WO2011034263A1

WO2011034263A1 - Method for predicting a drug target in pathogenic microorganisms using an essential metabolite

Info

Publication number: WO2011034263A1
Application number: PCT/KR2010/000162
Authority: WO
Inventors: 이상엽; 김현욱; 김태용
Original assignee: 한국과학기술원
Priority date: 2009-09-18
Filing date: 2010-01-11
Publication date: 2011-03-24
Also published as: WO2011034397A3; KR20110031143A; WO2011034397A2; KR101243378B1

Abstract

The present invention relates to a method for predicting a drug target in microorganisms, and more particularly, to a method comprising: selecting subject microorganisms; building a metabolic network model of the selected microorganisms; predicting a metabolite which is essential to cell growth by applying a metabolite essentiality method; removing currency metabolite and essential metabolite, the consuming reaction formula number of which falls short of a standard; additionally selecting the remaining essential metabolite and an enzyme which consumes essential metabolite but is not involved in a host metabolism; and accordingly, screening an efficient drug target enzyme in pathogenic microorganisms or a drug target gene encoding same.

Description

Drug target prediction method of pathogenic microorganism using essential metabolite

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.

However, it is difficult to determine which gene product is the ideal drug target to kill pathogenic microorganisms, and it is technically difficult to determine the lethality of the gene by deleting every single gene of the pathogenic microorganism. to be. In addition, drug targets are mostly determined by interactions between complex cellular components rather than a single gene, and each gene is considered to be lethal in multiple gene deletions even if it is not lethal. It becomes very difficult to predict.

Therefore, it is very important to understand the cellular mechanisms and interactions between microbial cell components in order to develop effective drugs that target pathogenic microorganisms. Therefore, the development of metabolites and metabolic networks through the development of genomic information and functional genomics has added the importance in understanding the interaction of genes and proteins to compose cellular components and constructing metabolic networks to develop effective drugs. .

Indeed, if metabolic network information through genomic information is used to identify new essential metabolic pathways that are not found in mammalian cells in pathogenic microorganisms, we have developed therapies that target these metabolic properties without causing adverse effects on human cells. Only pathogenic cells can be specifically attacked. It is also possible to develop drugs that inhibit these metabolic pathways if it is found that certain existing metabolic pathways are essential for survival of pathogenic microorganisms. When drugs against pathogenic microorganisms are developed, it is expected that drugs that inhibit other similar pathogenic microorganisms can be easily obtained using similar compounds.

Analytical and predictive techniques through metabolic networks have shown promise with rapidly growing genomic information. In particular, the metabolic network models of each microorganism have been combined with mathematical models and optimization techniques to make it possible to predict the response of the metabolic network after removal or addition of genes (Lee et al., Trends Biotechnol ., 23: 349, 2005 ). In addition, metabolic flow analysis techniques using metabolic networks are known to show the ideal metabolic flow of cells even when dynamic information is not required and to accurately simulate and predict cell behavior (Papin, J. et al., Nat. Rev. Mol. Cell Biol ., 6:99, 2005).

* 7 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.). In addition, 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. In addition, 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.

In the art, 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.

Therefore, 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. Of these, 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.

Summary of the Invention

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.

In order to achieve the above object, in the present invention

(a) selecting a target microorganism and building a metabolic network model of the selected microorganism;

(b) determining the specific metabolites as primary essential metabolites when the growth rate of the cell is zero while simultaneously blocking the consuming enzymatic reaction of specific metabolites in the established microbial metabolic network;

(c) of the primary essential metabolites determined in step (b),

Removing a current metabolite having no specificity with the microorganism of interest and selecting only those that are not present in the host's metabolism, each or all;

(d) If all of the enzymes consuming the essential metabolites determined in the previous step do not have homology with the host protein, determine the essential metabolites as the final essential metabolite, and determine the enzymes involved in the final essential metabolite. It provides a method for screening a drug target enzyme of a microorganism comprising the step of selecting a drug target enzyme of the.

Particularly, among the essential metabolites determined after step (c), 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. Can be.

Most preferably

(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);

(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; And

(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.

In addition, 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.

In this case, the host may be a human, and the target microorganism is preferably Escherichia coli or pathogenic microorganism, and more preferably pathogenic microorganism.

In addition, it is preferable that the metabolic network of the microorganism in step (a) is genomic level, and performing the step (b),

(i) expressing the constructed microbial metabolic network by using the following equation; And

[Revision under Rule 26 02.04.2010]
Equation 1

Where S is the change in X over time, X is the metabolite concentration, and t is the time.

(ii) using the following Equation 2, fixing the metabolic flow rate of the metabolite consumption equation to 0 and determining the case where the cell growth rate is 0 as the primary essential metabolite:

[Revision under Rule 26 02.04.2010]
Equation 2

(Where jm is a consumption equation of each metabolite; Vjm is a metabolic flow value of the corresponding consumption equation).

In particular, the application of the linear programming is preferably made by reflecting all the nutrient conditions necessary for the growth of cells.

In addition, 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.

In addition, 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.

In addition, the present invention

(a) establishing a metabolic network model of the genus Acinetobacter;

(b) the first essential metabolism of the specific metabolites when the cell growth rate is 0 while simultaneously blocking the enzymatic reaction of specific metabolites in the Acinetobacter genus microbial metabolic network Determining the products;

(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;

(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; And

(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.

In addition, 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.

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].

Detailed Description of the Invention and Preferred Embodiments

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.

1 illustrates the concept of an integrated drug targeting methodology in accordance with the present invention. In the methodology of the present invention, for example, 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).

Drug target enzyme screening method of the microorganism of the present invention

(d) determining the tertiary essential metabolite by considering the number of enzymatic reaction schemes involved and the number of enzymatic reaction schemes consumed;

(e) selecting only those that are not present in the host's metabolism to determine the fourth essential metabolite; And

(f) If all of the enzymes that consume the essential metabolites determined in the previous step do not have a homology with the host protein, determine those essential metabolites as the fifth essential metabolite and identify the enzymes involved in the fifth essential metabolite. Selecting a drug target enzyme of the subject microorganism.

At this time, in the method, 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.

In addition, 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. In general, there are usually more than 100 essential metabolites predicted through the analysis of essential metabolites, and it is very difficult to verify all of them experimentally, so the number of these needs to be reduced. Therefore, in the present invention, in order to maximize the effect of removing certain essential metabolites from the pathogen, the method of step (d) is devised in consideration of the number of reaction formulas that consume the essential metabolites.

