Metabolic pathway analysis of S. pneumoniae: an in silico approach towards drug-design

The emergence of multidrug resistant varieties of Streptococcus pneumoniae (S. pneumoniae) has led to a search for novel drug targets. An in silico comparative analysis of metabolic pathways of the host Homo sapiens (H. sapiens) and the pathogen S. pneumoniae have been performed. Enzymes from the biochemical pathways of S. pneumoniae from the KEGG metabolic pathway database were compared with proteins from the host H. sapiens, by performing a BLASTp search against the non-redundant database restricted to the H. sapiens subset. The e-value threshold cutoff was set to 0.005. Enzymes, which do not show similarity to any of the host proteins, below this threshold, were filtered out as potential drug targets. Five pathways unique to the pathogen S. pneumoniae when compared to the host H. sapiens have been identified. Potential drug targets from these pathways could be useful for the discovery of broad-spectrum drugs. Potential drug targets were also identified from pathways related to lipid metabolism, carbohydrate metabolism, amino acid metabolism, energy metabolism, vitamin and cofactor biosynthetic pathways and nucleotide metabolism. Of the 161 distinct targets identified from these pathways, many are in various stages of progress at the Microbial Genome Database. However, 44 of the targets are new and can be considered for rational drug design. The study was successful in listing out potential drug targets from the S. pneumoniae proteome involved in vital aspects of the pathogen's metabolism, persistence, virulence and cell wall biosynthesis. This systematic evaluation of metabolic pathways of host and pathogen through reliable and conventional bioinformatics approach can be extended to other pathogens of clinical interest.     

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.     

A Mapping of Drug Space from the Viewpoint of Small Molecule Metabolism

Small molecule drugs target many core metabolic enzymes in humans and pathogens, often mimicking endogenous ligands. The effects may be therapeutic or toxic, but are frequently unexpected. A large-scale mapping of the intersection between drugs and metabolism is needed to better guide drug discovery. To map the intersection between drugs and metabolism, we have grouped drugs and metabolites by their associated targets and enzymes using ligand-based set signatures created to quantify their degree of similarity in chemical space. The results reveal the chemical space that has been explored for metabolic targets, where successful drugs have been found, and what novel territory remains. To aid other researchers in their drug discovery efforts, we have created an online resource of interactive maps linking drugs to metabolism. These maps predict the “effect space” comprising likely target enzymes for each of the 246 MDDR drug classes in humans. The online resource also provides species-specific interactive drug-metabolism maps for each of the 385 model organisms and pathogens in the BioCyc database collection. Chemical similarity links between drugs and metabolites predict potential toxicity, suggest routes of metabolism, and reveal drug polypharmacology. The metabolic maps enable interactive navigation of the vast biological data on potential metabolic drug targets and the drug chemistry currently available to prosecute those targets. Thus, this work provides a large-scale approach to ligand-based prediction of drug action in small molecule metabolism.     

Metabonomic studies on potential plasma biomarkers in rats exposed to ionizing radiation and the protective effects of Hong Shan Capsule

An ultra performance liquid chromatography coupled to mass spectrometry-based metabonomic approach, combined with pattern recognition methods including PCA, PLS-DA, RF and heatmap, has been developed to characterize the global serum metabolic profile associated with ionizing radiation (IR). As the VIP-value threshold cutoff of the metabolites was set to 2, metabolites above this threshold were filtered out as potential target biomarkers. Nineteen distinct potential biomarkers in rat plasma were identified. To further elucidate the pathophysiology of IR, related metabolic pathways have been studied. It was found that IR was closely related to disturbed fatty acid metabolism, taurine and hypotaurine metabolism, sphingolipid metabolism, purine metabolism, pyrimidine metabolism, phospholipid catabolism, tryptophan metabolism, phenylalanine metabolism, and bile acid metabolism. With the presented metabonomic method, we systematically analyzed the protective effects of Traditional Chinese Medicine Hong Shan Capsule (HSC). The results demonstrated that HSC administration could provide satisfactory effects on IR through partially regulating the perturbed metabolic pathways.     

