DiMIZA : a dispersion modeling based impact zone assessment of mercury (Hg) emissions from coal-fired power plants and risk evaluation for inhalation exposure

Coal-fired combined heat and power plants (CHPPs) serving large districts are among the major sources of mercury (Hg) emissions globally, including Central Asia. Most CHPPs reside on the outskirts of urban areas, thus creating risk zones. The impact of atmospheric Hg levels on health is complex to establish due to the site-specific nature of the relationship between CHPP emissions and hotspots (i.e., localized areas where Hg concentrations greatly exceed its background value). However, a methodological identification of "emission impact zones" for atmospheric Hg emissions from CHPPs with potential adverse public health outcomes has not yet been fully studied. The present work suggests an easy-to-use and cost-free impact zone identification method based on HYSPLIT dispersion modeling for atmospheric Hg emissions from CHPPs. The dispersion modeling based impact zone assessment, DiMIZA, merges short-term dispersion runs (e.g., hourly) into long-term emission impacts (e.g., yearly), which allows to identify the source impact zones. To perform a case study using the suggested method, a CHPP plant in Nur-Sultan (capital of Kazakhstan) was selected. First, traditional ad-hoc measurements were performed to identify the level of dispersions at ground level in different atmospheric stability characteristics. Then, HYSPLIT dispersion model was run for the same days and times of those particular periods when the field measurements were performed. The model results were evaluated via a comparison with the ground measurements and assessed for their atmospheric stability and diel conditions. Due to different emission loads in heating and non-heating periods, two separate pairs of impact zone maps were generated, and public Hg exposure health risks (acute and chronic) were assessed

Proteins with Complex Architecture as Potential Targets for Drug Design: A Case Study of Mycobacterium tuberculosis

Lengthy co-evolution of Homo sapiens and Mycobacterium tuberculosis, the main causative agent of tuberculosis, resulted in a dramatically successful pathogen species that presents considerable challenge for modern medicine. The continuous and ever increasing appearance of multi-drug resistant mycobacteria necessitates the identification of novel drug targets and drugs with new mechanisms of action. However, further insights are needed to establish automated protocols for target selection based on the available complete genome sequences. In the present study, we perform complete proteome level comparisons between M. tuberculosis, mycobacteria, other prokaryotes and available eukaryotes based on protein domains, local sequence similarities and protein disorder. We show that the enrichment of certain domains in the genome can indicate an important function specific to M. tuberculosis. We identified two families, termed pkn and PE/PPE that stand out in this respect. The common property of these two protein families is a complex domain organization that combines species-specific regions, commonly occurring domains and disordered segments. Besides highlighting promising novel drug target candidates in M. tuberculosis, the presented analysis can also be viewed as a general protocol to identify proteins involved in species-specific functions in a given organism. We conclude that target selection protocols should be extended to include proteins with complex domain architectures instead of focusing on sequentially unique and essential proteins only

Methods of probing the interactions between small molecules and disordered proteins

It is generally recognized that a large fraction of the human proteome is made up of proteins that remain disordered in their native states. Despite the fact that such proteins play key biological roles and are involved in many major human diseases, they still represent challenging targets for drug discovery. A major bottleneck for the identification of compounds capable of interacting with these proteins and modulating their disease-promoting behaviour is the development of effective techniques to probe such interactions. The difficulties in carrying out binding measurements have resulted in a poor understanding of the mechanisms underlying these interactions. In order to facilitate further methodological advances, here we review the most commonly used techniques to probe three types of interactions involving small molecules: (1) those that disrupt functional interactions between disordered proteins; (2) those that inhibit the aberrant aggregation of disordered proteins, and (3) those that lead to binding disordered proteins in their monomeric states. In discussing these techniques, we also point out directions for future developments.Gabriella T. Heller is supported by the Gates Cambridge Trust Scholarship. Francesco A. Aprile is supported by a Senior Research Fellowship award from the Alzheimer’s Society, UK (grant number 317, AS-SF-16-003)

L-2-hydroxyglutarate production arises from non-canonical enzyme function at acidic pH

The metabolite 2-hydroxyglutarate (2HG) can be produced as either a D(R)- or L(S)- enantiomer, each of which inhibits alpha-ketoglutarate (αKG)-dependent enzymes involved in diverse biologic processes. Oncogenic mutations in isocitrate dehydrogenase produce D-2HG, which causes a pathologic blockade in cell differentiation. On the other hand, oxygen limitation leads to accumulation of L-2HG, which can facilitate physiologic adaptation to hypoxic stress in both normal and malignant cells. Here we demonstrate that purified lactate dehydrogenase (LDH) and malate dehydrogenase (MDH) catalyze stereospecific production of L-2HG via ‘promiscuous’ reduction of the alternative substrate αKG. Acidic pH enhances production of L-2HG by promoting a protonated form of αKG that binds to a key residue in the substrate-binding pocket of LDHA. Acid-enhanced production of L-2HG leads to stabilization of hypoxia-inducible factor 1 alpha (HIF-1α) in normoxia. These findings offer insights into mechanisms whereby microenvironmental factors influence production of metabolites that alter cell fate and function

Cyclized NDGA modifies dynamic α-synuclein monomers preventing aggregation and toxicity.

Growing evidence implicates α-synuclein aggregation as a key driver of neurodegeneration in Parkinson's disease (PD) and other neurodegenerative disorders. Herein, the molecular and structural mechanisms of inhibiting α-synuclein aggregation by novel analogs of nordihydroguaiaretic acid (NDGA), a phenolic dibenzenediol lignan, were explored using an array of biochemical and biophysical methodologies. NDGA analogs induced modest, progressive compaction of monomeric α-synuclein, preventing aggregation into amyloid-like fibrils. This conformational remodeling preserved the dynamic adoption of α-helical conformations, which are essential for physiological membrane interactions. Oxidation-dependent NDGA cyclization was required for the interaction with monomeric α-synuclein. NDGA analog-pretreated α-synuclein did not aggregate even without NDGA-analogs in the aggregation mixture. Strikingly, NDGA-pretreated α-synuclein suppressed aggregation of naïve untreated aggregation-competent monomeric α-synuclein. Further, cyclized NDGA reduced α-synuclein-driven neurodegeneration in Caenorhabditis elegans. The cyclized NDGA analogs may serve as a platform for the development of small molecules that stabilize aggregation-resistant α-synuclein monomers without interfering with functional conformations yielding potential therapies for PD and related disorders