That is, in the present invention, the steps are described as "(a)-(b)-(c)-(f)", "(a)-(b)-(e)-(f)", "(a)- (b)-(c)-(d)-(f) ”,“ (a)-(b)-(d)-(e)-(f) ”or“ (a)-(b)-(c )-(d)-(e)-(f) ”, which can be suitably carried out by those skilled in the art. However, it is most preferable to carry out by the aspect of "(a)-(b)-(c)-(d)-(e)-(f)".

Therefore, the method of one preferable aspect of this invention is as follows. That is, the present invention

(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.

Meanwhile, in the present invention, as a specific example, Acinetobacter genus microorganisms, for example, Acinetobacter baumannii, were used. Thus, in one aspect of the present invention, a method for screening drug target enzymes of the genus Acinetobacter may be provided, comprising the following steps:

(a) establishing a metabolic network model of the genus Acinetobacter;

(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.

In this case, too, the steps “(c) and / or (e); And (step (d)) may be selectively applied. The detailed description is as described above.

The detailed description of each step is as follows. In particular, the following description will focus on the most preferred aspects of the present invention.

(1) Metabolic network construction of target microorganism

"Metabolism" 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.

In the present invention, 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. In one embodiment of the present invention, 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.

In the method of the present invention, first, a metabolic network of microorganisms is established. At this time, it is desirable to construct a genome-level metabolic network using various known databases and experimental results. For example, you can build a network based on genes.

In one example of the present invention, a metabolic network model of Acinetobacter baumannii AYE was constructed and used. 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. 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. In adults, 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:

ABAYE0014, ABAYE0022, ABAYE0023, ABAYE0028, ABAYE0036, ABAYE0043, ABAYE0056, ABAYE0058, ABAYE0059, ABAYE0064, ABAYE0067, ABAYE0068, ABAYE0075, ABAYE0076, ABAYE0078, ABAYE0079, ABAYE0081, ABAYE0082, ABAYE0084, ABAYE0089, ABAYE0090, ABAYE0091, ABAYE0093, ABAYE0095, ABAYE0096, ABAYE0098, ABAYE0102, ABAYE0104, ABAYE0109, ABAYE0116, ABAYE0127, ABAYE0128, ABAYE0129, ABAYE0144, ABAYE0147, ABAYE0148, ABAYE0149, ABAYE0150, ABAYE0154, ABAYE0157, ABAYE0158, ABAYE0166, ABAYE0167, ABAYE0168, ABAYE0175, ABAYE0179, ABAYE0200, ABAYE0209, ABAYE0210, ABAYE0243, ABAYE0244, ABAYE0250, ABAYE0253, ABAYE0254, ABAYE0262, ABAYE0264, ABAYE0277, ABAYE0283, ABAYE0284, ABAYE0285, ABAYE0295, ABAYE0296, ABAYE0298, ABAYE0299, ABAYE0310, ABAYE0312, ABAYE0313, ABAYE0325, ABAYE0332, ABAYE0351, ABAYE0352, ABAYE0353, ABAYE0354, ABAYE0355, ABAYE0356, ABAYE0367, ABAYE0368, ABAYE0377, ABAYE0378, ABAYE0379, ABAYE0381, ABAYE0397, ABAYE0405, ABAYE0435, ABAYE0436, ABAYE0465, ABAYE0470, ABAYE0476, ABAYE0479, ABAYE0480, ABAYE0482, ABAYE0483, ABAYE0489, ABAYE0491, ABAYE0497, ABAYE0505, ABAYE0524, ABAYE0577, ABAYE0588, ABAYE0604, ABAYE0605, ABAYE0607, ABAYE0608, ABAYE0613, ABAYE0614, ABAYE0615, ABAYE0619, ABAYE0624, ABAYE0625, ABAYE0628, ABAYE0629, ABAYE0634, ABAYE0638, ABAYE0663, ABAYE0674, ABAYE0676, ABAYE0682, ABAYE0691, ABAYE0697, ABAYE0698, ABAYE0699, ABAYE0708, ABAYE0709, ABAYE0716, ABAYE0722, ABAYE0740, ABAYE0749, ABAYE0757, ABAYE0758, ABAYE0763, ABAYE0773, ABAYE0774, ABAYE0775, ABAYE0776, ABAYE0777, ABAYE0780, ABAYE0781, ABAYE0782, ABAYE0783, ABAYE0784, ABAYE0788, ABAYE0800, ABAYE0801, ABAYE0807, ABAYE0811, ABAYE0812, ABAYE0816, ABAYE0817, ABAYE0818, ABAYE0824, ABAYE0826, ABAYE0849, ABAYE0850, ABAYE0853, ABAYE0854, ABAYE0860, ABAYE0861, ABAYE0877, ABAYE0885, ABAYE0888, ABAYE0889, ABAYE0899, ABAYE0911, ABAYE0912, ABAYE0915, ABAYE0916, ABAYE0923, ABAYE0931, ABAYE0933, ABAYE0935, ABAYE0945, ABAYE0951, ABAYE0958, ABAYE0962, ABAYE0966, ABAYE0969, ABAYE0977, ABAYE0980, ABAYE0982, ABAYE1010, ABAYE1011, ABAYE1026 , ABAYE1027, ABAYE1028, ABAYE1030, ABAYE1039, ABAYE1047, ABAYE1052, ABAYE1066, ABAYE1067, ABAYE1083, ABAYE1094, ABAYE1098, ABAYE1103, ABAYE1104, ABAYE1106, ABAYE1113, ABAYE1114, ABAYE1115, ABAYE1118, ABAYE1119, ABAYE1123, ABAYE1126, ABAYE1127, ABAYE1128, ABAYE1138, ABAYE1141 , ABAYE132, ABAYE1145, ABAYE1147, ABAYE1171, ABAYE1199, ABAYE1204, ABAYE1206, ABAYE1207, ABAYE1209, ABAYE1223, ABAYE1278, ABAYE1280, ABAYE1295, ABAYE1296, ABAYE1354, ABAYE136 ABAYE136 , ABAYE1391, ABAYE1411, ABAYE1413, ABAYE1417, ABAYE1418, ABAYE1425, ABAYE1427, ABAYE1432, ABAYE1445, ABAYE1453, ABAYE1455, ABAYE1456, ABAYE1457, ABAYE1458, ABAYE1460, ABAYE1463, ABAYE1465, ABAYE1466, ABAYE1469, ABAYE1477, ABAYE1510, ABAYE1513, ABAYE1514, ABAYE1520, ABAYE1522 , ABAYE1526, ABAYE1537, ABAYE1538, ABAYE1539, ABAYE1544, ABAYE1546, ABAYE1562, ABAYE1563, ABAYE1567, ABAYE1569, ABAYE1571, ABAYE1577, ABAYE1580, ABAYE1581, ABAYE1585, ABAYE158 6, ABAYE1587, ABAYE1599, ABAYE1613, ABAYE1625, ABAYE1636, ABAYE1637, ABAYE1646, ABAYE1649, ABAYE1650, ABAYE1653, ABAYE1658, ABAYE1667, ABAYE1668, ABAYE1669, ABAYE1672, ABAYE1675 ABAYE1724, ABAYE1736, ABAYE1742, ABAYE1781, ABAYE1786, ABAYE1789, ABAYE1792, ABAYE1811, ABAYE1861, ABAYE1886, ABAYE1896, ABAYE1897, ABAYE1909, ABAYE1913, ABAYE1914, ABAYE1916, ABAYE1921, ABAYE1937, ABAYE1940, ABAYE1943, ABAYE1944, ABAYE1945, ABAYE1946, ABAYE1947, ABAYE1948, ABAYE1953, ABAYE1955, ABAYE1970, ABAYE1983, ABAYE1989, ABAYE1990, ABAYE1993, ABAYE1994, ABAYE2013, ABAYE2014, ABAYE2053, ABAYE2058, ABAYE2062, ABAYE2065, ABAYE2067, ABAYE2076, ABAYE2077, ABAYE2077, ABAYE2077, ABAYE2077, ABAYE2077, ABAYE 2077 ABAYE2181, ABAYE2184, ABAYE2188, ABAYE2191, ABAYE2209, ABAYE2219, ABAYE2220, ABAYE2227, ABAYE2246, ABAYE2248, ABAYE2250, ABAYE2270, ABAYE2288, ABAYE2290, ABAYE2291, ABAYE2392, ABAYE2292 04, ABAYE2306, ABAYE2307, ABAYE2310, ABAYE2311, ABAYE2317, ABAYE2318, ABAYE2329, ABAYE2333, ABAYE2342, ABAYE2344, ABAYE2366, ABAYE2367, ABAYE2368, ABAYE2369, ABAYE2370, ABAYE2377, ABAYE2377, ABAYE2377 ABAYE2481, ABAYE2483, ABAYE2491, ABAYE2493, ABAYE2533, ABAYE2562, ABAYE2566, ABAYE2577, ABAYE2578, ABAYE2589, ABAYE2592, ABAYE2593, ABAYE2594, ABAYE2595, ABAYE2596, ABAYE2601, ABAYE2606, ABAYE2607, ABAYE2613, ABAYE2614, ABAYE2618, ABAYE2628, ABAYE2630, ABAYE2631, ABAYE2641, ABAYE2646, ABAYE2663, ABAYE2666, ABAYE2678, ABAYE2764, ABAYE2767, ABAYE2771, ABAYE2776, ABAYE2777, ABAYE2778, ABAYE2783, ABAYE2790, ABAYE2791, ABAYE2794, ABAYE2799, ABAYE2803, ABAYE2809, ABAYE2810, ABAYE2819, ABAYE2822, ABAYE2823, ABAYE2824, ABAYE2829, ABAYE2832, ABAYE2836, ABAYE2837, ABAYE2838, ABAYE2843, ABAYE2845, ABAYE2852, ABAYE2867, ABAYE2868, ABAYE2869, ABAYE2871, ABAYE2878, ABAYE2905, ABAYE2909, ABAYE2910, ABAYE2927, ABAYE2928, ABAYE2929, ABAYE2929 940, ABAYE2951, ABAYE2955, ABAYE2958, ABAYE2964, ABAYE2969, ABAYE2976, ABAYE2981, ABAYE2984, ABAYE2987, ABAYE2992, ABAYE2993, ABAYE3001, ABAYE300, ABA3300, ABA300 ABAYE3047, ABAYE3048, ABAYE3049, ABAYE3050, ABAYE3051, ABAYE3052, ABAYE3053, ABAYE3054, ABAYE3055, ABAYE3056, ABAYE3057, ABAYE3058, ABAYE3059, ABAYE3060, ABAYE3065, ABAYE3067, ABAYE3078, ABAYE3079, ABAYE3086, ABAYE3097, ABAYE3101, ABAYE3104, ABAYE3105, ABAYE3114, ABAYE3129, ABAYE3130, ABAYE3131, ABAYE3132, ABAYE3133, ABAYE3151, ABAYE3153, ABAYE3154, ABAYE3159, ABAYE3160, ABAYE3169, ABAYE3174, ABAYE3175, ABAYE3176, ABAYE3179, ABAYE3181, ABAYE3184, ABAYE3186, ABAYE3187, ABAYE3188, ABAYE3191, ABAYE3192, ABAYE3193, ABAYE3228, ABAYE3238, ABAYE3239, ABAYE3240, ABAYE3244, ABAYE3250, ABAYE3258, ABAYE3262, ABAYE3263, ABAYE3267, ABAYE3269, ABAYE3272, ABAYE3276, ABAYE3278, ABAYE3280, ABAYE3281, ABAYE3282, ABAYE3283, ABAYE3284, ABAYE3284 3292, ABAYE3293, ABAYE3296, ABAYE3314, ABAYE3315, ABAYE3322, ABAYE3343, ABAYE3348, ABAYE3351, ABAYE3357, ABAYE3359, ABAYE3360, ABAYE3366, ABAYE3373, ABAYE3378, ABAYE3379, ABA428 ABAYE3470, ABAYE3471, ABAYE3497, ABAYE3498, ABAYE3507, ABAYE3508, ABAYE3511, ABAYE3518, ABAYE3519, ABAYE3524, ABAYE3530, ABAYE3531, ABAYE3537, ABAYE3540, ABAYE3544, ABAYE3546, ABAYE3568, ABAYE3572, ABAYE3588, ABAYE3612, ABAYE3614, ABAYE3616, ABAYE3644, ABAYE3661, ABAYE3670, ABAYE3671, ABAYE3675, ABAYE3678, ABAYE3696, ABAYE3697, ABAYE3713, ABAYE3715, ABAYE3716, ABAYE3717, ABAYE3718, ABAYE3719, ABAYE3720, ABAYE3721, ABAYE3723, ABAYE3731, ABAYE3732, ABAYE3740, ABAYE3750, ABAYE3763, ABAYE3764, ABAYE3766, ABAYE3767, ABAYE3768, ABAYE3773, ABAYE3774, ABAYE3791, ABAYE3792, ABAYE3793, ABAYE3795, ABAYE3796, ABAYE3797, ABAYE3800, ABAYE3801, ABAYE3802, ABAYE3803, ABAYE3804, ABAYE3807, ABAYE3814, ABAYE3815, ABAYE3823, ABAYE3825, ABAY E3834, ABAYE3835, ABAYE3839, ABAYE3846, ABAYE3851, ABAYE3852, ABAYE3871, ABAYE3872, ABAYE3885, ABAYE3887, p2ABAYE0004, p3ABAYE0020, p3ABAYE0024, p3ABAYE0029.

