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WO2011034263A1 - Procédé de prédiction d'une cible médicamenteuse dans des micro-organismes pathogènes au moyen d'un métabolite essentiel - Google Patents

Procédé de prédiction d'une cible médicamenteuse dans des micro-organismes pathogènes au moyen d'un métabolite essentiel Download PDF

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WO2011034263A1
WO2011034263A1 PCT/KR2010/000162 KR2010000162W WO2011034263A1 WO 2011034263 A1 WO2011034263 A1 WO 2011034263A1 KR 2010000162 W KR2010000162 W KR 2010000162W WO 2011034263 A1 WO2011034263 A1 WO 2011034263A1
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essential
metabolite
phosphate
metabolites
microorganism
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이상엽
김현욱
김태용
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한국과학기술원
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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B5/00—ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks

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  • the present invention relates to a method for predicting a drug target of a microorganism using computer system techniques, and more specifically, selecting a target microorganism, building a metabolic network model of the selected microorganism, and then analyzing metabolite essentiality,
  • the present invention relates to a method for predicting drug targets by removing currency metabolite, considering the number of reaction schemes, and irrelevance to host metabolism.
  • Pathogenic microorganisms can be very difficult and fatal to treat if they occur in people with weakened immune systems. Therefore, efforts to find a target for the development of effective anti-pathogenic drugs of pathogenic microorganisms are active.
  • Metabolic flow analysis uses the mass balance and cell composition information of biochemical equations to obtain the ideal metabolic flow space that cells can reach, and aims to maximize or minimize specific objective functions through optimization methods. Minimization of metabolic regulation by specific perturbation, etc.).
  • metabolic flow analysis can generally be used to confirm the lethality of specific genes of a desired metabolite through strain improvement, and can be used to determine the metabolic network characteristics within the strain.
  • various studies have been reported applying metabolic flow analysis methods to predict the flow changes in metabolic networks caused by the removal or addition of genes.
  • metabolic flow analysis techniques can be used to look at the metabolism of complex microorganisms from a holistic perspective using partial metabolic information and to identify the effects of manipulation on specific genes on overall metabolic flow to accurately predict drug targets of pathogenic microorganisms. There is an urgent need for the development of such methods.
  • the present inventors construct a metabolic network model of the microbial pathogen Acinetobacter baumannii, and then apply the metabolite essentiality method to the metabolic model to predict metabolites essential for cell growth.
  • the current metabolites and essential metabolites that consume less than the required number of reaction formulas are eliminated, and the remaining essential metabolites and enzymes consuming them are further selected by only selecting those that are not in human metabolism.
  • the present invention has been completed by theoretically finding that it is possible to select an effective pathogen drug target by selecting a candidate group.
  • An object of the present invention is to build a microbial metabolic network model structure, using the essential metabolite analysis (metabolite essentiality), distribution metabolite removal (currency metabolite) removal, considering the number of reactions, the relationship between the host metabolism,
  • the present invention provides a method for screening an enzyme or a gene encoding the same as a drug target.
  • Another object of the present invention is to provide a method for screening an enzyme or a gene encoding the enzyme that is a drug target of the genus Acinetobacter baumannii using the above method.
  • Another object of the present invention is to provide drug target enzymes for the genus Acinetobacter Baumani and the gene groups encoding them obtained by the above method.
  • At least three or more enzymes are involved in the reaction scheme, and at the same time, at least two or more of the essential metabolites consume the corresponding metabolites.
  • step (c) determining a secondary essential metabolite by removing a circulation metabolite having no specificity with the target microorganism among the first essential metabolites determined in step (b);
  • step (d) determining the third essential metabolite in consideration of the number of enzymatic schemes involved and the number of enzymatic schemes consumed among the secondary essential metabolites determined in step (c);
  • step (e) selecting only those which are not present in the metabolism of the host among the third essential metabolites determined in step (d) and determining the fourth essential metabolite;
  • step (f) if all of the enzymes consuming the fourth essential metabolites determined in step (e) do not have homology with the host protein, the corresponding metabolites are determined as the fifth essential metabolite, and the fifth essential metabolite It provides a method for screening a drug target enzyme of a microorganism comprising the step of selecting an enzyme involved in the drug target enzyme of the target microorganism.
  • the present invention provides a method for screening a drug target gene for a microorganism, characterized in that the gene group encoding the drug target enzyme of the selected microorganism is determined as a drug target gene of the target microorganism.
  • the host may be a human, and the target microorganism is preferably Escherichia coli or pathogenic microorganism, and more preferably pathogenic microorganism.
