Target-Pathogen: a structural bioinformatic approach to prioritize drug targets in pathogens

High-throughput prioritization of target proteins for development of new antileishmanial compounds

Leishmaniasis, a vector-borne disease, is caused by the infection of Leishmania spp., obligate intracellular protozoan parasites. Presently, human vaccines are unavailable, and the primary treatment relies heavily on systemic drugs, often presenting with suboptimal formulations and substantial toxicity, making new drugs a high priority for LMIC countries burdened by the disease, but a low priority in the agenda of most pharmaceutical companies due to unattractive profit margins. New ways to accelerate the discovery of new, or the repositioning of existing drugs, are needed. To address this challenge, our study aimed to identify potential protein targets shared among clinically-relevant Leishmania species. We employed a subtractive proteomics and comparative genomics approach, integrating high-throughput multi-omics data to classify these targets based on different druggability metrics. This effort resulted in the ranking of 6502 ortholog groups of protein targets across 14 pathogenic Leishmania species. Among the top 20 highly ranked groups, metabolic processes known to be attractive drug targets, including the ubiquitination pathway, aminoacyl-tRNA synthetases, and purine synthesis, were rediscovered. Additionally, we unveiled novel promising targets such as the nicotinate phosphoribosyltransferase enzyme and dihydrolipoamide succinyltransferases. These groups exhibited appealing druggability features, including less than 40% sequence identity to the human host proteome, predicted essentiality, structural classification as highly druggable or druggable, and expression levels above the 50th percentile in the amastigote form. The resources presented in this work also represent a comprehensive collection of integrated data regarding trypanosomatid biology.

Nitrosative stress under microaerobic conditions triggers inositol metabolism in Pseudomonas extremaustralis

Bacteria are exposed to reactive oxygen and nitrogen species that provoke oxidative and nitrosative stress which can lead to macromolecule damage. Coping with stress conditions involves the adjustment of cellular responses, which helps to address metabolic challenges. In this study, we performed a global transcriptomic analysis of the response of Pseudomonas extremaustralis to nitrosative stress, induced by S-nitrosoglutathione (GSNO), a nitric oxide donor, under microaerobic conditions. The analysis revealed the upregulation of genes associated with inositol catabolism; a compound widely distributed in nature whose metabolism in bacteria has aroused interest. The RNAseq data also showed heightened expression of genes involved in essential cellular processes like transcription, translation, amino acid transport and biosynthesis, as well as in stress resistance including iron-dependent superoxide dismutase, alkyl hydroperoxide reductase, thioredoxin, and glutathione S-transferase in response to GSNO. Furthermore, GSNO exposure differentially affected the expression of genes encoding nitrosylation target proteins, encompassing metalloproteins and proteins with free cysteine and /or tyrosine residues. Notably, genes associated with iron metabolism, such as pyoverdine synthesis and iron transporter genes, showed activation in the presence of GSNO, likely as response to enhanced protein turnover. Physiological assays demonstrated that P. extremaustralis can utilize inositol proficiently under both aerobic and microaerobic conditions, achieving growth comparable to glucose-supplemented cultures. Moreover, supplementing the culture medium with inositol enhances the stress tolerance of P. extremaustralis against combined oxidative-nitrosative stress. Concordant with the heightened expression of pyoverdine genes under nitrosative stress, elevated pyoverdine production was observed when myo-inositol was added to the culture medium. These findings highlight the influence of nitrosative stress on proteins susceptible to nitrosylation and iron metabolism. Furthermore, the activation of myo-inositol catabolism emerges as a protective mechanism against nitrosative stress, shedding light on this pathway in bacterial systems, and holding significance in the adaptation to unfavorable conditions.

Bacterial cytochrome P450s: a bioinformatics odyssey of substrate discovery

Bacterial P450 cytochromes (BacCYPs) are versatile heme-containing proteins responsible for oxidation reactions on a wide range of substrates, contributing to the production of valuable natural products with limitless biotechnological potential. While the sequencing of microbial genomes has provided a wealth of BacCYP sequences, functional characterization lags behind, hindering our understanding of their roles. This study employs a comprehensive approach to predict BacCYP substrate specificity, bridging the gap between sequence and function. We employed an integrated approach combining sequence and functional data analysis, genomic context exploration, 3D structural modeling with molecular docking, and phylogenetic clustering. The research begins with an in-depth analysis of BacCYP sequence diversity and structural characteristics, revealing conserved motifs and recurrent residues in the active site. Phylogenetic analysis identifies distinct groups within the BacCYP family based on sequence similarity. However, our study reveals that sequence alone does not consistently predict substrate specificity, necessitating additional perspectives. The study delves into the genetic context of BacCYPs, utilizing neighboring gene information to infer potential substrates, a method proven very effective in many cases. Molecular docking is employed to assess BacCYP-substrate interactions, confirming potential substrates and providing insights into selectivity. Finally, a comprehensive strategy is proposed for predicting BacCYP substrates, involving all the evaluated approaches. The effectiveness of this strategy is demonstrated with two case studies, highlighting its potential for substrate discovery.

Unrealized targets in the discovery of antibiotics for Gram-negative bacterial infections

Advances in areas that include genomics, systems biology, protein structure determination and artificial intelligence provide new opportunities for target-based antibacterial drug discovery. The selection of a 'good' new target for direct-acting antibacterial compounds is the first decision, for which multiple criteria must be explored, integrated and re-evaluated as drug discovery programmes progress. Criteria include essentiality of the target for bacterial survival, its conservation across different strains of the same species, bacterial species and growth conditions (which determines the spectrum of activity of a potential antibiotic) and the level of homology with human genes (which influences the potential for selective inhibition). Additionally, a bacterial target should have the potential to bind to drug-like molecules, and its subcellular location will govern the need for inhibitors to penetrate one or two bacterial membranes, which is a key challenge in targeting Gram-negative bacteria. The risk of the emergence of target-based drug resistance for drugs with single targets also requires consideration. This Review describes promising but as-yet-unrealized targets for antibacterial drugs against Gram-negative bacteria and examples of cognate inhibitors, and highlights lessons learned from past drug discovery programmes.

