in silico analyses of metabolic pathway and protein interaction network for identification of next gen therapeutic targets in Chlamydophila pneumoniae

Chlamydophila pneumoniae, the causative agent of chronic obstructive pulmonary disease (COPD), is presently the fifth mortality causing chronic disease in the world. The understanding of disease and treatment options are limited represents a severe concern and a need for better therapeutics. With the advancements in the field of complete genome sequencing and computational approaches development have lead to metabolic pathway analysis and protein-protein interaction network which provides vital evidence to the protein function and has been appropriate to the fields such as systems biology and drug discovery. Protein interaction network analysis allows us to predict the most potential drug targets among large number of the non-homologous proteins involved in the unique metabolic pathway. A computational comparative metabolic pathway analysis of the host H. sapiens and the pathogen C pneumoniae AR39 has been carried out at three level analyses. Firstly, metabolic pathway analysis was performed to identify unique metabolic pathways and non-homologous proteins were identified. Secondly, essentiality of the proteins was checked, where these proteins contribute to the growth and survival of the organism. Finally these proteins were further subjected to predict protein interaction networks. Among the total 65 pathways in the C pneumoniae AR39 genome 10 were identified as the unique metabolic pathways which were not found in the human host, 32 enzymes were predicted as essential and these proteins were considered for protein interaction analysis, later using various criteria''s we have narrowed down to prioritize ribonucleotide-diphosphate reductase subunit beta as a potential drug target which facilitate for the successful entry into drug designing.     

In silico identification of potential drug targets in swine pathogen Haemophilus parasuis

Gram-negative bacterium Haemophilus parasuis has recently become one of the most important etiological agents causing serious systemic disease (Gl?sser??s disease) in pigs. Antibiotic therapy has played a crucial role in the treatment of this disease. Antibiotic resistance observed from the clinical isolates of this pathogen urges us to discover novel drug targets for antimicrobial agents. In this study, we used a combined strategy including exploration of the gene essentiality and comparison of metabolic pathways to infer drug targets of H. parasuis. We identified 931 gene products essential for bacterial growth according to the DEG database. One hundred and ninety-nine enzyme-coding genes were found in the genome of H. parasuis but were absent in that of the swine host. Lastly, we determined 117 enzymes exhibiting essentiality and specificity to H. parasuis as a candidate set of drug targets. Comparison of metabolic pathways between the pathogen and host showed that 25 targeting enzymes belonged to nine unique pathways of the pathogen. The profile of promising targets identified in our study will provide a useful basis for developing more effective antibiotics against the severe swine disease caused by H. parasuis.     

Protein interaction network analysis—Approach for potential drug target identification in Mycobacterium tuberculosis

In host-parasite diseases like tuberculosis, non-homologous proteins (enzymes) as drug target are first preference. Most potent drug target can be identified among large number of non-homologous protein through protein interaction network analysis. In this study, the entire promising dimension has been explored for identification of potential drug target. A comparative metabolic pathway analysis of the host Homo sapiens and the pathogen M. tuberculosis H37Rv has been performed with three level of analysis. In first level, the unique metabolic pathways of M. tuberculosis have been identified through its comparative study with H. sapiens and identification of non-homologous proteins has been done through BLAST similarity search. In second level, choke-point analysis has been performed with identified non-homologous proteins of metabolic pathways. In third level, two type of analysis have been performed through protein interaction network. First analysis has been done to find out the most potential metabolic functional associations among all identified choke point proteins whereas second analysis has been performed to find out the functional association of high metabolic interacting proteins to pathogenesis causing proteins. Most interactive metabolic proteins which have highest number of functional association with pathogenesis causing proteins have been considered as potential drug target. A list of 18 potential drug targets has been proposed which are various stages of progress at the TBSGC and proposed drug targets are also studied for other pathogenic strains.As a case study, we have built a homology model of identified drug targets histidinol-phosphate aminotransferase (HisC1) using MODELLER software and various information have been generated through molecular dynamics which will be useful in wetlab structure determination. The generated model could be further explored for insilico docking studies with suitable inhibitors.     

