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Background:Clostridioides difficile (CD) is an enteric multi-drug resistant pathogenic bacterium. CD-associated infections are the leading cause of nosocomial diarrhea that can further lead to pseudomembranous colitis, toxic mega-colon or sepsis with greater mortality and morbidity risks. CD infection possesses higher rates of recurrence due to its greater resistance to antibiotics. Considering its higher rates of recurrence, it has become a major burden on healthcare facilities. Therefore, there is a dire need to identify novel drug targets to combat antibiotic resistance of Clostridioides difficile.Objective:To identify and propose new and novel drug targets against the Clostridioides difficile.Methods:In the current study, a computational subtractive genomics approach was applied to obtain a set of potential drug targets that exist in the multi-drug resistant strain of Clostridioides difficile. Here, the uncharacterized proteins were studied as potential drug targets. The methodology involved several bioinformatics databases and tools. The druggable proteins sequences were retrieved based on non-homology with host proteome and essentiality for the survival of the pathogen. The uncharacterized proteins were functionally characterized using different computational tools, and sub-cellular localization was also predicted. The metabolic pathways were analyzed using the KEGG database. Eventually, the druggable proteome has been fetched using sequence similarity with the already available drug targets present in the DrugBank database. These druggable proteins were further explored for the structural details to identify drug candidates.Results :A priority list of potential drug targets was provided with the help of the applied method on the complete proteome set of the C. difficile. Moreover, the drug-like compounds have been screened against the potential drug targets to prioritize potential drug candidates. To facilitate the need for drug targets and therapies, the study proposed five potential protein drug targets, out of which three proposed drug targets were subjected to homology modeling to explore their structural and functional activitiesConclusion:In conclusion, we proposed three unique, unexplored drug targets against C. difficile. The structure-based methods were applied and resulted in a list of top-scoring compounds as potential inhibitors to proposed drug targets.

BackgroundOne of the major issues in the fight against infectious diseases is the notable increase in multiple drug resistance in pathogenic species. For that reason, newly acquired high-throughput data on virulent microbial agents attract the attention of many researchers seeking potential new drug targets. Many approaches have been used to evaluate proteins from infectious pathogens, including, but not limited to, similarity analysis, reverse docking, statistical 3D structure analysis, machine learning, topological properties of interaction networks or a combination of the aforementioned methods. From a biological perspective, most essential proteins (knockout lethal for bacteria) or highly conserved proteins (broad spectrum activity) are potential drug targets. Ribosomal proteins comprise such an example. Many of them are well-known drug targets in bacteria. It is intuitive that we should learn from nature how to design good drugs. Firstly, known antibiotics are mainly originating from natural products of microorganisms targeting other microorganisms. Secondly, paleontological data suggests that antibiotics have been used by microorganisms for million years. Thus, we have hypothesized that good drug targets are evolutionary constrained and are subject of evolutionary selection. This means that mutations in such proteins are deleterious and removed by selection, which makes them less susceptible to random development of resistance. Analysis of the speed of evolution seems to be good approach to test this hypothesis.ResultsIn this study we show that pN/pS ratio of genes coding for known drug targets is significantly lower than the genome average and also lower than that for essential genes identified by experimental methods. Similar results are observed in the case of dN/dS analysis. Both analyzes suggest that drug targets tend to evolve slowly and that the rate of evolution is a better predictor of drugability than essentiality.ConclusionsEvolutionary rate can be used to score and find potential drug targets. The results presented here may become a useful addition to a repertoire of drug target prediction methods. As a proof of concept, we analyzed GO enrichment among the slowest evolving genes. These may become the starting point in the search for antibiotics with a novel mechanism.

Identification of novel drug targets is a critical step in drug development. Many recent studies have produced multiple types of data, which provides an opportunity to mine the relationships among them to predict drug targets. In this study, we present a novel integrative approach that combines ontology reasoning with network-assisted gene ranking to predict new drug targets. We utilized colorectal cancer (CRC) as a proof-of-concept use case to illustrate the approach. Starting from FDA-approved CRC drugs and the relationships among disease, drug, gene, pathway, and SNP in an ontology representing PharmGKB data, we inferred 113 potential CRC drug targets. We further prioritized these genes based on their relationships with CRC disease genes in the context of human protein–protein interaction networks. Thus, among the 113 potential drug targets, 15 were selected as the promising drug targets, including some genes that are supported by previous studies. Among them, EGFR, TOP1 and VEGFA are known targets of FDA-approved drugs. Additionally, CCND1 (cyclin D1), and PTGS2 (prostaglandin-endoperoxide synthase 2) have reported to be relevant to CRC or as potential drug targets based on the literature search. These results indicate that our approach is promising for drug target prediction for CRC treatment, which might be useful for other cancer therapeutics.