Identification of potential novel therapeutic drug target against Elizabethkingia anophelis by integrative pan and subtractive genomic analysis: An in silico approach

Elizabethkingia anophelis is a human pathogen responsible for severe nosocomial infections in neonates and immunocompromised patients. The significantly higher mortality rate from E. anophelis infections and the lack of available regimens highlight the critical need to explore novel drug targets. The current study investigated effective novel drug targets by employing a comprehensive in silico subtractive genomic approach integrated with pangenomic analysis of E. anophelis strains. A total of 2809 core genomic proteins were found by pangenomic analysis of non-paralogous proteins. Subsequently, 156 pathogen-specific, 442 choke point, 202 virulence factor, 53 antibiotic resistant and 119 host-pathogen interacting proteins were identified in E. anophelis. By subtractive genomic approach, at first 791 proteins were found to be indispensable for the survival of E. anophelis. 558 and 315 proteins were detected as non-homologous to human and gut microflora respectively. Following that 245 cytoplasmic, 245 novel, and 23 broad-spectrum targets were selected and finally four proteins were considered as potential therapeutic targets of E. anophelis based on highest degree score in PPI network. Among those, three proteins were subjected to molecular docking and subsequent MD simulation as one protein did not contain a plausible binding pocket with sufficient surface area and volume. All the complexes were found to be stable and compact in 100 ns molecular dynamics simulation studies as measured by RMSD, RMSF, and Rg. These three short-listed targets identified in this study may lead to the development of novel antimicrobials capable of curing infections and pave the way to prevent and control the disease progression caused by the deadly agent E. anophelis.

Omics data integration facilitates target selection for new antiparasitic drugs against TriTryp infections

Introduction:Trypanosoma cruzi, Trypanosoma brucei, and Leishmania spp., commonly referred to as TriTryps, are a group of protozoan parasites that cause important human diseases affecting millions of people belonging to the most vulnerable populations worldwide. Current treatments have limited efficiencies and can cause serious side effects, so there is an urgent need to develop new control strategies. Presently, the identification and prioritization of appropriate targets can be aided by integrative genomic and computational approaches.

Methods: In this work, we conducted a genome-wide multidimensional data integration strategy to prioritize drug targets. We included genomic, transcriptomic, metabolic, and protein structural data sources, to delineate candidate proteins with relevant features for target selection in drug development.

Results and Discussion: Our final ranked list includes proteins shared by TriTryps and covers a range of biological functions including essential proteins for parasite survival or growth, oxidative stress-related enzymes, virulence factors, and proteins that are exclusive to these parasites. Our strategy found previously described candidates, which validates our approach as well as new proteins that can be attractive targets to consider during the initial steps of drug discovery.

Latent tuberculosis and computational biology: A less-talked affair

Tuberculosis (TB) is a pervasive and devastating air-borne disease caused by the organisms belonging to the Mycobacterium tuberculosis (Mtb) complex. Currently, it is the global leader in infectious disease-related death in adults. The proclivity of TB to enter the latent state has become a significant impediment to the global effort to eradicate TB. Despite decades of research, latent tuberculosis (LTB) mechanisms remain poorly understood, making it difficult to develop efficient treatment methods. In this review, we seek to shed light on the current understanding of the mechanism of LTB, with an accentuation on the insights gained through computational biology. We have outlined various well-established computational biology components, such as omics, network-based techniques, mathematical modelling, artificial intelligence, and molecular docking, to disclose the crucial facets of LTB. Additionally, we highlighted important tools and software that may be used to conduct a variety of systems biology assessments. Finally, we conclude the article by addressing the possible future directions in this field, which might help a better understanding of LTB progression.

Identifying Potential Molecular Targets in Fungi Based on (Dis)Similarities in Binding Site Architecture with Proteins of the Human Pharmacolome

Invasive fungal infections represent a public health problem that worsens over the years with the increasing resistance to current antimycotic agents. Therefore, there is a compelling medical need of widening the antifungal drug repertoire, following different methods such as drug repositioning, identification and validation of new molecular targets and developing new inhibitors against these targets. In this work we developed a structure-based strategy for drug repositioning and new drug design, which can be applied to infectious fungi and other pathogens. Instead of applying the commonly accepted off-target criterion to discard fungal proteins with close homologues in humans, the core of our approach consists in identifying fungal proteins with active sites that are structurally similar, but preferably not identical to binding sites of proteins from the so-called "human pharmacolome". Using structural information from thousands of human protein target-inhibitor complexes, we identified dozens of proteins in fungal species of the genera Histoplasma, Candida, Cryptococcus, Aspergillus and Fusarium, which might be exploited for drug repositioning and, more importantly, also for the design of new fungus-specific inhibitors. As a case study, we present the in vitro experiments performed with a set of selected inhibitors of the human mitogen-activated protein kinases 1/2 (MEK1/2), several of which showed a marked cytotoxic activity in different fungal species.

