Potential drug targets in cyst-wall biosynthesis by intestinal protozoa

Jarroll, Edward L.; Şener, Keriman

doi:10.1016/s1368-7646(03)00065-7

Cited by 21 publications

(10 citation statements)

References 54 publications

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“…Potential targets for the development of antiamoebic drugs include the glycolytic pathway (namely, pyrophosphate-dependent phosphofructokinase and pyruvate kinase) (103,200), alcohol dehydrogenase 2 (90, 337), cysteine proteases (157,252), isoprenyltransferases (170,195), and sulfur-containing-aminoacid metabolism (233). For the development of new chemotherapeutics against giardiasis, several candidates have been investigated, including guanine phosphoribosyltransferase, a key enzyme in the purine salvage pathway (222), and biosynthesis of a novel ␤-(1,3)-N-acetyl-D-galactosamine homopolymer [including 4Ј-epimerase and ␤-(1,3)-N-acetyl-D-galactosamine transferase] (102,148,285). Encystation and excystation are unique cellular processes that fulfill the criteria for rational drug targets.…”

Section: Metabolic Pathways In Protozoan Parasites Under Investigatiomentioning

confidence: 99%

Current Therapeutics, Their Problems, and Sulfur-Containing-Amino-Acid Metabolism as a Novel Target against Infections by “Amitochondriate” Protozoan Parasites

2007

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SUMMARY The “amitochondriate” protozoan parasites of humans Entamoeba histolytica, Giardia intestinalis, and Trichomonas vaginalis share many biochemical features, e.g., energy and amino acid metabolism, a spectrum of drugs for their treatment, and the occurrence of drug resistance. These parasites possess metabolic pathways that are divergent from those of their mammalian hosts and are often considered to be good targets for drug development. Sulfur-containing-amino-acid metabolism represents one such divergent metabolic pathway, namely, the cysteine biosynthetic pathway and methionine γ-lyase-mediated catabolism of sulfur-containing amino acids, which are present in T. vaginalis and E. histolytica but absent in G. intestinalis. These pathways are potentially exploitable for development of drugs against amoebiasis and trichomoniasis. For instance, l-trifluoromethionine, which is catalyzed by methionine γ-lyase and produces a toxic product, is effective against T. vaginalis and E. histolytica parasites in vitro and in vivo and may represent a good lead compound. In this review, we summarize the biology of these microaerophilic parasites, their clinical manifestation and epidemiology of disease, chemotherapeutics, the modes of action of representative drugs, and problems related to these drugs, including drug resistance. We further discuss our approach to exploit unique sulfur-containing-amino-acid metabolism, focusing on development of drugs against E. histolytica.

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Section: Metabolic Pathways In Protozoan Parasites Under Investigatiomentioning

confidence: 99%

Current Therapeutics, Their Problems, and Sulfur-Containing-Amino-Acid Metabolism as a Novel Target against Infections by “Amitochondriate” Protozoan Parasites

2007

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“…It is necessary to define whether the other well characterized encystation-induced transcription factors are regulated by similar or distinct signaling pathways. Characterizing these processes at a functional level will reveal new targets for diagnosis, drug design and prophylactic intervention similarly to the cyst wall polysaccharide-targeting drugs and nucleotide-based cyst wall biosynthesis inhibitors (Jarroll & Sener, 2003;Suk et al, 2007) …”

Section: Resultsmentioning

confidence: 99%

Encystation commitment inGiardia duodenalis: a long and winding road

Argüello-García

Ortega‐Pierres

2009

Parasite

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“…This turns out to be true-CHS2 is involved in transferring N-acetylglucosamine to chitin. It is also relevant in diseasetreatment; some recent work on developing antiprotozoal drugs has focused on targeting the chitin-synthesis pathway 6 . Similarly, for DSF2-a hitherto uncharacterized gene-the set of its predicted interaction partners is enriched for genes related to DNA transposition and retrotransposons (p < 0.001), indicating DSF2's possible function.…”

Section: Novel Predictionsmentioning

confidence: 99%

Struct2net: Integrating Structure Into Protein-Protein Interaction Prediction

Singh

Berger³

2005

Biocomputing 2006

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This paper presents a framework for predicting protein-protein interactions (PPI) that integrates structure-based information with other functional annotations, e.g. GO, co-expression and co-localization, etc. Given two protein sequences, the structure-based interaction prediction technique threads these two sequences to all the protein complexes in the PDB and then chooses the best potential match. Based on this match, structural information is incorporated into logistic regression to evaluate the probability of these two proteins interacting. This paper also describes a random forest classifier which can effectively combine the structure-based prediction results and other functional annotations together to predict protein interactions. Experimental results indicate that the predictive power of the structurebased method is better than many other information sources. Also, combining the structure-based method with other information sources allows us to achieve a better performance than when structure information is not used. We also tested our method on a set of approximately 1000 yeast genes and, interestingly, the predicted interaction network is a scale-free network. Our method predicted some potential interactions involving yeast homologs of human disease-related proteins.

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Potential drug targets in cyst-wall biosynthesis by intestinal protozoa

Cited by 21 publications

References 54 publications

Current Therapeutics, Their Problems, and Sulfur-Containing-Amino-Acid Metabolism as a Novel Target against Infections by “Amitochondriate” Protozoan Parasites

Current Therapeutics, Their Problems, and Sulfur-Containing-Amino-Acid Metabolism as a Novel Target against Infections by “Amitochondriate” Protozoan Parasites

Encystation commitment inGiardia duodenalis: a long and winding road

Struct2net: Integrating Structure Into Protein-Protein Interaction Prediction

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