Therefore, in the following, a case of constructing a metabolic network model of AYE ( Acinetobacter baumannii AYE) has been described below.

(2) Execution of metabolic flow analysis

Next, 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).

For metabolic flow analysis, it is necessary to mathematically express 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. using a stoichiometric matrix) (the stoichiometric coefficient of the Sij, i of the second metabolite, the time in the j-th reaction), it is possible to calculate the metabolic flux vector _(j, j metabolic flux of the first metabolic reaction).

Equation 1

[Revision under Rule 26 02.04.2010]

Where S is the amount of change in X over time, X is the metabolite concentration, and t is the time.

At this 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.

In the above-described stoichiometric matrix, 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). In one embodiment of the present invention, 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.

On the other hand, 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.

In metabolic flow analysis based on the metabolic network of AYE ( Acinetobacter baumannii AYE) used in an example of the present invention, 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, Guanosine, L-Histidine, L-Histine Homoserine, Isocitrate, L-Isoleucine, Isomaltose, L-Leucine, L-Lysine, (S) -Malate, L-Methionine, Maltose, D-Mannitol, N-Acetyl-D-glucosamine, Sodium, NH ₃ , Nitrite, Nitrate , O ₂ , L-Ornithine, L-Phenylalanine, Orthophosphate, L-Proline, Putrescine, L-Serine, (S) -Lactate, Sulfate, Spermidine, Succinate, Sucrose, L-Threonine, alpha, alpha -Trehalose, L- Tryptophan, It may be selected from the group consisting of Taurine, L-Tyrosine, Uracil, Urea, Uridine, L-Valine, Xanthine and the like.

(3) Simulation of essential metabolite analysis using metabolic flow analysis and prediction of first essential metabolite

In general, in the conventional metabolic flow analysis, 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. However, in this case, in order to identify the cell growth deterioration phenomenon caused by the deletion of two or more genes, there has been a disadvantage in that all cases of two or more combinations must be calculated.

On the contrary, in 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).

Therefore, in the present invention, during the metabolic flow analysis process of the metabolites constituting the metabolic circuit of the target microorganism, all metabolic reactions consuming each metabolite are inactivated, that is, 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.

This is expressed as a formula below.

Equation 2

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Where j _m is the consumption equation of each metabolite and 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. 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.

During the analytical process 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.

