitochondrial DNA Copy Number Is Associated With Exercise Ventilatory Efficiency.

Chen, Y, Hill, HZ, Lange, G, and Falvo, MJ. Salivary mitochondrial DNA copy number is associated with exercise ventilatory efficiency. J Strength Cond Res 31(7): 2000-2004, 2017-Mitochondrial DNA copy number (mtDNAcn) is an index of mitochondrial content and is responsive to changes in exercise training volume. Therefore, assessment of mtDNAcn may help to optimize exercise prescription and aid in athlete monitoring. Although previous work has assessed mtDNAcn derived from skeletal muscle and blood using invasive approaches, no study has examined salivary mtDNAcn and its relationship with sport performance. Fifteen adults (32.2 ± 7.1 years) volunteered to participate in this study. Each participant provided a saliva sample for the analysis of mtDNAcn via real-time polymerase reaction. In addition, participants completed an exercise challenge test to assess oxygen consumption relative to body weight (V[Combining Dot Above]O2·kg) and ventilatory efficiency (VE/V[Combining Dot Above]CO2). Using multiple linear regression, we examined the association of V[Combining Dot Above]O2·kg and VE/V[Combining Dot Above]CO2 with salivary mtDNAcn, adjusting for self-reported physical activity (min·wk). Greater mtDNAcn was associated with lower VE/V[Combining Dot Above]CO2 (p < 0.01) and higher V[Combining Dot Above]O2·kg (p < 0.05). In our model adjusted for physical activity, greater mtDNAcn remained associated with lower VE/V[Combining Dot Above]CO2 (ß = -0.186; 95% confidence interval [CI], -0.348 to -0.025; p < 0.05), but not with V[Combining Dot Above]O2·kg (ß = -0.022; 95% CI, -0.113 to 0.063). Our findings suggest that salivary mtDNAcn is associated with ventilatory efficiency, which may reflect enhanced exercise efficiency as a consequence of greater total mitochondrial content. As saliva collection is noninvasive, stable at room temperature, and less costly in comparison to skeletal muscle and blood, future studies may consider using saliva for the evaluation of mitochondrial content for the purposes of monitoring exercise training as well as optimizing exercise prescription.

Evidence of water molecules--a statistical evaluation of water molecules based on electron density.

Water molecules play important roles in many biological processes, especially when mediating protein-ligand interactions. Dehydration and the hydrophobic effect are of central importance for estimating binding affinities. Due to the specific geometric characteristics of hydrogen bond functions of water molecules, meaning two acceptor and two donor functions in a tetrahedral arrangement, they have to be modeled accurately. Despite many attempts in the past years, accurate prediction of water molecules-structurally as well as energetically-remains a grand challenge. One reason is certainly the lack of experimental data, since energetic contributions of water molecules can only be measured indirectly. However, on the structural side, the electron density clearly shows the positions of stable water molecules. This information has the potential to improve models on water structure and energy in proteins and protein interfaces. On the basis of a high-resolution subset of the Protein Data Bank, we have conducted an extensive statistical analysis of 2.3 million water molecules, discriminating those water molecules that are well resolved and those without much evidence of electron density. In order to perform this classification, we introduce a new measurement of electron density around an individual atom enabling the automatic quantification of experimental support. On the basis of this measurement, we present an analysis of water molecules with a detailed profile of geometric and structural features. This data, which is freely available, can be applied to not only modeling and validation of new water models in structural biology but also in molecular design.

Mapping and Characterization of Target-Site Resistance to Cyclic Ketoenol Insecticides in Cabbage Whiteflies, Aleyrodes proletella (Hemiptera: Aleyrodidae).