A revision of the metabolic disposition of amantadine

Amantadine is one of the most commonly used drugs for the control of tremor in Parkinson's disease. Additionally, it has an antiviral action in the prevention of type A influenza. It has been previously reported that amantadine is nearly completely eliminated in the urine. No metabolites have been detected. Surprisingly, in a case of amantadine overdose, several metabolites could be identified by gas chromatography/mas spectrometry. This finding prompted us to re-investigate the metabolism of amantadine under a therapeutic dosing regimen. The bulk of the dose was eliminated unchanged. However, eight metabolites could be identified. Besides N-acetylation which is the major metabolic pathway, several rather unusual metabolic pathways were observed: N-methylation, formation of Schiff bases and N-formiates. No metabolites with a hydroxylated adamantane ring system could be detected.     

Rapid analysis of metabolic stability of dopamine receptor antagonists and detection of their metabolites by liquid chromatography/tandem mass spectrometry

In vitro metabolic stability of dopamine D(3)/D(4) receptor antagonists and identification of their metabolites by high-performance liquid chromatography (HPLC) coupled with ion-trap mass spectrometry (ITMS) were assessed in rat liver microsomes. The compounds were divided into three cassette groups for rapid quantitative analysis of multiple drugs and simultaneous detection of their metabolites. The samples from incubation with rat liver microsomes were pooled into designed cassette groups and analyzed by HPLC/electrospray ITMS in full-scan mode. The metabolic stability of the drugs was determined by comparing their signals after incubation for 0 and for 30min. The metabolic stability of the examined dopamine receptor antagonists was in the range of 9.9-84.4%. In addition, the present cassette analysis allowed the simultaneous detection of metabolites formed during the same incubation without having to reanalyze the samples. The metabolites were first characterized by nominal mass measurement of the corresponding protonated molecules. Subsequent multistage tandem mass spectrometry on the ion-trap instrument allowed characterization of the structure of the detected metabolites. N,O-dealkylation and ring hydroxylation reactions were identified as major metabolic reactions in piperazinylalkylisoxazole derivatives. These results suggested that the present approach is useful for the rapid evaluation of metabolic stability and structural characterization of metabolites within a short period in new drug discovery.     

In vitro metabolic fate of a novel structural class: evidence for the formation of a reactive intermediate on a benzothiophene moiety

The characterization of the metabolic pathways of new chemical entities with a special emphasis on detecting potentially reactive metabolites is increasingly being performed early in the drug discovery process. In the present study, the preliminary in vitro metabolic routes of a series of novel 2-substituted benzothiophene-containing discovery molecules were determined in fresh and cryopreserved hepatocyte suspensions. The objectives of this investigation were: (1) to use systematic LC/MS and LC/MS/MS analyses to provide a preliminary characterization of the in vitro metabolism of these compounds, with a particular focus on metabolites potentially arising from reactive intermediates, and (2) to identify potential lead molecules not associated with such metabolic pathways. This benzothiophene-containing series of compounds was characterized by the formation of five metabolites, at least two of which (dihydrodiol formation and glutathione adduct of the dihydrohydroxyl) were indicative of the formation of a reactive arene oxide intermediate. Tandem mass spectral analysis of the metabolites formed from a variety of structurally similar compounds demonstrated this reactive arene oxide intermediate to form on the 2-substituted benzothiophene moiety. Substitution of the benzothiophene with other functional groups eliminated these potentially toxic metabolites. The data presented here demonstrate the utility of performing metabolic route screens early in the drug discovery process prior to lengthy and costly radiolabeled studies, and furthermore, implicate a 2-substituted benzothiophene moiety as a substrate for formation of a reactive arene oxide intermediate.     

Drug repositioning for enzyme modulator based on human metabolite-likeness

Background

Recently, the metabolite-likeness of the drug space has emerged and has opened a new possibility for exploring human metabolite-like candidates in drug discovery. However, the applicability of metabolite-likeness in drug discovery has been largely unexplored. Moreover, there are no reports on its applications for the repositioning of drugs to possible enzyme modulators, although enzyme-drug relations could be directly inferred from the similarity relationships between enzyme’s metabolites and drugs.

Methods

We constructed a drug-metabolite structural similarity matrix, which contains 1,861 FDA-approved drugs and 1,110 human intermediary metabolites scored with the Tanimoto similarity. To verify the metabolite-likeness measure for drug repositioning, we analyzed 17 known antimetabolite drugs that resemble the innate metabolites of their eleven target enzymes as the gold standard positives. Highly scored drugs were selected as possible modulators of enzymes for their corresponding metabolites. Then, we assessed the performance of metabolite-likeness with a receiver operating characteristic analysis and compared it with other drug-target prediction methods. We set the similarity threshold for drug repositioning candidates of new enzyme modulators based on maximization of the Youden’s index. We also carried out literature surveys for supporting the drug repositioning results based on the metabolite-likeness.