Genome-Wide Subtraction Analysis and Reverse Vaccinology to Detect Novel Drug Targets and Potential Vaccine Candidates Against Ehrlichia chaffeensis

Human monocytotropic ehrlichiosis is an emerging tick-borne infection caused by the obligate intracellular pathogen, Ehrlichia chaffeensis. The non-specific symptoms can range from a self-limiting fever to a fatal septic-like syndrome and may be misdiagnosed. The limited treatment choices including doxycycline are effective only in the initiation phase of the infection. It seems that novel therapeutic targets and new vaccine strategies could be effective to control this pathogen. This study is comprised of two major phases. First, the common proteins retrieved through subtractive analysis and potential drug targets were evaluated by subcellular localization, homology prediction, metabolic pathways, druggability, essentiality, protein-protein interaction networks, and protein data bank availability. In the second phase, surface-exposed proteins were assessed based on antigenicity, allergenicity, physiochemical properties, B cell and T cell epitopes, conserved domains, and protein-protein interaction networks. A multi-epitope vaccine was designed and characterized using molecular dockings and immune simulation analysis. Six proteins including WP_011452818.1, WP_011452723.1, WP_006010413.1, WP_006010278.1, WP_011452938.1, and WP_006010644.1 were detected. They belong to unique metabolic pathways of E. chaffeensis that are considered as new essential drug targets. Based on the reverse vaccinology, WP_011452702.1, WP_044193405.1, WP_044170604.1, and WP_006010191.1 proteins were potential vaccine candidates. Finally, four B cell epitopes, including SINNQDRNC, FESVSSYNI, SGKKEISVQSN, and QSSAKRKST, were used to generate the multi-epitope vaccine based on LCL platform. The vaccine showed strong interactions with toll-like receptors and acceptable immune-reactivity by immune simulation analysis. The findings of this study may represent a turning point in developing an effective drug and vaccine against E. chaffeensis. However, further experimental analyses have remained.

Pathway Driven Target Selection in Klebsiella pneumoniae: Insights Into Carbapenem Exposure

Carbapenem-resistant Klebsiella pneumoniae (CR-KP) represents an emerging threat to public health. CR-KP infections result in elevated morbidity and mortality. This fact, coupled with their global dissemination and increasingly limited number of therapeutic options, highlights the urgency of novel antimicrobials. Innovative strategies linking genome-wide interrogation with multi-layered metabolic data integration can accelerate the early steps of drug development, particularly target selection. Using the BioCyc ontology, we generated and manually refined a metabolic network for a CR-KP, K. pneumoniae Kp13. Converted into a reaction graph, we conducted topological-based analyses in this network to prioritize pathways exhibiting druggable features and fragile metabolic points likely exploitable to develop novel antimicrobials. Our results point to the aptness of previously recognized pathways, such as lipopolysaccharide and peptidoglycan synthesis, and casts light on the possibility of targeting less explored cellular functions. These functions include the production of lipoate, trehalose, glycine betaine, and flavin, as well as the salvaging of methionine. Energy metabolism pathways emerged as attractive targets in the context of carbapenem exposure, targeted either alone or in conjunction with current therapeutic options. These results prompt further experimental investigation aimed at controlling this highly relevant pathogen.

Peptide-Based Vaccines for Tuberculosis

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis. As a result of the coronavirus disease 2019 (COVID-19) pandemic, the global TB mortality rate in 2020 is rising, making TB prevention and control more challenging. Vaccination has been considered the best approach to reduce the TB burden. Unfortunately, BCG, the only TB vaccine currently approved for use, offers some protection against childhood TB but is less effective in adults. Therefore, it is urgent to develop new TB vaccines that are more effective than BCG. Accumulating data indicated that peptides or epitopes play essential roles in bridging innate and adaptive immunity and triggering adaptive immunity. Furthermore, innovations in bioinformatics, immunoinformatics, synthetic technologies, new materials, and transgenic animal models have put wings on the research of peptide-based vaccines for TB. Hence, this review seeks to give an overview of current tools that can be used to design a peptide-based vaccine, the research status of peptide-based vaccines for TB, protein-based bacterial vaccine delivery systems, and animal models for the peptide-based vaccines. These explorations will provide approaches and strategies for developing safer and more effective peptide-based vaccines and contribute to achieving the WHO's End TB Strategy.

virusMED: an atlas of hotspots of viral proteins

Metal binding sites, antigen epitopes and drug binding sites are the hotspots in viral proteins that control how viruses interact with their hosts. virusMED (virus Metal binding sites, Epitopes and Drug binding sites) is a rich internet application based on a database of atomic interactions around hotspots in 7041 experimentally determined viral protein structures. 25306 hotspots from 805 virus strains from 75 virus families were characterized, including influenza, HIV-1 and SARS-CoV-2 viruses. Just as Google Maps organizes and annotates points of interest, virusMED presents the positions of individual hotspots on each viral protein and creates an atlas upon which newly characterized functional sites can be placed as they are being discovered. virusMED contains an extensive set of annotation tags about the virus species and strains, viral hosts, viral proteins, metal ions, specific antibodies and FDA-approved drugs, which permits rapid screening of hotspots on viral proteins tailored to a particular research problem. The virusMED portal (https://virusmed.biocloud.top) can serve as a window to a valuable resource for many areas of virus research and play a critical role in the rational design of new preventative and therapeutic agents targeting viral infections.