Cabbage whitefly, Aleyrodes proletella L., is an invasive hemipteran pest of cruciferous plants, particularly field brassica crops. Its importance has been increased over the last decade, particularly in European countries. The control of cabbage whiteflies largely relies on the application of synthetic insecticides, including tetronic and tetramic acid derivatives such as spiromesifen and spirotetramat (cyclic ketoenol insecticides), acting as insect growth regulators targeting acetyl-CoA carboxylase (ACC). In 2019, reduced efficacy against cabbage whiteflies of ketoenol insecticides at recommended label rates has been reported. Subsequently we collected field samples of A. proletella in different European countries and confirmed the presence of ketoenol resistance in laboratory bioassays. Reciprocal crossing experiments revealed an autosomal dominant trait, i.e., heterozygotes express a fully resistant phenotype. Transcriptome sequencing and assembly of ACC variants from resistant strains revealed the presence of an ACC target-site mutation, A2083V, as previously described and functionally validated in Bemisia tabaci (A2084V in A. proletella). Next, we employed a molecular genotyping assay to investigate the geographic spread of resistance and analyzed 49 populations collected in eight European countries. Resistance allele frequency was highest in the Netherlands, followed by Germany. Finally, we provide a proposal for the implementation of appropriate resistance management strategies.

Discovery and optimization of spirocyclic lactams that inhibit acyl-ACP thioesterase.

BACKGROUND: There are various methods to control weeds, that represent considerable challenges for farmers around the globe, although applying small molecular compounds is still the most effective and versatile technology to date. In the search for novel chemical entities with new modes-of-action that can control weeds displaying resistance, we have investigated two spirocyclic classes of acyl-ACP thioesterase inhibitors based on X-ray co-crystal structures and subsequent modelling studies. RESULTS: By exploiting scaffold-hopping and isostere concepts, we were able to identify new spirolactam-based lead structures showing promising activity in vivo against commercially important grass weeds in line with strong target affinity. CONCLUSION: The present work covers a series of novel herbicidal lead structures that contain a spirocyclic lactam as a structural key feature carrying ortho-substituted benzyl or heteroarylmethylene side chains. These new compounds show good acyl-ACP thioesterase inhibition in line with strong herbicidal activity. Glasshouse trials showed that the spirolactams outlined herein display promising control of grass-weed species in pre-emergence application combined with dose-response windows that enable partial selectivity in wheat and corn. Remarkably, some of the novel acyl-ACP thioesterase-inhibitors showed efficacy against resistant grass weeds such as Alopecurus myosuroides and Lolium spp. on competitive levels compared with commercial standards. © 2024 Society of Chemical Industry.

Self-reported stressors of National Guard women veterans before and after deployment: the relevance of interpersonal relationships.

BACKGROUND: With their rapidly expanding roles in the military, women service members experience significant stressors throughout their deployment experience. However, there are few studies that examine changes in women Veterans' stressors before and after deployment. OBJECTIVE: This study examines the types of stressors women Veterans report before deployment, immediately after deployment, 3 months after deployment, and 1 year post-deployment. DESIGN: Descriptive data on reported stressors was collected at four time points of a longitudinal study (HEROES Project). Open-ended responses from the Coping Response Inventory (CRI) were coded into six possible major stressor categories for analysis. PARTICIPANTS: Seventy-nine Army National Guard and Reserve female personnel deploying to Operation Enduring Freedom (OFF)/Operation Iraqi Freedom (OIF) were surveyed prior to deployment. Of these participants, 35 women completed Phase 2, 41 completed Phase 3, and 48 completed Phase 4 of the study. KEY RESULTS: We identified six major stressor categories: (1) interpersonal (i.e., issues with family and/or friends), (2) deployment-related and military-related, (3) health concerns, (4) death of a loved one, (5) daily needs (i.e., financial/housing/transportation concerns), and (6) employment or school-related concerns. At all time points, interpersonal issues were one of the most common type of stressor for this sample. Daily needs concerns increased from 3 months post-deployment to 1 year post-deployment. CONCLUSIONS: Interpersonal concerns are commonly reported by women Veterans both before and after their combat experience, suggesting that this is a time during which interpersonal support is especially critical. We discuss implications, which include the need for a more coordinated approach to women Veterans' health care (e.g., greater community-based outreach), and the need for more and more accessible Veterans Affairs (VA) services to address the needs of female Veterans.

A consistent description of HYdrogen bond and DEhydration energies in protein-ligand complexes: methods behind the HYDE scoring function.