Prioritization of potential drug targets against P. aeruginosa by core proteomic analysis using computational subtractive genomics and Protein-Protein interaction network

Neisseria gonorrhoeae is responsible for causing gonorrhea, one of the most common sexually transmitted diseases prevailing globally. Although extensive researches are in progress in order to control the transmission of the disease and to develop drug(s) against the pathogen, till date no effective vaccine or specific drug could be developed and only antibiotic treatment is in use. Perhaps, due to excess use of antibiotics, several resistant strains have been found. In the present study, metabolic pathways-related candidate drug and vaccine targets have been identified in N. gonorrhoeae virulent strain FA 1090 using an in silico subtractive genomics approach. 106 putative drug targets out of 537 essential genes have been predicted. 67 cytoplasmic and 9 membrane enzymes, along with 10 membrane transporters are found to be the potential drug targets from the host-pathogen common metabolic pathways. Among these targets, competence lipoproteins (NGO0277) and cysW have been identified as candidate vaccine targets. 20 drug targets have been identified from pathogen specific unique metabolic pathways. Out of these, 6 enzymes are involved in dual metabolic pathways and 2 are expressed in cell wall and fimbrium. These gonococci-specific proteins are expected to be better possible drug targets. Screening of the functional inhibitors against these novel targets may result in discovery of novel therapeutic compounds that can be effective against antibiotic resistant strains.

Mycobacterium tuberculosis, the causative agent of tuberculosis, has been a serious threat to public health. The recent emergence of extreme drug-resistant strains further worsened the situation and required more serious efforts to find a better cure for TB. Availability of the complete genome map of various Mycobacterium tuberculosis strains serves a basis to propose new therapeutic targets against Mycobacterium tuberculosis. The present study aimed to identify and characterize potential and novel drug target against Mycobacterium tuberculosis by using an in silico approach. The study consisted of three phases. In phase I, subtractive/comparative genomics was performed on genomic data of 17 strains of Mycobacterium tuberculosis comprised of 66,988 protein sequences. The analysis resulted in three identical hypothetical proteins of distinct origin. The shortlisted sequences were non-homologous to the host, a prerequisite characteristic of potential drug target. One of the sequences, i.e., WP_003901628.1 (the locus tag name is CFBR_RS17985) from the CDC5180 strain was further subjected to other bioinformatics methods in phase II. In phase II, the shortlisted protein sequence was qualitatively characterized for subcellular localization, functional family prediction and evolutionary relationships. The predicted subcellular localization of the query protein was found in cytoplasmic region. The functional family classification resulted in classifying the protein in transferase superfamily. Finally, in phase III of the study, the structure-based methods (i.e., homology modeling and docking) were performed to build the three-dimensional (3D) structure and to predict the putative binding site. The PDB-ID 3DR4 was found to be a suitable template having 30.1% sequence identity. The binding site of modeled protein was deciphered with DoGSite scorer tool. Later on, the ProBis tool was used to probe structurally similar binding sites in Protein Data Bank. Subsequently, the co-crystal ligands of the Protein Data Bank structures (prioritized by high-rank Z scores) were extracted and cross-docked into the binding site of the modeled protein. The cross-docking results revealed two ligands, i.e., 4′-deoxy-4′-aminopyridoxal-5′-phosphate and OG1 from two Protein Data Bank structures, i.e., 1MDO and 4K2M as best docked with RMSDs 2.8 and 2.5 A, respectively. It is inferred from the protein structure that the identified protein is alanine-rich with a PI < 7. Current study convincingly proposed that the shortlisted hypothetical protein (WP_003901628.1) is a potential drug target against which new drug candidates could be designed in a hope to cure tuberculosis.

Background: Clostridium tetani are rod-like, anaerobic types of pathogenic bacteria of the genus Clostridium. It is Gram-positive in nature and appears as a tennis racket or drumsticks on staining with the dye. Tetanus is a neuromuscular disease wherein the Clostridium tetani exotoxin produces muscle fits in the host. Tetanus is the second leading cause of worldwide deaths occurring from the family of immunization-preventable diseases. Methods: In this research, subtractive proteome analysis of C. tetani was performed to identify putative drug targets. The proteins were subjected to blast analysis against Homo sapiens to exclude homologous proteins. The database of Essential Genes was used to determine the essential proteins of the pathogen. These basic proteins were additionally analyzed to anticipate the corresponding metabolic pathways. Results: Cellular localization analysis was carried out to determine the possibility of the protein presence in the outer membrane. The study has recognized 29 essential genes and 20 unique pathways of 2314 proteins as potential drug targets. There are 29 essential proteins, out of which, 3 membrane proteins were also identified as putative drug targets. Conclusion: Virtual screening in contrast to these proteins can be valuable in the identification of novel clinical compounds for the C. tetani infections in Homo sapiens.