  • the metabolic network of the microorganism in step (a) is genomic level, and performing the step (b),
  • Vjm is a metabolic flow value of the corresponding consumption equation
  • the application of the linear programming is preferably made by reflecting all the nutrient conditions necessary for the growth of cells.
  • the distribution metabolite having no specificity with the target microorganism in step (c) is also involved in other enzymatic reactions of the target microorganism and other organisms, and in step (d), at least three or more of the secondary essential metabolites At least two or more at the same time involved in the enzymatic reaction, it is preferable to determine the metabolite in the case of consuming the required metabolite as the third essential metabolite, and in step (f) the examination of the homology is carried out Gene sequences can be used. At this time, the examination of the homology may be performed using the BLASTP program or the BLAST program.
  • the present invention provides the enzymes of the selected microorganism or gene groups encoding the same, and a method of using them as drug targets of the microorganism.
  • step (c) Of the primary essential metabolites determined in step (b), the secondary essential metabolite is removed by removing a circulation metabolite having no specificity with the microorganisms of the genus Acinetobacter. Determining;
  • step (d) determining the third essential metabolite in consideration of the number of enzymatic schemes involved and the number of enzymatic schemes consumed among the secondary essential metabolites determined in step (c); (e) selecting only those which are not present in the metabolism of the host among the third essential metabolites determined in step (d) and determining the fourth essential metabolite;
  • step (f) if all of the enzymes consuming the fourth essential metabolites determined in step (e) do not have homology with the host protein, the corresponding metabolites are determined as the fifth essential metabolite, and the fifth essential metabolite It provides a method for screening a drug target enzyme of the genus Acinetobacter (Acinetobacter) comprising the step of selecting an enzyme involved in the drug target enzyme of the genus Acinetobacter. At this time, Acinetobacter baumannii can be used among the microorganisms of the genus Acinetobacter.
  • the present invention is obtained by the above method, 2-amino-4-hydroxy-6-hydroxymethyldihydropteridine, pyrophosphokinase, dihydropteroate synthase, glutamate racemase, UDP-N-acetylmuramoylalanine--D-glutamate ligase, dihydrodipicolinate reductase, dihydroneopterin aldolase, alkaline phosphatase D precursor, 3-dehydroquinate dehydratase II, catabolic 3-dehydroquinate dehydratase (3-dehydroquinase), shikimate 5-dehydrogenase, quinate / shikimate dehydrogenase, 3-dehydroshikimate dehydratase, 1-deoxy-D-xylulose-5-phosphate reductoisomerase, Enzyme group of Acinetobacter sp.
  • microorganism selected from the group consisting of pyridoxine 5-phosphate synthase, 3-deoxy-manno-octulosonate cytidylyltransferase, and dihydropteroate synthase and methods for using the same as drug targets, ABAYE0036, ABAYE0082, ABAYE0377, ABAYE0807, ABAYE0811, ABAYE0945, ABAYE1417, ABAYE1418, ABAYE1539, ABAYE1581, ABAYE1682, ABAYE1683, ABAYE1685, ABAYE2076, ABAYE3176, ABAYE3395, ABAYE3524, ABAY Provided are a gene group of Acinetobacter genus microorganisms selected from the group consisting of E3568, ABAYE3612 and ABAYE3616, and a method of using the same as a drug target.
  • FIG. 1 is a schematic diagram illustrating the concept of a microbial drug targeting methodology in accordance with the present invention
  • A building a metabolic network of specific microorganisms
  • B Primary essential metabolite prediction using essential metabolite analysis
  • C removal of distribution metabolites
  • D Consider the number of schemes involved in that metabolite
  • E confirm presence in host metabolism
  • F drug target enzyme and gene determination
  • the present invention in one aspect, relates to a method for screening drug target enzymes or drug target genes encoding the microorganisms, in particular pathogenic microorganisms.
  • the schematic process is shown in FIG.
  • FIG. 1 illustrates the concept of an integrated drug targeting methodology in accordance with the present invention.
  • a metabolic network of a particular microorganism is constructed (A), from which essential metabolite analysis is predicted using essential metabolite analysis based on metabolic flow analysis (B). From this, the elimination of circulating metabolites (C), the consideration of the number of reaction formulas involved in the metabolites (D), the confirmation of the presence of essential metabolites and their involved reactions in human metabolism (E), etc. Predict the most effective drug targets of the microorganism (F).