The estimation of free energy of binding is a key problem in structure-based design. We developed the scoring function HYDE based on a consistent description of HYdrogen bond and DEhydration energies in protein-ligand complexes. HYDE is applicable to all types of protein targets since it is not calibrated on experimental binding affinity data or protein-ligand complexes. The comprehensible atom-based score of HYDE is visualized by applying a very intuitive coloring scheme, thereby facilitating the analysis of protein-ligand complexes in the lead optimization process. In this paper, we have revised several aspects of the former version of HYDE which was described in detail previously. The revised HYDE version was already validated in large-scale redocking and screening experiments which were performed in the course of the Docking and Scoring Symposium at 241st ACS National Meeting. In this study, we additionally evaluate the ability of the revised HYDE version to predict binding affinities. On the PDBbind 2007 coreset, HYDE achieves a correlation coefficient of 0.62 between the experimental binding constants and the predicted binding energy, performing second best on this dataset compared to 17 other well-established scoring functions. Further, we show that the performance of HYDE in large-scale redocking and virtual screening experiments on the Astex diverse set and the DUD dataset respectively, is comparable to the best methods in this field.

4-Hydroxyphenylpyruvate dioxygenase inhibitors in combination with safeners: solutions for modern and sustainable agriculture.

Inhibitors of 4-hydroxyphenylpyruvate dioxygenase (HPPD) prevent plant carotenoid pigment formation, which in turn leads to chlorophyll degradation. This "bleaching" herbicide mode of action provides weed-control products for various crops, such as rice, corn, and cereals. Combinations with suitable safeners allow the full exploitation of the potential of this compound class to selectively control major weed problems, including rapidly increasing cases of resistance against other important herbicide classes.

Selective herbicide safening in dicot plants: a case study in Arabidopsis.

Safeners are agrochemicals co-applied with herbicides that facilitate selective control of weeds by protecting monocot crops from chemical injury through enhancing the expression of detoxifying enzymes such as glutathione transferases (GSTs). Even though the application of safeners causes the induction of genes encoding GSTs in model dicots such as Arabidopsis thaliana, safeners do not protect broadleaf crops from herbicide injury. In this study, we proposed that the localized induction of Arabidopsis GSTs and the fundamental differences in their detoxifying activity between dicot and monocot species, underpin the failure of safeners to protect Arabidopsis from herbicide toxicity. Using the herbicide safener, isoxadifen-ethyl, we showed that three tau (U) family GSTs namely AtGSTU7, AtGSTU19 and AtGSTU24 were induced with different magnitude by isoxadifen treatment in root and rosette tissues. The higher magnitude of inducibility of these AtGSTUs in the root tissues coincided with the enhanced metabolism of flufenacet, a herbicide that is active in root tissue, protecting Arabidopsis plants from chemical injury. Assay of the recombinant enzyme activities and the significant reduction in flufenacet metabolism determined in the T-DNA insertion mutant of AtGSTU7 (gstu7) in Arabidopsis plants identified an important function for AtGSTU7 protein in flufenacet detoxification. In-silico structural modeling of AtGSTU7, suggested the unique high activity of this enzyme toward flufenacet was due to a less constrained active site compared to AtGSTU19 and AtGSTU24. We demonstrate here that it is possible to induce herbicide detoxification in dicotyledonous plants by safener treatment, albeit with this activity being restricted to very specific combinations of herbicide chemistry, and the localized induction of enzymes with specific detoxifying activities.

Designing New Protoporphyrinogen Oxidase-Inhibitors Carrying Potential Side Chain Isosteres to Enhance Crop Safety and Spectrum of Activity.

There are several methods to control weeds, which impose particular challenges for farmers in all parts of the world, although applying small molecular compounds still remains the most efficient technology to date. However, plants can evolve to become resistant toward active ingredients which is also the case for protoporphyrinogen oxidase (PPO) inhibitors, a class of highly effective herbicides in use for more than 50 years. Hence, it is essential to continuously discover and develop new herbicidal PPO inhibitors with enhanced intrinsic activity, an improved resistance profile, enhanced crop safety, favorable physicochemical properties, and a clean toxicological profile. By modifying structural key features from known PPO inhibitors such as tiafenacil, inspired by isostere and mix&match concepts in combination with modeling investigations based on a wild-type Amaranthus crystal structure, we have found new promising lead structures showing strong activity in vitro and in vivo against several notorious dicotyledon and monocotyledon weeds with emerging resistance (e.g., Amaranthus palmeri, Amaranthus tuberculatus, Lolium rigidum, and Alopecurus myosuroides). While several phenyl uracils carrying an isoxazoline motif in their thio-linked side chain showed promising resistance-breaking potential against different Amaranthus species, introducing a thioacrylamide side chain afforded outstanding efficacy against resistant grass weeds.