For example, 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- (erythro-1,2,3-trihydroxypropyl) dihydropteridine triphosphate, 2-Amino-4 -hydroxy-6-hydroxymethyl-7,8-dihydropteridine, 2-Dehydro-3-deoxy-D-arabino-heptonate 7-phosphate, 2-Dehydro-3-deoxy-D-octonate, 2-Dehydro-3-deoxy- D-octonate 8-phosphate, 2-Dehydropantoate, 2-Demethylmenaquinone, 2-Oxobutanoate, 2-Oxoglutarate, 2-succinyl-6-hydroxy-2,4-cyclohexadiene-1-carboxylate, 3-Amino-2-oxopropyl phosphate, 3-Dehy droquinate, 3-Dehydroshikimate, 3-Hydroxy-4-phospho-hydroxy-alpha-ketobutyrate, 3-Methyl-2-oxobutanoic acid, 4,6-Dideoxy-4-oxo-dTDP-D-glucose, 4-amino-4 -deoxychorismate, 4-Aminobenzoate, 4-Phospho-D-erythronate, 5,10-Methylenetetrahydrofolate, 5-Amino-6- (5'-phosphoribitylamino) uracil, 5-Amino-6- (5'-phosphoribosylamino) uracil, 5 -Amino-6-ribitylamino-2,4 (1H, 3H) -pyrimidinedione, 5-O- (1-Carboxyvinyl) -3-phosphoshikimate, 5-Phospho-alpha-D-ribose 1-diphosphate, 6,7-Dimethyl -8- (1-D-ribityl) lumazine, Acetyl- [acyl-carrier protein], Acetyl-CoA, Acyl-carrier protein, ADP, all-trans-Octaprenyl diphosphate, alpha-D-Glucose, alpha-D-Glucose 6-phosphate, alpha-D-Mannose 1-phosphate, AMP, ATP, beta-Alanine, beta-D-Fructose 1,6-bisphosphate, beta-D-Fructose 6-phosphate, beta-D-Glucose, beta-hydroxy dodecanoic acid, beta-hydroxy tetradecanoic acid, Cardiolipin (biomass component), CDP, CDP-diacylglycerol, Chorismate, CO ₂ , CoA, Cofactors and vitamins, CTP, D-4'-Phosphopantothenate, dADP, D-alanine, D -alanyl-D-alanine, D-Arabinose 5-phosphate, dATP, dCDP, dCTP, Deamino-NAD ⁺ , Decanoyl- [acyl-carrier protein], Dephospho-CoA, D-Erythrose 4-phosphate, dGDP, D-Glucosamine 1-phosphate, D-Glucosamine 6-phosphate, D-Glucose 1-phosphate, D-Glutamate, D-Glyceraldehyde 3-phosphate, dGTP, Dihydrofolate, Dihydropteroate, D-Mannose 6-phosphate, DNA (biomass component), DNA 5 -methylcytosine, Dodecanoyl- [acyl-carrier protein], D-Ribose 5-phosphate, D-Ribulose 5-phosphate, dTDP, dTDP-4-dehydro-6-deoxy-L-mannose, dTDP-6-deoxy-L- mannose, dTDP-glucose, dTMP, dTTP, dUMP, Exopolysaccharide, Flavin adenine dinucleotide, FMN, GDP, GDP-mannose, Glycerone phosphate, Glycine, GMP, GTP, H2O2, HCO3, Heptadecanoyl- [acyl-carrier protein], Heptadecenoyl- [acyl-carrier protein], Hexadecanoyl- [acyl-carrier protein], Hexadecenoyl- [acyl-carrier protein], Iminoaspartate, IMP, Isochorismate, L, L-2,6-Diaminopimelate, L-3,4-Dihydroxy-2 -butanone 4-phosphate, L-Alanine, L-Arginine, L-Asparagine, L-Aspartate, L-Aspartate 4- semialdehyde, L-Cysteine, L-Glutamate, L-Glutamine, L-Histidine, Lipids other than phospholipid, Lippolysaccharide, L-Isoleucine, L-Leucine, L-Lysine, L-Methionine, L-Phenylalanine, L-Proline, L -Serine, L-Threonine, L-Tryptophan, L-Tyrosine, L-Valine, Malonyl- [acyl-carrier protein], Malonyl-CoA, menaquinol, menaquinone, meso-2,6-Diaminoheptanedioate, N6- (1,2 -Dicarboxyethyl) -AMP, N-Acetyl-D-glucosamine 1-phosphate, NAD ⁺ , NADP ⁺ , NADPH, NH ₃ , Nicotinate D-ribonucleotide, N-Succinyl-2-amino-6-oxopimelate, N-Succinyl-L -2,6-diaminopimelate, Octadecanoyl- [acyl-carrier protein], Octadecenoyl- [acyl-carrier protein], O-Phospho-4-hydroxy-L-threonine, Orthophosphate, O-succinylbenzoate, O-succinylbenzoate-CoA, Oxygen , Pantetheine 4'-phosphate, Pentadecanoyl- [acyl-carrier protein], Peptidoglycan (biomass component), Peptidoglycan precursor, Phosphatidate, Phosphatidylethanolamine, Phosphatidylglycerol, Phosphatidylglycerophosphate, Phosphatidylserine, Phosphosinospypymas s component), Propanoyl- [acyl-carrier protein], Propanoyl-CoA, Proteins, Pyridoxal, Pyridoxal 5'-phosphate, Pyridoxine, Pyridoxine 5'-phosphate, Pyruvate, Quinolinate, Riboflavin, RNA, S-Adenosyl-L-methionine , Shikimate, Shikimate 3-phosphate, sn-Glycerol 3-phosphate, Succinyl-CoA, Tetradecanoyl- [acyl-carrier protein], Tetrahydrofolate, Thioredoxin, Thioredoxin disulfide, Thymidine, Thymine, UDP, UDP-D-galactose, UDP-glucose , UDP-N-acetyl-3- (1-carboxyvinyl) -D-glucosamine, UDP-N-acetyl-D-galactosamine, UDP-N-acetyl-D-glucosamine, UDP-N-acetylmuramate, UDP-N-acetylmuramoyl -L-alanine, UDP-N-acetylmuramoyl-L-alanyl-D-gamma-glutamyl-meso-2,6-diaminopimelate, UDP-N-acetylmuramoyl-L-alanyl-D-glutamate, UDP-N-acetylmuramoyl-L -alanyl-D-glutamyl-6-carboxy-L-lysyl-D-alanyl-D-alanine, UMP, Undecaprenyl diphosphate, Undecaprenyl phosphate, Undecaprenyl-diphospho-N-acetylmuramoyl- (N-acetylglucosamine) -L-alanyl-D -glutaminyl-meso-2,6-diaminopimeloyl- (glycyl) 5-D-alanyl-D-alanine, Undecaprenyl-diphosp ho-N-acetylmuramoyl- (N-acetylglucosamine) -L-alanyl-D-glutaminyl-meso-2,6-diaminopimeloyl-D-alanyl-D-alanine, Undecaprenyl-diphospho-N-acetylmuramoyl- (N-acetylglucosamine)- L-alanyl-D-glutamyl-meso-2,6-diaminopimeloyl-D-alanyl-D-alanine, Undecaprenyl-diphospho-N-acetylmuramoyl-L-alanyl-D-glutamyl-meso-2,6-diaminopimeloyl-D- alanyl-D-alanine, UTP, and Xanthosine 5'-phosphate.

(4) Additional Screening of Essential Metabolites

4-1. Removal of Currency Metabolites

Among the essential metabolites determined in (3), there is a so-called 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.

4-2. Selection of essential metabolites involved in multiple reactions

Among the secondary essential metabolites determined by removing the circulation metabolite in (4-1) above, at least three or more reactions are involved, and at least two or more of these reactions consume the corresponding metabolites. Investigate if you do. Only those essential metabolites that meet the criteria are selected.

That is, 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.

Typically, 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.

As described above, 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.

In particular, 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.

4-3. Selection of essential metabolites that are not present in the host's metabolism

In order to minimize the possibility of adverse reactions that the host may receive from the drug, firstly, only the metabolites which are not present in the metabolism of the host among the tertiary essential metabolites determined in the above (4-2) are selected and the fourth essential metabolites are selected. Named as

For example, if the host is human, only those metabolites that are not present in human metabolism are selected from the tertiary essential metabolites determined in (4-2).

4-4. Select only those enzymes that are not consumed among essential metabolites by the host

And further selecting essential metabolites when all the enzymes involved in consuming each of the essential metabolites from the fourth essential metabolites determined in (4-3) consist only of those not homologous to the host protein. Perform the steps. In the present invention, 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.

As a result, the remaining metabolites are named 5th essential metabolites.

For example, if the host is a human, only those metabolites that do not have an enzyme in the human body that consumes any of the fourth essential metabolites, ie, have no homology with human proteins, are selected as the fifth essential metabolite.

In this step, 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. .

In particular, 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

Thus, if any of the enzymes in the consumption schemes in the essential metabolites are statistically similar to the protein of the host, the essential metabolites and their consumption schemes are no longer considered as drug targets.

At this stage, in examining the homology, it is preferable to use the genomic information of the host as a database.

For example, the BLASTP program may be used when using an amino acid sequence, or the BLAST program may be used when using a gene sequence. However, any data can be used as long as those skilled in the art can identify homology regardless of amino acid sequence or gene sequence. In one embodiment of the present invention used the BLASTP program. When targeting a human as a host, the human genomic information is used as a database.

By carrying out this step, 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.

In the above (4-3) and the present (4-4) process, as in the case of using the metabolite analogue as a drug, one drug simultaneously suppresses several enzyme consumption reaction schemes, but the protein does not exist in the host. Therefore, it can be said to minimize the possibility of side effects that can be received from drugs.