The thermal proteome stability profile of Trypanosoma cruzi in epimastigote and trypomastigote life stages

Trypanosoma cruzi is a flagellate protozoa being the etiological agent of Chagas disease, a neglected tropical disease, which still poses a public health problem worldwide. The intricate molecular changes during T. cruzi-host interaction have been explored using different largescale omics techniques. However, protein stability is largely unknown. Thermal proteome profiling (TPP) methodology has the potential to characterize proteome-wide stability highlighting key proteins during T. cruzi infection and life stage transition from the invertebrate to the mammalian host. In the present work, T. cruzi epimastigotes and trypomastigotes cell lysates were subjected to TPP workflow and analyzed by quantitative large-scale mass spectrometry-based proteomics to fit a melting profile for each protein. A total of 2884 proteins were identified and associated to 1741 melting curves being 1370 in trypomastigotes (Tm_AVG 53.53 °C) and 1279 in epimastigotes (Tm_AVG 50.89 °C). A total of 453 proteins were identified with statistically different melting profiles between the two life stages. Proteins associated to pathogenesis and intracellular transport had regulated melting temperatures. Membrane and glycosylated proteins had a higher average Tm in trypomastigotes compared to epimastigotes. This study represents the first large-scale comparison of parasite protein stability between life stages. SIGNIFICANCE: Trypanosoma cruzi, a unicellular flagellate parasite, is the etiological agent of Chagas disease, endemic in South America and affecting more that 7 million people worldwide. There is an intense research to identify novel chemotherapeutic and diagnostic targets of Chagas disease. Proteomic approaches have helped in elucidating the quantitative proteome and PTMs changes of T. cruzi during life cycle transition and upon different biotic and abiotic stimuli. However, a comprehensive knowledge of the protein-protein interaction and protein conformation is still missing. In order to fill this gap, this manuscript elucidates the T. cruzi Y strain proteome-wide thermal stability map in the epimastigote and trypomastigote life stages. Comparison between life stages showed a higher average melting temperature stability for trypomastigotes than epimastigotes indicating a host temperature adaptation. Both presented a selective thermal stability shift for cellular compartments, molecular functions and biological processes based on the T. cruzi life stage. Membrane and glycosylated proteins presented a higher thermal stability in trypomastigotes when compared to the epimastigotes.

Identification of Potential Kinase Inhibitors within the PI3K/AKT Pathway of Leishmania Species

Leishmaniasis is a public health disease that requires the development of more effective treatments and the identification of novel molecular targets. Since blocking the PI3K/AKT pathway has been successfully studied as an effective anticancer strategy for decades, we examined whether the same approach would also be feasible in Leishmania due to their high amount and diverse set of annotated proteins. Here, we used a best reciprocal hits protocol to identify potential protein kinase homologues in an annotated human PI3K/AKT pathway. We calculated their ligandibility based on available bioactivity data of the reported homologues and modelled their 3D structures to estimate the druggability of their binding pockets. The models were used to run a virtual screening method with molecular docking. We found and studied five protein kinases in five different Leishmania species, which are AKT, CDK, AMPK, mTOR and GSK3 homologues from the studied pathways. The compounds found for different enzymes and species were analysed and suggested as starting point scaffolds for the design of inhibitors. We studied the kinases’ participation in protein–protein interaction networks, and the potential deleterious effects, if inhibited, were supported with the literature. In the case of Leishmania GSK3, an inhibitor of its human counterpart, prioritized by our method, was validated in vitro to test its anti-Leishmania activity and indirectly infer the presence of the enzyme in the parasite. The analysis contributes to improving the knowledge about the presence of similar signalling pathways in Leishmania, as well as the discovery of compounds acting against any of these kinases as potential molecular targets in the parasite.

From Genome to Drugs: New Approaches in Antimicrobial Discovery

Decades of successful use of antibiotics is currently challenged by the emergence of increasingly resistant bacterial strains. Novel drugs are urgently required but, in a scenario where private investment in the development of new antimicrobials is declining, efforts to combat drug-resistant infections become a worldwide public health problem. Reasons behind unsuccessful new antimicrobial development projects range from inadequate selection of the molecular targets to a lack of innovation. In this context, increasingly available omics data for multiple pathogens has created new drug discovery and development opportunities to fight infectious diseases. Identification of an appropriate molecular target is currently accepted as a critical step of the drug discovery process. Here, we review how diverse layers of multi-omics data in conjunction with structural/functional analysis and systems biology can be used to prioritize the best candidate proteins. Once the target is selected, virtual screening can be used as a robust methodology to explore molecular scaffolds that could act as inhibitors, guiding the development of new drug lead compounds. This review focuses on how the advent of omics and the development and application of bioinformatics strategies conduct a "big-data era" that improves target selection and lead compound identification in a cost-effective and shortened timeline.

Five-year microevolution of a multidrug-resistant Mycobacterium tuberculosis strain within a patient with inadequate compliance to treatment

BACKGROUND

Whole-genome sequencing has shown that the Mycobacterium tuberculosis infection process can be more heterogeneous than previously thought. Compartmentalized infections, exogenous reinfections, and microevolution are manifestations of this clonal complexity. The analysis of the mechanisms causing the microevolution -the genetic variability of M. tuberculosis at short time scales- of a parental strain into clonal variants with a patient is a relevant issue that has not been yet completely addressed. To our knowledge, a whole genome sequence microevolution analysis in a single patient with inadequate adherence to treatment has not been previously reported.

CASE PRESENTATION

In this work, we applied whole genome sequencing analysis for a more in-depth analysis of the microevolution of a parental Mycobacterium tuberculosis strain into clonal variants within a patient with poor treatment compliance in Argentina. We analyzed the whole-genome sequence of 8 consecutive Mycobacterium tuberculosis isolates obtained from a patient within 57-months of intermittent therapy. Nineteen mutations (9 short-term, 10 fixed variants) emerged, most of them associated with drug resistance. The first isolate was already resistant to isoniazid, rifampicin, and streptomycin, thereafter the strain developed resistance to fluoroquinolones and pyrazinamide. Surprisingly, isolates remained susceptible to the pro-drug ethionamide after acquiring a frameshift mutation in ethA, a gene required for its activation. We also found a novel variant, (T-54G), in the 5' untranslated region of whiB7 (T-54G), a region allegedly related to kanamycin resistance. Notably, discrepancies between canonical and phage-based susceptibility testing to kanamycin were previously found for the isolate harboring this mutation. In our patient, microevolution was mainly driven by drug selective pressure. Rare short-term mutations fixed together with resistance-conferring mutations during therapy.