Potential therapeutic drug target identification in Community Acquired-Methicillin Resistant Staphylococcus aureus (CA-MRSA) using computational analysis

The emergence of multidrug-resistant strain of community-acquired methicillin resistant Staphylococcus aureus (CA-MRSA) strain has highlighted the urgent need for the alternative and effective therapeutic approach to combat the menace of this nosocomial pathogen. In the present work novel potential therapeutic drug targets have been identified through the metabolic pathways analysis. All the gene products involved in different metabolic pathways of CA-MRSA in KEGG database were searched against the proteome of Homo sapiens using the BLASTp program and the threshold of E-value was set to as 0.001. After database searching, 152 putative targets were identified. Among all 152 putative targets, 39 genes encoding for putative targets were identified as the essential genes from the DEG database which are indispensable for the survival of CA-MRSA. After extensive literature review, 7 targets were identified as potential therapeutic drug target. These targets are Fructose-bisphosphate aldolase, Phosphoglyceromutase, Purine nucleoside phosphorylase, Uridylate kinase, Tryptophan synthase subunit beta, Acetate kinase and UDP-N-acetylglucosamine 1-carboxyvinyltransferase. Except Uridylate kinase all the identified targets were involved in more than one metabolic pathways of CA-MRSA which underlines the importance of drug targets. These potential therapeutic drug targets can be exploited for the discovery of novel inhibitors for CA-MRSA using the structure based drug design (SBDD) strategy.     

Core Proteomic Analysis of Unique Metabolic Pathways of Salmonella enterica for the Identification of Potential Drug Targets

Background

Infections caused by Salmonella enterica, a Gram-negative facultative anaerobic bacteria belonging to the family of Enterobacteriaceae, are major threats to the health of humans and animals. The recent availability of complete genome data of pathogenic strains of the S. enterica gives new avenues for the identification of drug targets and drug candidates. We have used the genomic and metabolic pathway data to identify pathways and proteins essential to the pathogen and absent from the host.

Methods

We took the whole proteome sequence data of 42 strains of S. enterica and Homo sapiens along with KEGG-annotated metabolic pathway data, clustered proteins sequences using CD-HIT, identified essential genes using DEG database and discarded S. enterica homologs of human proteins in unique metabolic pathways (UMPs) and characterized hypothetical proteins with SVM-prot and InterProScan. Through this core proteomic analysis we have identified enzymes essential to the pathogen.

Results

The identification of 73 enzymes common in 42 strains of S. enterica is the real strength of the current study. We proposed all 73 unexplored enzymes as potential drug targets against the infections caused by the S. enterica. The study is comprehensive around S. enterica and simultaneously considered every possible pathogenic strain of S. enterica. This comprehensiveness turned the current study significant since, to the best of our knowledge it is the first subtractive core proteomic analysis of the unique metabolic pathways applied to any pathogen for the identification of drug targets. We applied extensive computational methods to shortlist few potential drug targets considering the druggability criteria e.g. Non-homologous to the human host, essential to the pathogen and playing significant role in essential metabolic pathways of the pathogen (i.e. S. enterica). In the current study, the subtractive proteomics through a novel approach was applied i.e. by considering only proteins of the unique metabolic pathways of the pathogens and mining the proteomic data of all completely sequenced strains of the pathogen, thus improving the quality and application of the results. We believe that the sharing of the knowledge from this study would eventually lead to bring about novel and unique therapeutic regimens against the infections caused by the S. enterica.     