At this time, in the method, the “(4-1) step and / or (4-3) step; And step (4-2) may be selectively applied to step (4-4).

Through the above steps, 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. In addition, 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, dihydropteroate synthase can be determined, and drug target gene groups are ABAYE0036, ABAYE0082, ABAYE0377, ABAYE0807, ABAYE0811, ABAYE0945, ABAYE1417, ABAYE139, ABA1639, ABA16, ABA158 , ABAYE1685, ABAYE2076, ABAYE3176, ABAYE3395, ABAYE3524, ABAYE3568, ABAYE3612 and ABAYE3616 can be determined.

Furthermore, in another aspect, 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.

That is, 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; In 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; And (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.

In another aspect, 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.

Thus, in one aspect, the above-selected 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- Enzyme family of phosphate synthase, 3-deoxy-manno-octulosonate cytidylyltransferase, dihydropteroate synthase or ABAYE0036, ABAYE0082, ABAYE0377, ABAYE0807, ABAYE0811, ABAYE0945, ABAYE1417, ABAYE1418, AYE158, ABA1615, ABA1615, ABA16 The gene groups ABAYE3524, ABAYE3568, ABAYE3612, ABAYE3616 can be used as drug targets of AYE (Acinetobacter baumannii AYE).

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.

EXAMPLE

Hereinafter, the present invention will be described in more detail with reference to Examples. These examples are only for illustrating the present invention, and it will be apparent to those skilled in the art that the scope of the present invention is not to be construed as being limited by these examples. That is, the following steps are described as an example, and the scope of the present invention is not limited thereto.

In particular, the following examples are only illustrated for the drug target screening method using A. baumanii AYE as a model system, but it is apparent to those skilled in the art from the present disclosure that the present invention also applies to pathogenic microorganisms other than A. baumanii AYE. Do.

Example 1 Construction of a Metabolic Network of A. baumanii AYE

To predict the drug target of A. baumanii AYE using a computer, a genome-level metabolic network was constructed using various databases and experimental results.

KEGG (Kanehisa et al. Nucleic Acids Res, 34: D354, 2006), TransportDB (Ren et al., PLoS Comput. Biol ., 1: e27, 2005), MetaCyc (Caspi et al. Nucleic Acids Res ., 36 (D623, 2008), an early version of the metabolic network was established, and genomic information was used to clarify the relationship between the directionality and the gene protein of the enzyme reaction.

As shown in Table 1 below, 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.

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Table 1

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Example 2 Analysis of Essential Metabolites and Determination of Primary Essential Metabolites Using Metabolic Flow Analysis

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.

That is, in the metabolic flow analysis process of metabolites constituting the metabolic network of the target microorganism, all metabolic reactions consuming each metabolite are deleted, that is, the metabolic flow value of the corresponding reaction equation is fixed to 0 (= νj). When the objective function was set to maximize the cell growth rate, the cell growth rate of 0 was selected as an essential metabolite.

The nutrient intake equations are all fixed at -2 (= vj), so 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, Guanosine, L-Histidine, L-Homoserine, Isocitrate, L-Isoleucine, Isomaltose, L- Leucine, L-Lysine, (S) -Malate, L-Methionine, Maltose, D-Mannitol, N-Acetyl-D-glucosamine, Sodium, NH ₃ , Nitrite, Nitrate, O ₂ , L-Ornithine, L-Phenylalanine, Orthophosphate, L-Proline, Putrescine, L-Serine, (S) -Lactate, Sulfate, Spermidine, Succinate, Sucrose, L-Threonine, alpha, alpha-Trehalose, L-Tryptophan, Taurine, L-Tyrosine, Uracil, Urea, Uridine, L-Valine, Xanthine It was taken to be.

As a result, a total of 211 primary essential metabolites of Table 2 were determined through metabolic flow analysis.

TABLE 2

C180ACP, DMK, C171ACP, NAGA1P, D8RL, DHPANT, 5MC, 4PPNCYS, G3P, UMP, SME3P, DTDPRMNS, C170ACP, CAV, TYR, G1P, PGP, CDP, PI, PL, 3PSME, C140OH, PA, PG, PE, PS, UPPMN (GN) LADGMDDADA, OBUT, DUMP, TRP, C161ACP, UDP, DHSK, ACCOA, DTTP, HCO3, bALA, DHPT, TM, FMN, SDAPIM, H2O2, DATP, PEP, QA, DNA, ALAALA, MALCOA, OIVAL, bDGLC, ASUC, A5P, PYR, ILE, NADP, DQT, GDPMAN, NADPH, PRO, ASPSA, NACN, C120ACP, EXOPOLYS, IMP, NAAD, PPEPTIDO, OHB, O2, UDPNAMAG, DHP, DHF, CL, DHN, FAD, OSBCOA, CDPDG, MK, UTP, UDPG, DALA, DTDP4ORMNS, KDO, ATP, DT, PROTEIN, GL3P, DPCOA, PEPTIDO, C120OH, PANT, MKH2, ACACP, PHT, PYRDX, UDPGAL, DB4P, GLU, DADP, SHCHC, CHOR, PABA, UDPNAGEP, LPS, DAPIM, 3A2OP, MDAPIM, DTDPGLU, UPPMN (GN) LADGNMD (G) 5DADA, 2AG3PE, ASN, MAN6P, ASP, ICHOR, PRPP, OTHIO, CTP, MAN1P, XMP, ADCHOR, SME, AGL3P, DHDP, GA6P, NAD, ARG, DHAP, PNTO, LYS, C100ACP, SAOPIM, A6RP, SAM, GA1P, RTHIO, UDPAGLACA, DX5P, GTP, AKG, F6P, LEU, PPACOA, NH3, C150ACP, SER, DTMP, UPPMNLADGMDDADA, C160ACP, METTHF, DCDP, IASP, 4PPNT O, ALA, PHOSPHOLIPID, D6RP5P, GLY, ACP, GLC, GLN, DGTP, UDPMNLADGMDDADA, CYS, UDCPP, RIBFLAV, AMP, 4PPNTE, E4P, GMP, UDPNAMA, RL5P, PPAACP, G6P, P5P, FDP, DCTP, UPPN GN) LADGNMDDADA, A6RP5P2, A6RP5P, ADP, DTDP, DGLU, GDP, THF, VAL, R5P, THR, SUCCOA, AHHMP, DTDP4O6DG, RNA, PL5P, MET, C181ACP, C140ACP, MALACP, KDIP, AHTDAH HIS, TDHDP, OPP, DGDP, OSB, UDPNAG, UDPNAM, ER4P, PHE, UDCP, COA, UDPMNLADGMD, CO2

Example 3: Additional Screening of Essential Metabolites

For the essential metabolite determined through metabolic flow analysis in Example 2, those corresponding to the distribution metabolite were removed to obtain 179 secondary essential metabolites.