CONCLUSIONS

This report highlights the relevance of whole-genome sequencing analysis in the clinic for characterization of pre-XDR and MDR resistance profile, particularly in patients with incomplete and/or intermittent treatment.

Computer aided drug discovery review for infectious diseases with case study of anti-Chagas project

Neglected tropical diseases (NTDs) are parasitic and bacterial infections that are widespread, especially in the tropics, and cause health problems for about one billion people over 149 countries worldwide. However, in terms of therapeutic agents, for example, nifurtimox and benznidazole were developed in the 1960s to treat Chagas disease, but new drugs are desirable because of their side effects. Drug discovery takes 12 to 14 years and costs $2.6 billon dollars, and hence, computer aided drug discovery (CADD) technology is expected to reduce the time and cost. This paper describes our methods and results based on CADD, mainly for NTDs. An overview of databases, molecular simulation and pharmacophore modeling, contest-based drug discovery, and machine learning and their results are presented herein.

Resources and computational strategies to advance small molecule SARS-CoV-2 discovery: Lessons from the pandemic and preparing for future health crises

There is an urgent need to identify new therapies that prevent SARS-CoV-2 infection and improve the outcome of COVID-19 patients. This pandemic has thus spurred intensive research in most scientific areas and in a short period of time, several vaccines have been developed. But, while the race to find vaccines for COVID-19 has dominated the headlines, other types of therapeutic agents are being developed. In this mini-review, we report several databases and online tools that could assist the discovery of anti-SARS-CoV-2 small chemical compounds and peptides. We then give examples of studies that combined in silico and in vitro screening, either for drug repositioning purposes or to search for novel bioactive compounds. Finally, we question the overall lack of discussion and plan observed in academic research in many countries during this crisis and suggest that there is room for improvement.

Carbonic Anhydrases: New Perspectives on Protein Functional Role and Inhibition in Helicobacter pylori

Our understanding of the function of bacterial carbonic anhydrases (CAs, EC 4.2.1.1) has increased significantly in the last years. CAs are metalloenzymes able to modulate CO₂, HCO₃ ^- and H⁺ concentration through their crucial role in catalysis of reversible CO₂ hydration (CO₂ + H₂O ⇄ HCO₃ ^- + H⁺). In all living organisms, CA activity is linked to physiological processes, such as those related to the transport and supply of CO₂ or HCO₃ ^-, pH homeostasis, secretion of electrolytes, biosynthetic processes and photosynthesis. These important processes cannot be ensured by the very low rate of the non-catalyzed reaction of CO₂ hydration. It has been recently shown that CAs are important biomolecules for many bacteria involved in human infections, such as Vibrio cholerae, Brucella suis, Salmonella enterica, Pseudomonas aeruginosa, and Helicobacter pylori. In these species, CA activity promotes microorganism growth and adaptation in the host, or modulates bacterial toxin production and virulence. In this review, recent literature in this research field and some of the above-mentioned issues are discussed, namely: (i) the implication of CAs from bacterial pathogens in determining the microorganism growth and virulence; (ii) the druggability of these enzymes using classical CA inhibitors (CAIs) of the sulfonamide-type as examples; (iii) the role played by Helicobacter pylori CAs in the acid tolerance/adaptation of the microbe within the human abdomen; (iv) the role of CAs played in the outer membrane vesicles spawned by H. pylori in its planktonic and biofilm phenotypes; (v) the possibility of using H. pylori CAIs in combination with probiotic strains as a novel anti-ulcer treatment approach. The latter approach may represent an innovative and successful strategy to fight gastric infections in the era of increasing resistance of pathogenic bacteria to classical antibiotics.

Combining structure and genomics to understand antimicrobial resistance

Antimicrobials against bacterial, viral and parasitic pathogens have transformed human and animal health. Nevertheless, their widespread use (and misuse) has led to the emergence of antimicrobial resistance (AMR) which poses a potentially catastrophic threat to public health and animal husbandry. There are several routes, both intrinsic and acquired, by which AMR can develop. One major route is through non-synonymous single nucleotide polymorphisms (nsSNPs) in coding regions. Large scale genomic studies using high-throughput sequencing data have provided powerful new ways to rapidly detect and respond to such genetic mutations linked to AMR. However, these studies are limited in their mechanistic insight. Computational tools can rapidly and inexpensively evaluate the effect of mutations on protein function and evolution. Subsequent insights can then inform experimental studies, and direct existing or new computational methods. Here we review a range of sequence and structure-based computational tools, focussing on tools successfully used to investigate mutational effect on drug targets in clinically important pathogens, particularly Mycobacterium tuberculosis. Combining genomic results with the biophysical effects of mutations can help reveal the molecular basis and consequences of resistance development. Furthermore, we summarise how the application of such a mechanistic understanding of drug resistance can be applied to limit the impact of AMR.

Genomics, Computational Biology and Drug Discovery for Mycobacterial Infections: Fighting the Emergence of Resistance

Tuberculosis (TB) and leprosy are mycobacterial infections caused by Mycobacterium tuberculosis and Mycobacterium leprae respectively. These diseases continue to be endemic in developing countries where the cost of new medicines presents major challenges. The situation is further exacerbated by the emergence of resistance to many front-line antibiotics. A priority now is to design new antimycobacterials that are not only effective in combatting the diseases but are also less likely to give rise to resistance. In both these respects understanding the structure of drug targets in M. tuberculosis and M. leprae is crucial. In this review we describe structure-guided approaches to understanding the impacts of mutations that give rise to antimycobacterial resistance and the use of this information in the design of new medicines.