Reconstruction of pathways associated with amino acid metabolism in human mitochondria

We have used a bioinformatics approach for the identification and reconstruction of metabolic pathways associated with amino acid metabolism in human mitochondria. Human mitochondrial proteins determined by experimental and computational methods have been superposed on the reference pathways from the KEGG database to identify mitochondrial pathways. Enzymes at the entry and exit points for each reconstructed pathway were identified, and mitochondrial solute carrier proteins were determined where applicable. Intermediate enzymes in the mitochondrial pathways were identified based on the annotations available from public databases, evidence in current literature, or our MITOPRED program, which predicts the mitochondrial localization of proteins. Through integration of the data derived from experimental, bibliographical, and computational sources, we reconstructed the amino acid metabolic pathways in human mitochondria, which could help better understand the mitochondrial metabolism and its role in human health.     

Reconstruction of Pathways Associated with Amino Acid Metabolism in Human Mitochondria

We have used a bioinformatics approach for the identification and reconstruction of metabolic pathways associated with amino acid metabolism in human mitochon- dria. Human mitochondrial proteins determined by experimental and computa- tional methods have been superposed on the reference pathways from the KEGG database to identify mitochondrial pathways. Enzymes at the entry and exit points for each reconstructed pathway were identified, and mitochondrial solute carrier proteins were determined where applicable. Intermediate enzymes in the mito- chondrial pathways were identified based on the annotations available from public databases, evidence in current literature, or our MITOPRED program, which pre- dicts the mitochondrial localization of proteins. Through integration of the data derived from experimental, bibliographical, and computational sources, we recon- structed the amino acid metabolic pathways in human mitochondria, which could help better understand the mitochondrial metabolism and its role in human health.     

Reconstruction of Pathways Associated with Amino Acid Metabolism in Human Mitochondria

We have used a bioinformatics approach for the identification and reconstruction of metabolic pathways associated with amino acid metabolism in human mitochon- dria. Human mitochondrial proteins determined by experimental and computa- tional methods have been superposed on the reference pathways from the KEGG database to identify mitochondrial pathways. Enzymes at the entry and exit points for each reconstructed pathway were identified, and mitochondrial solute carrier proteins were determined where applicable. Intermediate enzymes in the mito- chondrial pathways were identified based on the annotations available from public databases, evidence in current literature, or our MITOPRED program, which pre- dicts the mitochondrial localization of proteins. Through integration of the data derived from experimental, bibliographical, and computational sources, we recon- structed the amino acid metabolic pathways in human mitochondria, which could help better understand the mitochondrial metabolism and its role in human health.     

Computational genome analyses of metabolic enzymes in Mycobacterium leprae for drug target identification

Leprosy is an infectious disease caused by Mycobacterium leprae. M. leprae has undergone a major reductive evolution leaving a minimal set of functional genes for survival. It remains non-cultivable. As M. leprae develops resistance against most of the drugs, novel drug targets are required in order to design new drugs. As most of the essential genes mediate several biosynthetic and metabolic pathways, the pathway predictions can predict essential genes. We used comparative genome analysis of metabolic enzymes in M. leprae and H. sapiens using KEGG pathway database and identified 179 non-homologues enzymes. On further comparison of these 179 non-homologous enzymes to the list of minimal set of 48 essential genes required for cell-wall biosynthesis of M. leprae reveals eight common enzymes. Interestingly, six of these eight common enzymes map to that of peptidoglycan biosynthesis and they all belong to Mur enzymes. The machinery for peptidoglycan biosynthesis is a rich source of crucial targets for antibacterial chemotherapy and thus targeting these enzymes is a step towards facilitating the search for new antibiotics.     

Potential drug targets on insomnia and intervention effects of Jujuboside A through metabolic pathway analysis as revealed by UPLC/ESI-SYNAPT-HDMS coupled with pattern recognition approach

Potential metabolites from the metabolic pathways could be therapeutic targets and useful for the discovery of broad spectrum drugs. UPLC/ESI-SYNAPT-HDMS coupled with pattern recognition methods including PCA, PLS-DA, OPLS-DA and Heatmap were integrated to examine the global metabolic signature of insomnia and intervention effects of Jujuboside A (JuA). Six unique pathways of the insomnia were identified using Ingenuity Pathway Analysis (IPA) software. The VIP-value threshold cutoff of the metabolites was set to 10, above this threshold, were filtered out as potential target biomarkers. Sixteen distinct metabolites were identified from these pathways, and 6 of them can be considered for rational drug design. It was further experimental validation that the changes in metabolic profiling were restored to their baseline values after JuA treatment according to the multivariate data analysis. Potential metabolite network of the insomnia was preliminarily predicted JuA-target interaction networks, and could be further explored for in silico docking studies with suitable drugs. Thus, our method is an efficient procedure for drug target identification through metabolic analysis. It can guide testable predictions, provide insights into drug action mechanisms and enable us to increase research productivity toward metabolomic drug discovery.     