  • step (c) determining a secondary essential metabolite by removing a circulation metabolite having no specificity with the target microorganism among the first essential metabolites determined in step (b);
  • the step (c) and / or (e); And (step (d)) may be selectively applied. Therefore, in another aspect, the present invention relates to a method for determining an essential metabolite according to the method of each step.
  • Step (f) is a step necessary to minimize adverse effects on the host of the drug, for example, the human body, and may shorten step (f) by performing steps (c) and (e). Therefore, in the case of performing step (f) in view of such efficiency, step (c) and step (e) can be selected individually or simultaneously. Most preferably, all the steps (c), (e) and (f) are performed.
  • step (d) may alternatively be carried out as a method devised in the present invention to significantly reduce the number of drug targets more effectively.
  • the method of one preferable aspect of this invention is as follows. That is, the present invention
  • step (c) determining a secondary essential metabolite by removing a circulation metabolite having no specificity with the target microorganism among the first essential metabolites determined in step (b);
  • step (d) determining the third essential metabolite in consideration of the number of enzymatic schemes involved and the number of enzymatic schemes consumed among the secondary essential metabolites determined in step (c);
  • step (e) selecting only those which are not present in the metabolism of the host among the third essential metabolites determined in step (d) and determining the fourth essential metabolite;
  • step (f) if all of the enzymes consuming the fourth essential metabolites determined in step (e) do not have homology with the host protein, the corresponding metabolites are determined as the fifth essential metabolite, and the fifth essential metabolite Selecting an enzyme involved in the drug target enzyme of the target microorganism.
  • Acinetobacter genus microorganisms for example, Acinetobacter baumannii
  • a method for screening drug target enzymes of the genus Acinetobacter comprising the following steps:
  • step (c) Of the primary essential metabolites determined in step (b), the secondary essential metabolite is removed by removing a circulation metabolite having no specificity with the microorganisms of the genus Acinetobacter. Determining;
  • step (d) determining the third essential metabolite in consideration of the number of enzymatic schemes involved and the number of enzymatic schemes consumed among the secondary essential metabolites determined in step (c);
  • step (e) selecting only those which are not present in the metabolism of the host among the third essential metabolites determined in step (d) and determining the fourth essential metabolite;
  • step (f) if all of the enzymes consuming the fourth essential metabolites determined in step (e) do not have homology with the host protein, the corresponding metabolites are determined as the fifth essential metabolite, and the fifth essential metabolite Selecting an enzyme involved in the drug target enzyme of the microorganism of the genus Acinetobacter.
  • steps “(c) and / or (e); And (step (d)) may be selectively applied.
  • the detailed description is as described above.
  • Methodabolism means a series of activities related to the energy activities of living things. That is, a series of activities that synthesize various metabolites necessary for life's activities through various biosynthesis through digestion that absorbs energy sources from the outside and converts them into the energy forms that are most readily available to life. Included in The earliest studied biological network is this "metabolic network.”
  • the first step in the present invention is to build a metabolic network of the target microorganism, to build a network consisting of all metabolites and reactive enzymes by collecting biochemical reactions occurring inside and outside the cell.
  • the target microorganism for constructing the metabolic network may be Escherichia coli or pathogenic microorganism, and any pathogenic microorganism may be used without particular limitation.
  • Acinetobacter genus microorganisms such as Acinetobacter baumannii, were used.
  • 'Pathogenic microorganism' is a microorganism having infectivity determined by pathogens, pathogens, pathogens, infectious paths and host susceptibility caused by toxins, enzymes and other products produced by microorganisms, and may include various viruses, bacteria and fungi. And they can be transmitted to various organisms such as animals and plants.
  • a metabolic network of microorganisms is established.
  • Acinetobacter baumannii (AB) is a gram-negative bacillus named after integrating two strains of Acinetobacter calcoaceticus and anitratus in the past, and has a wide range of bacteriological characteristics with various energy sources. It can be grown at or at pH and is found in samples taken from almost all soils and fresh water. Acinetobacter baumannii, which has this characteristic, has been reported as an important causative agent of hospital infections in many hospitals. Once hospital infections occur, they usually survive long-term in environments where bacteria are difficult to survive, resulting in high antibiotic resistance and resistance.
  • A. baumannii Due to its characteristics, it is difficult to treat, and as a result, the mortality rate caused by the causative organism also increases, which has recently emerged as an important pathogen.
  • A. baumannii is known to cause pneumonia associated with respirators, wound infections in burn patients, and sepsis.