The identification of essential cellular genes is critical for validating drug targets

Computational screening of potential drug targets for pathogens causing bacterial pneumonia

Background: In our day-to-day life, we are facing many dreadful diseases caused by many infectious pathogens. These pathogens invade the living organisms (host) and lethally damaging them. These dreadful pathogens were also be used as bioweapons. Among them, Clostridium perfringens is taken for the study. Clostridium perfringens is an anaerobic, rod shaped, gram positive bacteria capable of forming spores. It is prevalent in the environment and in the intestine of humans and other animals. It is the causative agent for a wide range of diseases including food borne diseases, gas gangrene and flesh eating disease called necrotizing fasciitis. C. perfringens is commonly found on raw meat and poultry that espouse to grow in conditions with very little or no oxygen, and under ideal conditions can multiply very rapidly. These conditions are occasionally lethal due to the substantial number of toxins such as alpha toxin, beta toxin, epsilon toxin and iota toxin produced by C. perfringens. It is significantly important to analyze the Drug targets of the pathogen in order to destroy them. Objective: The present work aims in identifying potential drug targets in C. perfringens through metabolic pathway analysis. Method: Primarily, the metabolic pathways of the host and pathogen are compared to identify unique pathways in the bacteria. Among the enzymes that catalyze unique metabolic pathways, the essential ones for the survival of the pathogen are identified. The druggability of the essential enzymes are predicted through identification of its sub cellular localization and other druggable parameters. Results: The comparative metabolic pathway analysis result shows that, among the 98 metabolic pathways of C.perfringens, 25 pathways were unique that they did not have a counterpart with Human. There were 113 enzymes involved in these unique pathways. The NCBI’s protein Blast search against human was done to identify the non-homologous proteins. There were 93 non-homologous proteins. Among the 93 non-homologous proteins, 47 proteins were found to be essential. Based on their sub-cellular localization, 32 proteins were identified as potential drug targets and 15 are probable vaccine candidates. Conclusion: The present work which started with 25 different pathways with more than a hundred different enzymes, resulted in the identification of 32 putative drug targets against C.perfringens infection. All these 32 identified targets did not have any human homolog and are highly essential for the survival of the organism. They were concluded as potential drug targets. Designing of compounds to inhibit these enzymes would be successful for treating the life threatening infections caused by this pathogen.

Evaluation of clan CD C11 peptidase PNT1 and other Leishmania mexicana cysteine peptidases as potential drug targets

Bacterial enteric infections resulting in diarrhea, dysentery, or enteric fever constitute a huge public health problem, with more than a billion episodes of disease annually in developing and developed countries. In this study, the deadly agent of hemorrhagic diarrhea and hemolytic uremic syndrome, Escherichia coli O157:H7 was investigated with extensive computational approaches aimed at identifying novel and broad-spectrum antibiotic targets. A systematic in silico workflow consisting of comparative genomics, metabolic pathways analysis, and additional drug prioritizing parameters was used to identify novel drug targets that were essential for the pathogen’s survival but absent in its human host. Comparative genomic analysis of Kyoto Encyclopedia of Genes and Genomes annotated metabolic pathways identified 350 putative target proteins in E. coli O157:H7 which showed no similarity to human proteins. Further bio-informatic approaches including prediction of subcellular localization, calculation of molecular weight, and web-based investigation of 3D structural characteristics greatly aided in filtering the potential drug targets from 350 to 120. Ultimately, 44 non-homologous essential proteins of E. coli O157:H7 were prioritized and proved to have the eligibility to become novel broad-spectrum antibiotic targets and DNA polymerase III alpha (dnaE) was the top-ranked among these targets. Moreover, druggability of each of the identified drug targets was evaluated by the DrugBank database. In addition, 3D structure of the dnaE was modeled and explored further for in silico docking with ligands having potential druggability. Finally, we confirmed that the compounds N-coeleneterazine and N-(1,4-dihydro-5H-tetrazol-5-ylidene)-9-oxo-9H-xanthene-2-sulfon-amide were the most suitable ligands of dnaE and hence proposed as the potential inhibitors of this target protein. The results of this study could facilitate the discovery and release of new and effective drugs against E. coli O157:H7 and other deadly human bacterial pathogens.