Metabolic pathway analysis and molecular docking analysis for identification of putative drug targets in Toxoplasma gondii: novel approach

Toxoplasma gondii is an obligate intracellular apicomplexan parasite that can infect a wide range of warm-blooded animals including humans. In humans and other intermediate hosts, toxoplasma develops into chronic infection that cannot be eliminated by host's immune response or by currently used drugs. In most cases, chronic infections are largely asymptomatic unless the host becomes immune compromised. Thus, toxoplasma is a global health problem and the situation has become more precarious due to the advent of HIV infections and poor toleration of drugs used to treat toxoplasma infection, having severe side effects and also resistance have been developed to the current generation of drugs. The emergence of these drug resistant varieties of T. gondii has led to a search for novel drug targets. We have performed a comparative analysis of metabolic pathways of the host Homo sapiens and the pathogen T. gondii. The enzymes in the unique pathways of T. gondii, which do not show similarity to any protein from the host, represent attractive potential drug targets. We have listed out 11 such potential drug targets which are playing some important work in more than one pathway. Out of these, one important target is Glutamate dehydrogenase enzyme; it plays crucial part in oxidation reduction, metabolic process and amino acid metabolic process. As this is also present in the targets of tropical diseases of TDR (Tropical disease related Drug) target database and no PDB and MODBASE 3D structural model is available, homology models for Glutamate dehydrogenase enzyme were generated using MODELLER9v6. The model was further explored for the molecular dynamics simulation study with GROMACS, virtual screening and docking studies with suitable inhibitors against the NCI diversity subset molecules from ZINC database, by using AutoDock-Vina. The best ten docking solutions were selected (ZINC01690699, ZINC17465979, ZINC17465983, ZINC18141294_03, ZINC05462670, ZINC01572309, ZINC18055497_01, ZINC18141294, ZINC05462674 and ZINC13152284_01). Further the Complexes were analyzed through LIGPLOT. On the basis of Complex scoring and binding ability it is deciphered that these NCI diversity set II compounds, specifically ZINC01690699 (as it has minimum energy score and one of the highest number of interactions with the active site residue), could be promising inhibitors for T. gondii using Glutamate dehydrogenase as Drug target.     

肺炎链球菌体内诱导基因的筛选及初步鉴定

为筛选鉴定肺炎链球菌宿主体内诱导的基因,寻找潜在的抗生素作用靶点和疫苗候选者,应用体内表达技术,以肺炎链球菌荚膜合成的关键基因galU作为体内报告基因,利用其缺陷体不能合成荚膜多糖,从而不能在宿主体内存活的特点,筛选鉴定肺炎链球菌体内诱导基因。首先,把肺炎链球菌基因组DNA的随机酶切片段(200~500bp)克隆到含有体内、体外双重报告基因(galU-lacZ)的报告载体pEVP3-galU的BglⅡ位点,将获得的质粒库转化肺炎链球菌galU缺陷菌株,得到肺炎链球菌体内启动子诱捕文库,将此文库去感染BALB/c小鼠,经过两轮体内筛选,在涂布有X-gal的TSA血清平板上得到了165个白色菌落,对插入的随机片段进行测序及生物信息学分析,共证实15个不同的体内诱导基因片段,8个为单独的ORF,7个为含有多个ORFs的操纵子结构,它们分别参与细菌在宿主体内的定植与粘附、能量代谢、物质转运、转录调节、DNA复制与重组、细胞壁合成等,另外还包括功能不明的假想蛋白。其中部分ORFs可能与细菌毒力相关,可以作为候选疫苗和药物的靶标。     