  • Acinetobacter genus microbial metabolic network construction used in an example of the present invention can be made based on a gene group consisting of the following genes:
  • metabolic flow analysis is performed on the established metabolic network of the microorganism, which is to determine the essential metabolite of the microorganism primarily (called a primary essential metabolite).
  • the metabolic network of the constructed microorganism including all metabolites constituting the constructed metabolic network model, the metabolic pathway of the metabolite and the stoichiometric matrix S in the metabolic pathway.
  • a stoichiometric matrix the stoichiometric coefficient of the Sij, i of the second metabolite, the time in the j-th reaction
  • S is the amount of change in X over time
  • X is the metabolite concentration
  • t is the time
  • the change in the metabolite concentration X over time can be represented as the sum of the flows of all metabolic reactions. Assuming that the amount of change of X with time is constant, i.e., if the amount of change of X is 0, the amount of change of the metabolite concentration with time under the quasi-steady state may be defined by Equation 1 above.
  • the reaction scheme to be optimized that is, maximized or minimized, is set as the objective function and the metabolic flow in the cell is predicted using linear programming (Kim et al., Mol Biosyst . 4 (2)). : 113, 2008).
  • the cell growth rate is optimized by representing the constituents of the cells in matrix S and setting the scheme as the objective function. In other words, when applying the linear programming method, the objective function is set to maximize cell growth rate.
  • the metabolic flow analysis should be carried out on the assumption that all the nutrients necessary for the cell to grow can be taken. This is because when pathogenic microorganisms grow in the host, various nutrients can be taken from the host.
  • the enzyme reaction may appear to be essential only under certain conditions, but if metabolic flow analysis is applied on the assumption that all the nutrients can be ingested, it is possible to predict the essential enzyme reaction at all times.
  • the nutrients used were 2-Phospho-D-glycerate, 3-Phospho-D-glycerate, Acetate, Adenosine, 2 -Oxoglutarate, L-Alanine, L-Arginine, L-Asparagine, L-Aspartate, Betaine, Benzoate, Choline, Citrate, CO 2 , Cytosine, L-Cysteine, Cytidine, D-alanine, Deoxyadenosine, Deoxycytidine, D-Glutamate, Deoxyguanosine, D-Serine, Thymidine, Deoxyuridine, Ethanolamine, Formate, D-fructose, Fumarate, alpha-D-Glucose, L-Glutamine, D-Gluconate, L-Glutamate, Glycolate, Glycine, Gu
  • the method of determining the cell growth rate according to a specific gene deletion uses a method of inactivating each corresponding reaction scheme. Suppressing these enzyme reactions is based on the assumption that it is impossible to consume or produce the specific metabolites involved in these enzymes, which will eventually stop the cell growth of the target microorganism.
  • Suppressing these enzyme reactions is based on the assumption that it is impossible to consume or produce the specific metabolites involved in these enzymes, which will eventually stop the cell growth of the target microorganism.
  • the present invention by defining the 'essentiality' of each metabolite and looking at the properties of each metabolite, it is easy to identify the phenomenon of cell growth caused by the deletion of two or more genes. That is, the present invention provides a method of defining and using 'essentiality' of metabolites constituting the metabolic network of the target microorganism as follows.
  • the 'essentiality' of metabolites is the effect of cells on the growth of cells when they are not consumed by metabolism.
  • the rate of cell growth for each metabolite under certain conditions is determined by metabolic flow analysis.
  • the necessity of metabolites can be determined by investigating (FIG. 4) (Kim et al., Proc. Natl. Acad. Sci. USA , 104: 13638, 2007).
  • the metabolic flow value of the corresponding reaction equation is fixed to zero. In this case, if the growth rate of the cell is 0 is selected as an essential metabolite.
  • V jm represents the metabolic flow value of the consumption equation.
  • Essential metabolite analysis applies Equation 2 as an additional constraint while simultaneously blocking (deleting) all metabolic reactions consuming each metabolite in the stoichiometric matrix.
  • the metabolic flow value of the consumption equation By fixing the metabolic flow value of the consumption equation to 0, the case where the cell growth rate is 0 is selected as an essential metabolite. In other words, if there is no metabolic flow of essential metabolite, the cells of the microorganism do not grow to determine the essentiality.
  • the reason for not inactivating a metabolite produced without consuming a given metabolite is that the metabolite that produces the metabolite, even if the metabolite is non-essential Because it is also possible to produce other essential metabolites, if cell growth is inhibited due to inactivation of the metabolic reaction, it may be misunderstood that a non-essential metabolite is essential.