Results

In this paper, we applied metabolite-likeness to repurpose FDA-approved drugs to disease-associated enzyme modulators that resemble human innate metabolites. All antimetabolite drugs were mapped with their known 11 target enzymes with statistically significant similarity values to the corresponding metabolites. The comparison with other drug-target prediction methods showed the higher performance of metabolite-likeness for predicting enzyme modulators. After that, the drugs scored higher than similarity score of 0.654 were selected as possible modulators of enzymes for their corresponding metabolites. In addition, we showed that drug repositioning results of 10 enzymes were concordant with the literature evidence.

Conclusions

This study introduced a method to predict the repositioning of known drugs to possible modulators of disease associated enzymes using human metabolite-likeness. We demonstrated that this approach works correctly with known antimetabolite drugs and showed that the proposed method has better performance compared to other drug target prediction methods in terms of enzyme modulators prediction. This study as a proof-of-concept showed how to apply metabolite-likeness to drug repositioning as well as potential in further expansion as we acquire more disease associated metabolite-target protein relations.

     

Thermodynamically based profiling of drug metabolism and drug-drug metabolic interactions: a case study of acetaminophen and ethanol toxic interaction

Drug-drug metabolic interactions can result in unwanted side effects, including reduced drug efficacy and formation of toxic metabolic intermediates. In this work, thermodynamic constraints on non-equilibrium metabolite concentrations are used to reveal the biochemical interactions between the metabolic pathways of ethanol and acetaminophen (N-acetyl-p-aminophenol), two drugs known to interact unfavorably. It is known that many reactions of these pathways are coupled to the central energy metabolic reactions through a number of metabolites and the cellular redox potential. Based on these observations, a metabolic network model has been constructed and a database of thermodynamic properties for all participating metabolites and reactions has been compiled. Constraint-based computational analysis of the feasible metabolite concentrations reveals that the non-toxic pathways for APAP metabolism and the pathway for detoxifying N-acetyl-p-benzoquinoneimine (NAPQI) are inhibited by network interactions with ethanol metabolism. These results point to the potential utility of thermodynamically based profiling of metabolic network interactions in screening of drug candidates and analysis of potential toxicity.     

Identification of Phosphoribosyl-AMP cyclohydrolase,as drug target and its inhibitors in Brucella melitensis bv. 1 16M using metabolic pathway analysis

Brucella melitensis is a pathogenic Gram-negative bacterium which is known for causing zoonotic diseases (Brucellosis). The organism is highly contagious and has been reported to be used as bioterrorism agent against humans. Several antibiotics and vaccines have been developed but these antibiotics have exhibited the sign of antibiotic resistance or ineffective at lower concentrations, which imposes an urgent need to identify the novel drugs/drug targets against this organism. In this work, metabolic pathways analysis has been performed with different filters such as non-homology with humans, essentially of genes and choke point analysis, leading to identification of novel drug targets. A total of 18 potential drug target proteins were filtered out and used to develop the high confidence protein–protein interaction network The Phosphoribosyl-AMP cyclohydrolase (HisI) protein has been identified as potential drug target on the basis of topological parameters. Further, a homology model of (HisI) protein has been developed using Modeller with multiple template (1W6Q (48%), 1ZPS (55%), and 2ZKN (48%)) approach and validated using PROCHECK and Verify3D. The virtual high throughput screening (vHTS) using DockBlaster tool has been performed against 16,11,889 clean fragments from ZINC database. Top 500 molecules from DockBlaster were docked using Vina. The docking analysis resulted in ZINC04880153 showing the lowest binding energy (?9.1 kcal/mol) with the drug target. The molecular dynamics study of the complex HisI-ZINC04880153 was conducted to analyze the stability and fluctuation of ligand within the binding pocket of HisI. The identified ligand could be analyzed in the wet-lab based experiments for future drug discovery.     

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.     