Proteomic analysis of protein expression in Streptococcus pneumoniae in response to temperature shift

From its initial colonization to causation of disease, Streptococcus pneumoniae has evolved strategies to cope with a number of stressful in vivo environmental conditions. In order to analyze a global view of this organism's response to heat shock, we established a 2-D electrophoresis proteome map of the S. pneumoniae D39 soluble proteins under in vitro culture conditions and performed the comparative proteome analysis to a 37 to 42 degrees temperature up-shift in S. pneumoniae. When the temperature of an exponentially growing S. pneumoniae D39 culture was raised to 42 degrees , the expression level of 25 proteins showed changes when compared to the control. Among these 25 proteins, 12 were identified by MALDI-TOF and LC-coupled ESI MS/MS. The identified proteins were shown to be involved in the general stress response, energy metabolism, nucleotide biosynthesis pathways, and purine metabolism. These results provide clues for understanding the mechanism of adaptation to heat shock by S. pneumoniae and may facilitate the assessment of a possible role for these proteins in the physiology and pathogenesis of this pathogen.     

In silico quest for putative drug targets in <Emphasis Type="Italic">Helicobacter pylori</Emphasis> HPAG1: molecular modeling of candidate enzymes from lipopolysaccharide biosynthesis pathway

Aimed at identification and structural characterization of novel putative therapeutic targets in H. pylori, the etiological agent of numerous gastrointestinal diseases including peptic ulcer and gastric cancer, the present study comprised of three phases. First, through subtractive analysis of metabolic pathways of Helicobacter pylori HPAG1 and human, as documented in the KEGG database, 11 pathogen-specific pathways were identified. Next, all proteins involved in these pathogen-specific pathways were scrutinized in search of promising targets and the study yielded 25 candidate target proteins that are likely to be essential for the pathogen viability, but have no homolog in human. The lipopolysaccharide (LPS) biosynthesis pathway was found to be the largest contributor (nine proteins) to this list of candidate proteins. Considering the importance of LPS in H. pylori virulence, 3D structural models of three predicted target enzymes of this pathway, namely 2-dehydro-3-deoxy-phosphooctonate aldolase, UDP-3-O-[3-hydroxymyristoyl] N-acetylglucosamine deacetylase and Phosphoheptose isomerase, were then built up using the homology modeling approaches. Binding site analysis and docking of the known biological substrate PEP to 2-dehydro-3-deoxyphosphooctonate aldolase revealed the potential binding pocket present in the single monomeric form of the enzyme and identified 11 amino acid residues that might play the key roles in this protein-ligand interaction.     

Genome subtraction for novel target definition in Salmonella typhi

Large genomic sequencing projects of pathogens as well as human genome leads to immense genomic and proteomic data which would be very beneficial for the novel target identification in pathogens. Subtractive genomic approach is one of the most useful strategies helpful in identification of potential targets. The approach works by subtracting the genes or proteins homologous to both host and the pathogen and identify those set of gene or proteins which are essential for the pathogen and are exclusively present in the pathogen. Subtractive genomic approach is employed to identify novel target in salmonella typhi. The pathogen has 4718 proteins out of which 300 are found to be essential (“ indispensable to support cellular life”) in the pathogen with no human homolog. Metabolic pathway analyses of these 300 essential proteins revealed that 149 proteins are exclusively involved in several metabolic pathway of S. typhi. 8 metabolic pathways are found to be present exclusively in the pathogen comprising of 27 enzymes unique to the pathogen. Thus, these 27 proteins may serve as prospective drug targets. Sub-cellular localization prediction of the 300 essential proteins was done which reveals that 11 proteins lie on the outer membrane of the pathogen which could be probable vaccine candidates.     