  • the primary essential metabolite of AYE (Acinetobacter baumannii AYE) obtained through the metabolic flow analysis step using Equations 1 and 2 above is (R) -4′-Phosphopantothenoyl-L-cysteine, (R ) -pantoate, (R) -Pantothenate, 1,4-dihydroxy-2-naphthoate, 1-Acyl-sn-glycerol 3-phosphate, 1-Deoxy-D-xylulose 5-phosphate, 2,3,4,5- Tetrahydrodipicolinate, 2,3-Dihydrodipicolinate, 2,5-Diamino-6-hydroxy-4- (5'-phosphoribosylamino) -pyrimidine, 2-Acyl-sn-glycero-3-phosphoethanolamine, 2-Amino-4-hydroxy-6 -(D-erythro-1,2,3-trihydroxypropyl) -7,8-dihydropteridine, 2-Amino-4-hydroxy-6
  • circulation metabolite (currency metabolite) involved in a number of enzyme reactions of various organisms.
  • Information on the metabolites in circulation is published in a paper published in Bioinformatics in 2003 (Ma and Zeng, Bioinformatics, 19: 1423, 2003), which do not have the specificity unique to the target microbial pathogen. Remove from the list of primary essential metabolites on the computer.
  • the result of removing the distribution metabolite from the first essential metabolite was named as a second essential metabolite.
  • At least two or more of the secondary essential metabolites are involved in the enzyme reaction, while at least two or more simultaneously name the metabolite when consuming the essential metabolite as the third essential metabolite.
  • This method has the advantage of simultaneously targeting the consuming enzymes when using a metabolite analogue (metabolite analogue) as a drug.
  • the biggest problem of anti-pathogen drugs is that the resistance of the pathogen to the drug occurs quickly, which is mainly caused by a single endogenous mutation of the enzyme target enzyme gene, thus the drug target gene group of the present invention.
  • the combination has the advantage of being able to simultaneously target several places of the target microbial pathogen metabolism to minimize the resistance of the pathogen, and to reliably control the growth of the pathogen in the host.
  • the present invention provides a metabolite in which at least two or more of the essential metabolites constituting the metabolic network model of the target microorganism are involved in at least three or more enzyme reaction equations, and at the same time, at least two or more of the metabolites are consumed. It is possible to provide an essential metabolite screening method characterized in that the screening.
  • acinetobacter Baumani used as an embodiment in the present invention, is a kind of multi-drug resistant (MDR) infectious bacteria that is resistant to many drugs, and the method of the present invention is such a multi-drug resistant pathogen. It suggests that it can be an effective method for attacking microorganisms.
  • MDR multi-drug resistant
  • the strategy is to ultimately disable the intake of essential metabolites from pathogens, thereby simultaneously inactivating all of the surrounding reactions, so even if the reactions are carried out by isoenzymes, it is not a problem.
  • the remaining metabolites are named 5th essential metabolites.
  • the host is a human
  • the essential metabolites predicted through the metabolic flow analysis are further screened based on the homology between the enzymes and the host proteins related to their consumption equations to further reduce the number of possible essential metabolites. .
  • drugs developed by targeting specific genes or enzymes act on the basis of the 'sequence' of the genes or enzymes. Therefore, if the genes or enzymes in these sequences are present in humans, the drugs also act on human proteins. May cause
  • the genomic information of the host is preferable to use as a database.
  • the BLASTP program may be used when using an amino acid sequence, or the BLAST program may be used when using a gene sequence.
  • any data can be used as long as those skilled in the art can identify homology regardless of amino acid sequence or gene sequence.
  • the present invention used the BLASTP program.
  • the human genomic information is used as a database.
  • the genes and amino acid sequences encoding all enzymes consuming each of the essential metabolites further selected in the present invention will be significantly different from those of the host protein, resulting in structural and functional differences with the host protein. Will be different.
  • step (4-1) step and / or (4-3) step; And step (4-2) may be selectively applied to step (4-4).
  • the pathogenic microorganism-specific essential metabolites can be finally determined, and the enzymes involved in these essential metabolites are determined as drug target enzyme groups.
  • genes encoding the drug target enzymes thus determined can be determined as a drug target gene group.