TABLE 3

AHHMP, DGLU, DHDP, DHP, DHSK, DX5P, DQT, KDO, PABA, ASPSA, C120OH, C140OH, C171ACP, CHOR, DMK, MDAPIM, MK, MKH2, OPP, PHT, PPAACP, SME, ACACP, ACCOA, ACP, AHTD, ARG, ASN, ASP, bALA, bDGLC, C100ACP, C120ACP, C140ACP, C150ACP, C160ACP, C161ACP, C170ACP, C180ACP, C181ACP, CDPDG, CYS, DADP, DALA, DCDP, DCTP, DGDP, DGTP, DHAP DTDP, DTDPGLU, DTDPRMNS, DTMP, DTTP, DUMP, E4P, F6P, FDP, FMN, G1P, G3P, G6P, GL3P, GLC, GLY, HCO3, HIS, ILE, LEU, LYS, MALACP, MET, NAAD, NACN, OBUT, OIVAL, PE, PEP, PG, PHE, PL, PPACOA, PRO, PRPP, PS, R5P, RL5P, SER, SUCCOA, THR, TRP, TYR, UDPG, UDPNAG, VAL, XMP, 2AG3PE, 3A2OP, 3DDAH7P, 3PSME, 4PPNCYS, 4PPNTE, 4PPNTO, 5MC, A5P, A6RP, A6RP5P, A6RP5P2, ADCHOR, AGL3P, ALAALA, ASUC, CAV, CL, D6RP5P, D8RL, DAPIM, DATP, DB4P, DHN, DHPANT, DCOA, DNA DT, DTDP4O6DG, DTDP4ORMNS, ER4P, EXOPOLYS, GA1P, GA6P, GDPMAN, IASP, ICHOR, KDOP, LIPID, LPS, MALCOA, MAN1P, MAN6P, NAGA1P, OHB, OSB, OSBCOA, P5P, PA, PANTGP PHOSPHOLIPID, PL5P, PNTO, PPEPTIDO, PROTEIN , PYRDX, QA, RIBFLAV, RNA, SAOPIM, SDAPIM, SHCHC, SME3P, TDHDP, TM, UDCP, UDCPP, UDPAGLACA, UDPGAL, UDPMNLADGMD, UDPMNLADGMDDADA, UDPNAGEP, UDPNAM, UDPNAMA, UDPNAMAG, UPPMN (GN) LADGN ) LADGNMD (G) 5DADA, UPPMN (GN) LADGNMDDADA, UPPMNLADGMDDADA

Of these secondary essential metabolites, they were associated with at least three or more reaction schemes, but two or more reaction schemes were further selected only to consume those essential metabolites to obtain 97 tertiary essential metabolites.

Table 4

AHHMP, DGLU, DHDP, DHP, DHSK, DX5P, DQT, KDO, PABA, ASPSA, C120OH, C140OH, C171ACP, CHOR, DMK, MDAPIM, MK, MKH2, OPP, PHT, PPAACP, SME, ACACP, ACCOA, ACP, AHTD, ARG, ASN, ASP, bALA, bDGLC, C100ACP, C120ACP, C140ACP, C150ACP, C160ACP, C161ACP, C170ACP, C180ACP, C181ACP, CDPDG, CYS, DADP, DALA, DCDP, DCTP, DGDP, DGTP, DHAP DTDP, DTDPGLU, DTDPRMNS, DTMP, DTTP, DUMP, E4P, F6P, FDP, FMN, G1P, G3P, G6P, GL3P, GLC, GLY, HCO3, HIS, ILE, LEU, LYS, MALACP, MET, NAAD, NACN, OBUT, OIVAL, PE, PEP, PG, PHE, PL, PPACOA, PRO, PRPP, PS, R5P, RL5P, SER, SUCCOA, THR, TRP, TYR, UDPG, UDPNAG, VAL, XMP

Finally, the remaining essential metabolites were selected only those that do not exist in the human body to obtain 22 quaternary metabolites.

Table 5

AHHMP, DGLU, DHDP, DHP, DHSK, DX5P, DQT, KDO, PABA, ASPSA, C120OH, C140OH, C171ACP, CHOR, DMK, MDAPIM, MK, MKH2, OPP, PHT, PPAACP, SME

Finally, their consumption equations were further screened based on homology with humans to further reduce the number of possible essential metabolites. If any of the enzymes in the consumption schemes of the essential metabolites are statistically similar to human proteins, the essential metabolites and their consumption schemes are no longer considered as drug targets.

As a result, the genes and amino acid sequences associated with all consumption reactions of each of the essential metabolites selected next are significantly different from those of human proteins, which are structurally and functionally different from human proteins.

[Revision under Rule 26 02.04.2010]
Table 6

As such, among the enzyme groups or gene groups screened by the method of the present invention, those skilled in the art can optionally use the drug target.

Having described the specific part of the present invention in detail, it is obvious to those skilled in the art that such a specific description is only a preferred embodiment, thereby not limiting the scope of the present invention. something to do. Therefore, the substantial scope of the present invention will be defined by the appended claims and their equivalents.

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.