From genetic footprinting to antimicrobial drug targets: examples in cofactor biosynthetic pathways

Novel drug targets are required in order to design new defenses against antibiotic-resistant pathogens. Comparative genomics provides new opportunities for finding optimal targets among previously unexplored cellular functions, based on an understanding of related biological processes in bacterial pathogens and their hosts. We describe an integrated approach to identification and prioritization of broad-spectrum drug targets. Our strategy is based on genetic footprinting in Escherichia coli followed by metabolic context analysis of essential gene orthologs in various species. Genes required for viability of E. coli in rich medium were identified on a whole-genome scale using the genetic footprinting technique. Potential target pathways were deduced from these data and compared with a panel of representative bacterial pathogens by using metabolic reconstructions from genomic data. Conserved and indispensable functions revealed by this analysis potentially represent broad-spectrum antibacterial targets. Further target prioritization involves comparison of the corresponding pathways and individual functions between pathogens and the human host. The most promising targets are validated by direct knockouts in model pathogens. The efficacy of this approach is illustrated using examples from metabolism of adenylate cofactors NAD(P), coenzyme A, and flavin adenine dinucleotide. Several drug targets within these pathways, including three distantly related adenylyltransferases (orthologs of the E. coli genes nadD, coaD, and ribF), are discussed in detail.     

金属蛋白质组学研究锌离子匮乏对肺炎链球菌的影响

【目的】研究锌离子缺乏对肺炎链球菌的影响,找到其适应性生长机制。【方法】以肺炎链球菌为模型,利用加锌和不加锌的培养基对细菌进行培养,收集细胞蛋白,采用双向凝胶电泳,结合金属亲和层析和质谱技术鉴定差异表达蛋白,进而通过生物信息学分析蛋白质相互关系,从中找到细菌适应锌离子匮乏条件的关键代谢通路和蛋白。【结果】测定了在限制培养条件下肺炎链球菌的最适生长浓度,建立了锌离子调控蛋白双向凝胶电泳图谱,鉴定到了96个差异表达蛋白斑点,共67个差异蛋白,其中32个表达下调,35个表达上调,锌离子调控蛋白的作用可能主要体现在糖代谢、核酸代谢、氧化还原作用、辅助蛋白质翻译、合成及折叠等方面。建立了锌结合蛋白的差异表达图谱,鉴定到了10个差异表达蛋白斑点,共7个差异蛋白,其中1个表达下调,6个表达上调。锌离子结合蛋白的作用可能主要体现在应对压力、蛋白质折叠和转运、氨基酸代谢等方面。【结论】肺炎链球菌主要通过调控碳水化合物代谢和核酸代谢等多个代谢通路来应对宿主锌金属离子匮乏的环境,从而使自身能够存活并对宿主形成感染。本研究为揭示细菌在宿主环境,特别是金属离子匮乏条件下的适应性生长机制提供理论基础。     

Proteomic analysis of membrane proteins from Streptococcus pneumoniae with multiple separation methods plus high accuracy mass spectrometry

Abstract Streptococcus pneumoniae is a Gram-positive human pathogen that causes a variety of serious mucosal and invasive diseases in human. Bacterial membrane proteins play crucial roles in host-pathogen interactions and bacterial pathogenesis, and thus are potential drug targets or vaccine candidates. In this study, membranes from Streptococcus pneumoniae D39 were enriched by mechanical grinding and ultracentrifugation, and then the membrane proteins were extracted with trifluroethanol and chloroform. Around 60% of the extracted proteins were identified to be membrane proteins with 2-DE coupled with MALDI-MS/MS and 2D-LC-ESI-MS/MS. These identified membrane proteins can be functionally categorized into various groups involved in nutriment transport, signal transduction, protein folding or secretion, oxidation, carbohydrate metabolism, and other physiological processes. A protein interaction network was constructed for understanding the regulation relationship of the membrane proteins. This study represents the first global characterization of membrane proteome from Gram-positive streptococcus species of bacteria, providing valuable clues for further investigation aiming at identifying drug/vaccine targets for the bacterial infection.