Acinetobacter baumannii, a gram negative bacteria, has emerged as a critical pathogen responsible for nosocomial and other infections. A. baumannii exhibits resistance to a variety of antibiotic classes, emphasizing that new therapeutic targets are urgently needed. In A. baumannii, ATCC 179778, 458 genes have been identified as essential genes, indispensable for growth and survival of the pathogen. The functions of 47 proteins encoded by A.baumannii essential genes were found to be hypothetical and thus referred as essential hypothetical proteins (EHPs). The present study aims to carry out functional characterization of EHPs using bioinformatics tools/databases. Evaluation of physicochemical parameters, homology search against known proteins, domain analysis, subcellular localization analysis, 3D structure prediction and virulence prediction assisted us to characterize EHPs. They belong to different functional classes like enzymes, binding proteins, helicases, transporters, miscellaneous proteins and virulence factors. Around 47% of EHPs were enzymes. A group of EHPs (17.6%) were predicted as virulence factors. Proteins present in the pathogen but absent in the host were identified using host non-homology analysis. Further druggability analysis examined the druggable property of the proteins. Of 34, 27 essential pathogen-specific proteins which could serve as potential novel drug and vaccine targets. Druggability analysis was performed to examined the druggable property of the proteins. One target was found to be druggable and others were novel targets. The study's findings might assist in the development of new drugs for the treatment of Acinetobacter baumannii infections.

Identification of essential genes is critical to understanding the physiology of a species, proposing novel drug targets and uncovering minimal gene sets required for life. Although essential gene sets of several organisms have been determined using large-scale mutagenesis techniques, systematic studies addressing their conservation, genomic context and functions remain scant. Here we integrate 17 essential gene sets from genome-wide in vitro screenings and three gene collections required for growth in vivo, encompassing 15 Bacteria and one Archaea. We refine and generalize important theories proposed using Escherichia coli. Essential genes are typically monogenic and more conserved than nonessential genes. Genes required in vivo are less conserved than those essential in vitro, suggesting that more divergent strategies are deployed when the organism is stressed by the host immune system and unstable nutrient availability. We identified essential analogous pathways that would probably be missed by orthology-based essentiality prediction strategies. For example, Streptococcus sanguinis carries horizontally transferred isoprenoid biosynthesis genes that are widespread in Archaea. Genes specifically essential in Mycobacterium tuberculosis and Burkholderia pseudomallei are reported as potential drug targets. Moreover, essential genes are not only preferentially located in operons, but also occupy the first position therein, supporting the influence of their regulatory regions in driving transcription of whole operons. Finally, these important genomic features are shared between Bacteria and at least one Archaea, suggesting that high order properties of gene essentiality and genome architecture were probably present in the last universal common ancestor or evolved independently in the prokaryotic domains.

Background: Phosgene is one of the highly produced industrial gases and is an essential intermediate in polymer, pharmaceutical, and metallurgy synthesis. However, phosgene is highly toxic when inhaled. Phosgene inhalation causes delayed onset of symptoms starting 8 hours post-inhalation. While symptoms are consistent with acute respiratory distress syndrome (ARDS), pulmonary edema is the pathognomonic symptom. Due to its high propensity for toxicity, it was deployed as a chemical warfare agent during World War I. Currently, there are no mechanistic-based antidotes for treating phosgene inhalation injuries. The treatment is mainly supportive and symptomatic. As the medical countermeasures are approved through the FDA's animal rule, there is a knowledge gap in non-rodent animal models that recapitulate human phosgene inhalation injuries and detailed proteomic changes that happen in the lungs after phosgene inhalation. Methods: Sedated domestic Yorkshire swine were exposed to phosgene (40 ppm for 20 minutes) through a nose cone. Animals were recovered from sedation and observed in their home pens frequently. Animals were re-sedated at 8 or 24 hours post-phosgene exposure. Oxygenation, respiratory physiological, and pulmonary function testing parameters were recorded. At the end of the study, animals were euthanized and lung tissues were collected. Lung tissues were processed for unbiased global proteomics using previously established mass spectrometry methods and multiplex protein array assays were also performed to identify potential drug biomarkers and targets. Results: Phosgene inhalation resulted in hypoxemia and worsening of respiratory physiological parameters such as decreased compliance dynamics, and elevated airway resistance and peak inspiratory pressure. Pulmonary function testing showed decreased tolerance to increasing concentrations of nebulized methacholine concentrations. Histopathology revealed neutrophilic alveolitis, hyaline membranes, and increased septal thickness in consistent with ARDS. Unbiased global proteomics studies in phosgene-exposed lung tissues revealed &amp;gt;8,000 protein groups with good precision and accuracy based on quality control pool samples and internal spike-in standards. Prominent among the differentially-expressed proteins were plasma-derived and acute-phase proteins, and TGFβ activation, which were increased upon phosgene exposure. Proteins that were significantly decreased include putative cilia-expressed proteins and collagen isoforms. Conclusions: We established an acute porcine model that recapitulates human phosgene inhalation injuries and that can be utilized for testing potential medical countermeasures. Differentially expressed proteome changes may serve as potential diagnostic biomarkers and drug targets. Additional studies are warranted to develop and study extended observation porcine phosgene models.