Prioritisation of potential drug targets against Bartonella bacilliformis by an integrative in-silico approach

BACKGROUND Carrion's disease (CD) is a neglected biphasic illness caused by Bartonella bacilliformis, a Gram-negative bacteria found in the Andean valleys. The spread of resistant strains underlines the need for novel antimicrobials against B. bacilliformis and related bacterial pathogens. OBJECTIVE The main aim of this study was to integrate genomic-scale data to shortlist a set of proteins that could serve as attractive targets for new antimicrobial discovery to combat B. bacilliformis. METHODS We performed a multidimensional genomic scale analysis of potential and relevant targets which includes structural druggability, metabolic analysis and essentiality criteria to select proteins with attractive features for drug discovery. FINDINGS We shortlisted seventeen relevant proteins to develop new drugs against the causative agent of Carrion's disease. Particularly, the protein products of fabI, folA, aroA, trmFO, uppP and murE genes, meet an important number of desirable features that make them attractive targets for new drug development. This data compendium is freely available as a web server (http://target.sbg.qb.fcen.uba.ar/). MAIN CONCLUSION This work represents an effort to reduce the costs in the first phases of B. bacilliformis drug discovery.

Prioritization of Mur family drug targets against A. baumannii and identification of their homologous proteins through molecular phylogeny, primary sequence, and structural analysis

Background

The World Health Organization (WHO) report stated that Acinetobacter baumannii had been classified as one of the most important pathogenic bacteria causing nosocomial infection in hospital patients due to multi-drug resistance (MDR). It is vital to find out new bacterial drug targets and annotated their structure and function for the exploration of new anti-bacterial agents. The present study utilized a systematic route to prioritize the potential drug targets that belong to Mur family of Acinetobacter baumannii and identify their homologous proteins using a computational approach such as sequence similarity search, multiple sequence alignment, phylogenetic analysis, protein sequence, and protein structure analysis.

Results

From the results of protein sequence analysis of eight Mur family proteins, they divided into three main enzymatic classes namely transferases (MurG, MurA and MraY), ligases (MurC, MurD, MurE, and MurF), and oxidoreductase (MurB). Based on the results of intra-comparative protein sequence analysis and enzymatic classification, we have chosen MurB, MurE, and MurG as the prioritized drug targets from A. baumannii and subjected them for further detailed studies of inter-species comparison. This inter-species comparison help us to explore the sequential and structural properties of homologous proteins in other species and hence, opens a gateway for new target identification and using common inhibitor for different bacterial species caused by various diseases. The pairwise sequence alignment results between A. baumannii’s MurB with A. calcoaceticus’s MurB, A. baumannii’s MurE with A. seifertii’s MurE, and A. baumannii’s MurG with A. pittii’s MurG showed that every group of the proteins are highly similar with each other and they showed sequence identity of 95.7% and sequence similarity of 97.2%.

Conclusion

Together with the results of secondary and three-dimensional structure predictions explained that three selected proteins (MurB, MurE, and MurG) from A. baumannii and their related proteins (AcMurB, AsMurE, and ApMurG) belong to mixed αβ class and they are very similar.

The Effect of Substituted Benzene-Sulfonamides and Clinically Licensed Drugs on the Catalytic Activity of CynT2, a Carbonic Anhydrase Crucial for Escherichia coli Life Cycle

Proteins are relevant antimicrobial drug targets, and among them, enzymes represent a significant group, since most of them catalyze reactions essential for supporting the central metabolism, or are necessary for the pathogen vitality. Genomic exploration of pathogenic and non-pathogenic microorganisms has revealed genes encoding for a superfamily of metalloenzymes, known as carbonic anhydrases (CAs, EC 4.2.1.1). CAs catalyze the physiologically crucial reversible reaction of the carbon dioxide hydration to bicarbonate and protons. Herein, we investigated the sulfonamide inhibition profile of the recombinant β-CA (CynT2) identified in the genome of the Gram-negative bacterium Escherichia coli. This biocatalyst is indispensable for the growth of the microbe at atmospheric pCO₂. Surprisingly, this enzyme has not been investigated for its inhibition with any class of CA inhibitors. Here, we show that CynT2 was strongly inhibited by some substituted benzene-sulfonamides and the clinically used inhibitor sulpiride (K_Is in the range of 82–97 nM). This study may be relevant for identifying novel CA inhibitors, as well as for another essential part of the drug discovery pipeline, such as the structure–activity relationship for this class of enzyme inhibitors.

A chemical inhibitor of heat shock protein 78 (HSP78) from Leishmania donovani represents a potential antileishmanial drug candidate

The emergence of resistance to available antileishmanial drugs advocates identification of new drug targets and their inhibitors for visceral leishmaniasis. Here, we identified Leishmania donovani heat shock protein 78 (LdHSP78), a putative caseinolytic protease, as important for parasite infection of host macrophages and a potential therapeutic target. Enrichment of LdHSP78 in infected humans, hamsters, and parasite amastigotes suggested its importance for disease persistence. Heterozygous knockouts of L. donovani HSP78 (LdHSP78+/-) and Leishmania mexicana HSP78 (LmxHSP78+/-) were generated using a flanking UTR-based multifragment ligation strategy and the CRISPR-Cas9 technique, respectively to investigate the significance of HSP78 for disease manifestation. The LdHSP78+/- parasite burden was dramatically reduced in both murine bone marrow-derived macrophages and hamsters, in association with enrichment of proinflammatory cytokines and NO. This finding implies that LdHSP78+/- parasites cannot suppress immune activation and escape NO-mediated toxicity in macrophages. Furthermore, phosphorylation of the mitogen-activated protein kinase p38 was enhanced and phosphorylation of extracellular signal-regulated kinase 1/2 was decreased in cells infected with LdHSP78+/- parasites, compared with WT parasites. Virulence of the LdHSP78+/- strain was restored by episomal addition of the LdHSP78 gene. Finally, using high-throughput virtual screening, we identified P ¹,P ⁵-di(adenosine-5')-pentaphosphate (Ap5A) ammonium salt as an LdHSP78 inhibitor. It selectively induced amastigote death at doses similar to amphotericin B doses, while exhibiting much less cytotoxicity to healthy macrophages than amphotericin B. In summary, using both a genetic knockout approach and pharmacological inhibition, we establish LdHSP78 as a drug target and Ap5A as a potential lead for improved antileishmanial agents.