  • the fifth essential metabolite of AYE ( Acinetobacter baumannii AYE) used in the example of the present invention is 2-Amino-4-hydroxy-6-hydroxymethyl-7,8-dihydropteridine, D-Glutamate, 2,3-Dihydrodipicolinate, 2-Amino -4-hydroxy-6- (D-erythro-1,2,3-trihydroxypropyl) -7,8-dihydropteridine, 3-Dehydroshikimate, 1-Deoxy-D-xylulose 5-phosphate, 3-Dehydroquinate, 2-Dehydro- 3-deoxy-D-octonate, 4-Aminobenzoate and the like,
  • Drug target enzymes involved in metabolism include 2-amino-4-hydroxy-6-hydroxymethyldihydropteridine, pyrophosphokinase, dihydropteroate synthase, glutamate racemase, UDP-N-acetylmuramoylalanine--D-glutamate ligase, dihydrodipicolinate reductase, dihydroneopterin aldolase, alkaline phosphatase D precursor, 3-dehydroquinate dehydratase II, catabolic 3-dehydroquinate dehydratase (3-dehydroquinase), shikimate 5-dehydrogenase, quinate / shikimate dehydrogenase, 3-dehydroshikimate dehydratase, 1-deoxy-D-xylulose-5-phosphate reductoisomerase, pyridoxine 5-phosphate synthase, 3-deoxy-manno-octulosonate cytidylyltransferase, dihydropter
  • the present invention obtains a drug target enzyme candidate and a gene encoding the drug target enzyme of the microorganisms described above which are involved in the metabolism of essential metabolites at each step, which are obtained according to the screening method. Provide the military.
  • step (d) drug target enzyme candidates involved in the primary essential metabolite determined by the metabolic flow analysis of step (b) and the gene group encoding the same; drug target enzyme candidates involved in the secondary essential metabolite determined by removing the circulation metabolite of step (c) and the gene group encoding the same;
  • step (d) at least three or more enzyme reactions, and at least two or more at the same time the drug target enzyme candidates and genes encoding the enzymes involved in the selected third essential metabolite when the essential metabolite is consumed group; drug target enzyme candidates involved in the fourth essential metabolite determined by selecting only those not present in the metabolism of the host in step (e) and the gene group encoding the same;
  • step (f) a drug target enzyme candidate involved in the fifth essential metabolite determined by selecting a case where there is no homology with the host protein among enzymes related to metabolism of the fourth essential metabolite and a gene group encoding the same.
  • the present invention also relates to a method of using the determined enzyme group and the gene group encoding the same as the drug target of the target microorganism.
  • Such drug target enzymes and drug target genes according to the present invention obtain only the next effective drug target candidate groups for pathogenic diseases, and are useful for the treatment and prevention of diseases caused by microbial pathogens.
  • the constructed metabolic network of A. baumanii AYE consists of 891 biochemical schemes and 778 metabolites, and the information of this metabolic network contains the following 650 gene information.
  • the predicted drug targets were selected from these schemes.
  • Example 1 In the metabolic network constructed in Example 1, the effects of cells on the growth of cells when metabolism was not consumed by metabolic reactions of 778 metabolites of A. baumanii AYE, through metabolic flow analysis The metabolite's essentiality was determined by investigating.
  • the present invention relates to a methodology for predicting a drug target of a microorganism, and extracts the results according to the 'essential metabolite analysis' based on metabolic flow analysis to obtain only the next effective drug target candidates for diseases caused by pathogens. It is useful for the treatment and prevention of diseases caused by microbial pathogens. In particular, it is useful for the treatment and prevention of diseases caused by pathogenic microorganisms, such as pathogens with multi-drug resistance, such as acinetobacter Baumani.

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Abstract

Cette invention concerne un procédé de prédiction d'une cible médicamenteuse, et en particulier un procédé consistant : à sélectionner des micro-organismes ; à construire un modèle de réseau métabolique des micro-organismes sélectionnés ; à prédire un métabolite qui est essentiel pour la croissance cellulaire au moyen d'un procédé de détermination du caractère essentiel des métabolites ; à extraite le métabolite « courant » (currency metabolite) et le métabolite essentiel, dont le numéro de formule de réaction consommatrice ne satisfait pas aux exigences ; à sélectionner en outre le métabolite essentiel restant et un enzyme dégradant ce métabolite essentiel mais qui n'intervient pas dans un métabolisme hôte ; et, en conséquence, à cribler une enzyme pour cible médicamenteuse dans un micro-organisme pathogène ou un gène de cible médicamenteuse codant pour celui-ci.
PCT/KR2010/000162 2009-09-18 2010-01-11 Procédé de prédiction d'une cible médicamenteuse dans des micro-organismes pathogènes au moyen d'un métabolite essentiel WO2011034263A1 (fr)

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