Design, synthesis and screening of herbicidal activity for new phenyl pyrazole-based protoporphyrinogen oxidase-inhibitors (PPO) overcoming resistance issues.

BACKGROUND: Whilst there are several methods to control weeds, which continuously plague farmers around the globe, the application of small molecular compounds is still the most effective technology to date. Plants can evolve to become resistant to PPO-inhibitors, a class of herbicides in commercial use since the 1960s. It is therefore essential to continuously develop new herbicides based on this mode-of-action with enhanced intrinsic activity, an improved resistance profile and favourable physicochemical properties. Based on an Amaranthus PPO crystal structure and subsequent modelling studies, halogen-substituted pyrazoles have been investigated as isosteres of uracil-based PPO-inhibitors. RESULTS: By combining structural features from the commercial PPO-inhibitors tiafenacil and pyraflufen-ethyl and by investigating receptor-binding properties, we identified new promising pyrazole-based lead structures showing strong activity in vitro and in vivo against economically important weeds of the Amaranthus genus: A. retroflexus, and resistant A. palmeri and A. tuberculatus. CONCLUSION: The present work covers a series of novel PPO-inhibiting compounds that contain a pyrazole ring and a substituted thioacetic acid sidechain attached to the core phenyl group. These compounds show good receptor fit in line with excellent herbicidal activity against weeds that plague corn and rice crops with low application rates. This, in combination with promising selectivity in corn, have the potential to mitigate and affect weeds that have become resistant to some of the current market standards. Remarkably, some of the novel PPO-inhibitors outlined herein show efficacies against economically important weeds that were superior to recently commercialized and structurally related tiafenacil. © 2023 Society of Chemical Industry.

A Study in Scaffold Hopping: Discovery and Optimization of Thiazolopyridines as Potent Herbicides That Inhibit Acyl-ACP Thioesterase.

In the search for new chemical entities that can control resistant weeds by addressing novel modes of action (MoAs), we were interested in further exploring a compound class that contained a 1,8-naphthyridine core. By leveraging scaffold hopping methodologies, we were able to discover the new thiazolopyridine compound class that act as potent herbicidal molecules. Further biochemical investigations allowed us to identify that the thiazolopyridines inhibit acyl-acyl carrier protein (ACP) thioesterase (FAT), with this being further confirmed via an X-ray cocrystal structure. Greenhouse trials revealed that the thiazolopyridines display excellent control of grass weed species in pre-emergence application coupled with dose response windows that enable partial selectivity in certain crops.

Substantial improvements in large-scale redocking and screening using the novel HYDE scoring function.

The HYDE scoring function consistently describes hydrogen bonding, the hydrophobic effect and desolvation. It relies on HYdration and DEsolvation terms which are calibrated using octanol/water partition coefficients of small molecules. We do not use affinity data for calibration, therefore HYDE is generally applicable to all protein targets. HYDE reflects the Gibbs free energy of binding while only considering the essential interactions of protein-ligand complexes. The greatest benefit of HYDE is that it yields a very intuitive atom-based score, which can be mapped onto the ligand and protein atoms. This allows the direct visualization of the score and consequently facilitates analysis of protein-ligand complexes during the lead optimization process. In this study, we validated our new scoring function by applying it in large-scale docking experiments. We could successfully predict the correct binding mode in 93% of complexes in redocking calculations on the Astex diverse set, while our performance in virtual screening experiments using the DUD dataset showed significant enrichment values with a mean AUC of 0.77 across all protein targets with little or no structural defects. As part of these studies, we also carried out a very detailed analysis of the data that revealed interesting pitfalls, which we highlight here and which should be addressed in future benchmark datasets.