Computational approaches for drug discovery against trypanosomatid-caused diseases

During three decades, only about 20 new drugs have been developed for malaria, tuberculosis and all neglected tropical diseases (NTDs). This critical situation was reached because NTDs represent only 10% of health research investments; however, they comprise about 90% of the global disease burden. Computational simulations applied in virtual screening (VS) strategies are very efficient tools to identify pharmacologically active compounds or new indications for drugs already administered for other diseases. One of the advantages of this approach is the low time-consuming and low-budget first stage, which filters for testing experimentally a group of candidate compounds with high chances of binding to the target and present trypanocidal activity. In this work, we review the most common VS strategies that have been used for the identification of new drugs with special emphasis on those applied to trypanosomiasis and leishmaniasis. Computational simulations based on the selected protein targets or their ligands are explained, including the method selection criteria, examples of successful VS campaigns applied to NTDs, a list of validated molecular targets for drug development and repositioned drugs for trypanosomatid-caused diseases. Thereby, here we present the state-of-the-art of VS and drug repurposing to conclude pointing out the future perspectives in the field.

The antischistosomal potential of GSK-J4, an H3K27 demethylase inhibitor: insights from molecular modeling, transcriptomics and in vitro assays

Background

Schistosomiasis chemotherapy is largely based on praziquantel (PZQ). Although PZQ is very safe and tolerable, it does not prevent reinfection and emerging resistance is a primary concern. Recent studies have shown that the targeting of epigenetic machinery in Schistosoma mansoni may result in severe alterations in parasite development, leading to death. This new route for drug discovery in schistosomiasis has focused on classes of histone deacetylases (HDACs) and histone acetyltransferases (HATs) as epigenetic drug targets. Schistosoma histone demethylases also seem to be important in the transition of cercariae into schistosomula, as well as sexual differentiation in adult worms.

Methods

The Target-Pathogen database and molecular docking assays were used to prioritize the druggability of S. mansoni histone demethylases. The transcription profile of Smp_03400 was re-analyzed using available databases. The effect of GSK-J4 inhibitor in schistosomula and adult worms’ motility/viability/oviposition was assessed by in vitro assays. Ultrastructural analysis was performed on adult worms exposed to GSK-J4 by scanning electron microscopy, while internal structures and muscle fiber integrity was investigated by confocal microscopy after Langeronʼs carmine or phalloidin staining.

Results

The present evaluation of the potential druggability of 14 annotated S. mansoni demethylase enzymes identified the S. mansoni ortholog of human KDM6A/UTX (Smp_034000) as the most suitable druggable target. In silico analysis and molecular modeling indicated the potential for cofactor displacement by the chemical probe GSK-J4. Our re-analysis of transcriptomic data revealed that Smp_034000 expression peaks at 24 h in newly transformed schistosomula and 5-week-old adult worms. Moreover, this gene was highly expressed in the testes of mature male worms compared to the rest of the parasite body. In in vitro schistosome cultures, treatment with GSK-J4 produced striking effects on schistosomula mortality and adult worm motility and mortality, as well as egg oviposition, in a dose- and time-dependent manner. Unexpectedly, western blot assays did not demonstrate overall modulation of H3K27me3 levels in response to GSK-J4. Confocal and scanning electron microscopy revealed the loss of original features in muscle fibers and alterations in cell-cell contact following GSK-J4 treatment.

Conclusions

GSK-J4 presents promising potential for antischistosomal control; however, the underlying mechanisms warrant further investigation.

Methylobacterium sp. 2A Is a Plant Growth-Promoting Rhizobacteria That Has the Potential to Improve Potato Crop Yield Under Adverse Conditions

A Gram-negative pink-pigmented bacillus (named 2A) was isolated from Solanum tuberosum L. cv. Desirée plants that were strikingly more developed, presented increased root hair density, and higher biomass than other potato lines of the same age. The 16S ribosomal DNA sequence, used for comparative gene sequence analysis, indicated that strain 2A belongs to the genus Methylobacterium. Nucleotide identity between Methylobacterium sp. 2A sequenced genome and the rest of the species that belong to the genus suggested that this species has not been described so far. In vitro, potato plants inoculated with Methylobacterium sp. 2A had a better performance when grown under 50 mM NaCl or when infected with Phytophthora infestans. We inoculated Methylobacterium sp. 2A in Arabidopsis thaliana roots and exposed these plants to salt stress (75 mM NaCl). Methylobacterium sp. 2A-inoculated plants, grown in control or salt stress conditions, displayed a higher density of lateral roots (p < 0.05) compared to noninoculated plants. Moreover, under salt stress, they presented a higher number of leaves and larger rosette diameter. In dual confrontation assays, Methylobacterium sp. 2A displayed biocontrol activity against P. infestans, Botrytis cinerea, and Fusarium graminearum, but not against Rhizoctonia solani, and Pythium dissotocum. In addition, we observed that Methylobacterium sp. 2A diminished the size of necrotic lesions and reduced chlorosis when greenhouse potato plants were infected with P. infestans. Methylobacterium sp. 2A produces indole acetic acid, solubilizes mineral phosphate and is able to grow in a N2 free medium. Whole-genome sequencing revealed metabolic pathways associated with its plant growth promoter capacity. Our results suggest that Methylobacterium sp. 2A is a plant growth-promoting rhizobacteria (PGPR) that can alleviate salt stress, and restricts P. infestans infection in potato plants, emerging as a potential strategy to improve crop management.