TNT biotransformation: when chemistry confronts mineralization

The recent increase and availability of whole genome sequences have revised our view of the metabolic capabilities of microorganisms. From these data, a large number of orphan biosynthesis pathways have been identified by bio-informatics. Orphan biosynthetic pathways are gene clusters for which the encoded natural product is unknown. It is worthy to note that the number of orphan pathways coding for putative natural products outnumbers by far the number of currently known metabolites for a given organism. Whilst Streptomyces coelicolor was known to produce only 4 secondary metabolites, the genome analysis revealed 18 additional orphan biosynthetic pathways. It is intriguing to note that this is not a particular case because analysis of other microbial genomes originating from myxobacteria, cyanobacteria and filamentous fungi showed the presence of a comparable or even larger number of orphan pathways. The discovery of these numerous pathways represents a treasure trove, which is likely to grow exponentially in the future, uncovering many novel and possibly bio-active compounds. The few natural products that have been correlated with their orphan pathway are merely the tip of the iceberg, whilst plenty of metabolites await discovery. The recent strategies and methods to access these promising hidden natural products are discussed in this review.     

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.     

代谢组学在肿瘤药物靶点筛选中的应用进展

肿瘤是一种多因素参与造成机体各系统功能平衡紊乱的代谢性疾病,代谢重编程是恶性肿瘤的重要特征之一.研究"代谢指纹图谱"的代谢组学,通过揭示肿瘤或药物引起的宿主内源性代谢物的变化,为肿瘤药物靶点的筛选提供了可能.但目前对代谢组在肿瘤药物靶点筛选中的整体性综述并不多见,因此,本文在介绍了代谢组学筛选肿瘤药物靶点的流程的基础上...     

Effects of celastrol on human cervical cancer cells as revealed by ion-trap gas chromatography–mass spectrometry based metabolic profiling

Background

Celastrol, a quinine methide triterpene extracted from a Chinese medicine (Trypterygium wilfordii Hook F.), has the potential to become an anticancer drug with promising prospects. Cell culture metabolomics has been a powerful method to study metabolic profiles in cell line after drug treatment, which can be used for discovery of drug targets and investigation of drug effects.

Methods

We analyzed the metabolic modifications induced by celastrol treatment in human cervical cancer cells, using an ion-trap gas chromatography–mass spectrometry based metabolomics combined with multivariate statistical analysis, which allows simultaneous screening of multiple characteristic metabolic pathways related to celastrol treatment. Three representative apoptosis-inducing cytotoxic agents, namely cisplatin, doxorubicin hydrochloride and paclitaxel, were selected as positive control drugs to validate reasonableness and accuracy of our metabolomic investigation on celastrol.

Results

Anti-proliferation and apoptotic effects of celastrol were demonstrated by CCK-8 assay, Annexin-V/PI staining method, mitochondrial membrane potential (ΔΨm) assay and caspase-3 assay. Several significant metabolites involved in energy, amino acid and nucleic acid metabolism in HeLa cells induced by celastrol and positive drugs were reported. Our method is proved to be effective and robust to provide new evidence of pharmacological mechanism of celastrol.

Conclusions

The metabolic alterations induced by drug treatment showed the impaired physiological activity of HeLa cells, which also indicated anti-proliferative and apoptotic effects of celastrol and these positive drugs.

General significance

GC/MS-based metabolomic approach applied to cell culture could give valuable information on the systemic effects of celastrol in vitro and help us to further study its anticancer mechanism.     

Transformation of verapamil by Cunninghamella blakesleeana

A filamentous fungus, Cunninghamella blakesleeana AS 3.153, was used as a microbial model of mammalian metabolism to transform verapamil, a calcium channel antagonist. The metabolites of verapamil were separated and assayed by the liquid chromatography-ion trap mass spectrometry method. After 96 h of incubation, nearly 93% of the original drug was metabolized to 23 metabolites. Five major metabolites were isolated by semipreparative high-performance liquid chromatography and were identified by proton nuclear magnetic resonance and electrospray mass spectrometry. Other metabolites were characterized according to their chromatographic behavior and mass spectral data. The major metabolic pathways of verapamil transformation by the fungus were N dealkylation, O demethylation, and sulfate conjugation. The phase I metabolites of verapamil (introduction of a functional group) by C. blakesleeana paralleled those in mammals; therefore, C. blakesleeana could be a useful tool for generating the mammalian phase I metabolites of verapamil.