Core regulon of the global anaerobic regulator Anr targets central metabolism functions in Pseudomonas species

A comparative genome analysis of the global anaerobic regulator Anr regulon in five species of Pseudomonas with different life style was performed. Expression of this regulator was detected in all analyzed Pseudomonas. The predicted Anr regulon (pan-regulon) consisted of 253 genes. However, only 11 Anr-boxes located upstream of qor/hemF, hemN, cioA/PA3931, azu, rpsL, gltP, orthologous to PA2867, cspD, tyrZ, slyD and oprG, were common to all species. Whole genome in silico prediction of metabolic pathways identified genes belonging to heme biosynthesis, cytochromes and Entner-Doudoroff pathway as members of Anr regulon in all strains. Extending genome analysis to 28 Pseudomonas spp. spanning all phylogenetic groups showed Anr-boxes conservation in genes related to these functions. When present, genes related to anaerobic metabolism were predicted to hold Anr-boxes. Focused on the genomes of eight P. aeruginosa isolates of diverse origins, we observed a conserved regulon, sharing nearly 80% of the genes, indicating its key role in this opportunistic pathogen. The results suggest that the core Anr regulon comprises genes involved in central metabolism and aerobic electron transport chain, whereas those genes related to anaerobic metabolism and other functions constitute the accessory Anr-regulon, thereby differentially contributing to the ecological fitness of each Pseudomonas species.

Exploring lectin-like activity of the S-layer protein of Lactobacillus acidophilus ATCC 4356

The surface layer (S-layer) protein of Lactobacillus acidophilus is a crystalline array of self-assembling, proteinaceous subunits non-covalently bound to the outmost bacterial cell wall envelope and is involved in the adherence of bacteria to host cells. We have previously described that the S-layer protein of L. acidophilus possesses anti-viral and anti-bacterial properties. In this work, we extracted and purified S-layer proteins from L. acidophilus ATCC 4356 cells to study their interaction with cell wall components from prokaryotic (i.e., peptidoglycan and lipoteichoic acids) and eukaryotic origin (i.e., mucin and chitin), as well as with viruses, bacteria, yeast, and blood cells. Using chimeric S-layer fused to green fluorescent protein (GFP) from different parts of the protein, we analyzed their binding capacity. Our results show that the C-terminal part of the S-layer protein presents lectin-like activity, interacting with different glycoepitopes. We further demonstrate that lipoteichoic acid (LTA) serves as an anchor for the S-layer protein. Finally, a structure for the C-terminal part of S-layer and possible binding sites were predicted by a homology-based model.

Discovery and Genetic Validation of Chemotherapeutic Targets for Chagas' Disease

There is an urgent need to develop new treatments for Chagas' disease. To identify drug targets, it is important to understand the basic biology of Trypanosoma cruzi, in particular with respect to the biological pathways or proteins that are essential for its survival within the host. This review provides a streamlined approach for identifying drug targets using freely available chemogenetic databases and outlines the relevant characteristics of an ideal chemotherapeutic target. Among those are their essentiality, druggability, availability of structural information, and selectivity. At the moment only 16 genes have been found as essential by gene disruption in T. cruzi. At the TDR Targets database, a chemogenomics resource for neglected diseases, information about published structures for these genes was only found for three of these genes, and annotation of validated inhibitors was found in two. These inhibitors have activity against the parasitic stages present in the host. We then analyzed three of the pathways that are considered promising in the search for new targets: (1) Ergosterol biosynthesis, (2) Resistance to oxidative stress, (3) Synthesis of surface glycoconjugates. We have annotated all the genes that participate in them, identified those that are considered as druggable, and incorporated evidence from either Trypanosoma brucei, and Leishmania spp. that supports the hypothesis that these pathways are essential for T. cruzi survival.

An integrative, multi-omics approach towards the prioritization of Klebsiella pneumoniae drug targets

Klebsiella pneumoniae (Kp) is a globally disseminated opportunistic pathogen that can cause life-threatening infections. It has been found as the culprit of many infection outbreaks in hospital environments, being particularly aggressive towards newborns and adults under intensive care. Many Kp strains produce extended-spectrum β-lactamases, enzymes that promote resistance against antibiotics used to fight these infections. The presence of other resistance determinants leading to multidrug-resistance also limit therapeutic options, and the use of 'last-resort' drugs, such as polymyxins, is not uncommon. The global emergence and spread of resistant strains underline the need for novel antimicrobials against Kp and related bacterial pathogens. To tackle this great challenge, we generated multiple layers of 'omics' data related to Kp and prioritized proteins that could serve as attractive targets for antimicrobial development. Genomics, transcriptomics, structuromic and metabolic information were integrated in order to prioritize candidate targets, and this data compendium is freely available as a web server. Twenty-nine proteins with desirable characteristics from a drug development perspective were shortlisted, which participate in important processes such as lipid synthesis, cofactor production, and core metabolism. Collectively, our results point towards novel targets for the control of Kp and related bacterial pathogens.

Draft Genome Sequence of Lactobacillus helveticus ATCC 12046

Lactobacillus helveticus is a lactic acid bacterium used traditionally in the dairy industry, especially in the manufacture of cheeses. We present here the 2,141,841-bp draft genome sequence of L. helveticus strain ATCC 12046, a potential starter strain for improving cheese production.