Claims

A method for screening a drug target enzyme for a microorganism, comprising the following steps:

(a) selecting a target microorganism and building a metabolic network model of the selected microorganism;

(b) determining the specific metabolites as primary essential metabolites when the growth rate of the cell is zero while simultaneously blocking the consuming enzymatic reaction of specific metabolites in the established microbial metabolic network;

(c) of the primary essential metabolites determined in step (b),

Removing a current metabolite having no specificity with the microorganism of interest and selecting only those that are not present in the host's metabolism, each or all;

(d) If all of the enzymes consuming the essential metabolites determined in the previous step do not have homology with the host protein, determine the essential metabolites as the final essential metabolite, and determine the enzymes involved in the final essential metabolite. Selecting a drug target enzyme.
The method of claim 1, wherein the step of selecting a metabolite in the case where at least two or more of the essential metabolites determined after step (c) is involved in at least three or more enzyme reaction schemes and at the same time consumes the essential metabolites. The screening method, characterized in that further performing.
A method for screening a drug target enzyme for a microorganism, comprising the following steps:

(a) selecting a target microorganism and building a metabolic network model of the selected microorganism;

(b) determining the specific metabolites as primary essential metabolites when the growth rate of the cell is zero while simultaneously blocking the consuming enzymatic reaction of specific metabolites in the established microbial metabolic network;

(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);

(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; And

(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.
The method of claim 1 or 3, wherein the target microorganism is Escherichia coli or pathogenic microorganism.
4. The method of claim 1 or 3, wherein said host is a human.
4. A method according to claim 1 or 3, wherein in step (a) said metabolic network of microorganisms is at the genome level.
[Revision under Rule 26 02.04.2010]
The method of claim 1 or 3, wherein performing step (b) comprises: (i) using a linear programming method by expressing the constructed microbial metabolic network by the following equation; And equation 1
Where S is the amount of change of X over time, X is the concentration of metabolite, and t is the time. If the growth rate of 0 is determined as the first essential metabolite method: Equation 2
Where j m is the consumption equation of each metabolite; V jm is the metabolic flow value of the corresponding consumption equation.
8. The method of claim 7, wherein when applying the linear programming method, the objective function is set to maximize the cell growth rate.
8. The method of claim 7, wherein the application of the linear programming method reflects all the nutrient conditions necessary for the growth of the cell.
The method of claim 3, wherein in step (d), at least two or more of the secondary essential metabolites are involved in the enzymatic reaction, while at least two or more of the secondary metabolites consume the corresponding metabolite. Characterized in that it is determined as a product.
4. The method according to claim 1 or 3, wherein the examination of homology uses amino acid sequences or gene sequences.
12. The method of claim 11, wherein examining the homology is performed using a BLASTP program or a BLAST program.
A method of screening a drug target gene for a microorganism, characterized in that the gene groups encoding the drug target enzyme of the target microorganism selected from claim 1 or 3 are determined as the drug target gene of the target microorganism.
Enzymes of the target microorganism selected from claim 1 or 3; Or using the gene groups of the subject microorganism determined in claim 12 as drug targets of the subject microorganism.
A method for screening a drug target enzyme of a microorganism of the genus Acinetobacter , comprising the following steps:

(a) establishing a metabolic network model of the genus Acinetobacter ;

(b) metabolizing the specific metabolites in the Acinetobacter genus microbial metabolic network at the same time with the specific metabolites when the growth rate of the cell is zero; Determining the products;

(c) Among 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;

(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; And

(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 .
The method of claim 15, wherein the Acinetobacter (Acinetobacter) in the microorganism is characterized in that the Acinetobacter baumannii (Acinetobacter baumannii).
The method of claim 15, wherein said host is a human.
The method of claim 15, wherein the Acinetobacter genus microbial metabolic network construction in step (a) is ABAYE0014, ABAYE0022, ABAYE0023, ABAYE0028, ABAYE0036, ABAYE0043, ABAYE0056, ABAYE0058, ABAYE0059, ABAYE0064, ABAYE0067, ABAYE0067, ABAYE0067, ABAYE0067 , ABAYE0076, ABAYE0078, ABAYE0079, ABAYE0081, ABAYE0082, ABAYE0084, ABAYE0089, ABAYE0090, ABAYE0091, ABAYE0093, ABAYE0095, ABAYE0096, ABAYE0098, ABAYE0102, ABAYE0104, ABAYE0109, ABAYE0116, ABAYE0127, ABAYE0128, ABAYE0129, ABAYE0144, ABAYE0147, ABAYE0148, ABAYE0149, ABAYE0150 , ABAYE0154, ABAYE0157, ABAYE0158, ABAYE0166, ABAYE0167, ABAYE0168, ABAYE0175, ABAYE0179, ABAYE0200, ABAYE0209, ABAYE0210, ABAYE0243, ABAYE0244, ABAYE0250, ABAYE0253, ABAYE0254, ABAYE0262, ABAYE0264, ABAYE0277, ABAYE0283, ABAYE0284, ABAYE0285, ABAYE0295, ABAYE0296, ABAYE0298 , ABAYE0299, ABAYE0310, ABAYE0312, ABAYE0313, ABAYE0325, ABAYE0332, ABAYE0351, ABAYE0352, ABAYE0353, ABAYE0354, ABAYE0355, ABAYE0356, ABAYE0367, ABAYE0368, ABAYE0377, ABAYE0378, ABAYE0378 BAYE0379, ABAYE0381, ABAYE0397, ABAYE0405, ABAYE0435, ABAYE0436, ABAYE0465, ABAYE0470, ABAYE0476, ABAYE0479, ABAYE0480, ABAYE0482, ABAYE0483, ABAYE0489, ABAYE0491, ABAYE0497, ABAYE0505, ABAYE0524, ABAYE0577, ABAYE0588, ABAYE0604, ABAYE0605, ABAYE0607, ABAYE0608, ABAYE0613, ABAYE0614, ABAYE0615, ABAYE0619, ABAYE0624, ABAYE0625, ABAYE0628, ABAYE0629, ABAYE0634, ABAYE0638, ABAYE0663, ABAYE0674, ABAYE0676, ABAYE0682, ABAYE0691, ABAYE0697, ABAYE0698, ABAYE0699, ABAYE0708, ABAYE0709, ABAYE0716, ABAYE0722, ABAYE0740, ABAYE0749, ABAYE0757, ABAYE0758, ABAYE0763, ABAYE0773, ABAYE0774, ABAYE0775, ABAYE0776, ABAYE0777, ABAYE0780, ABAYE0781, ABAYE0782, ABAYE0783, ABAYE0784, ABAYE0788, ABAYE0800, ABAYE0801, ABAYE0807, ABAYE0811, ABAYE0812, ABAYE0816, ABAYE0817, ABAYE0818, ABAYE0824, ABAYE0826, ABAYE0849, ABAYE0850, ABAYE0853, ABAYE0854, ABAYE0860, ABAYE0861, ABAYE0877, ABAYE0885, ABAYE0888, ABAYE0889, ABAYE0899, ABAYE0911, ABAYE0912, ABAYE0915, ABAYE0916, ABAYE0923, ABAYE0931, ABAYE0933, ABAYE0935, ABAYE0945, ABAYE0951, ABAYE0958, ABAYE0962, ABAYE0966, ABAYE0969, ABAYE0977, ABAYE0980, ABAYE0982, ABAYE1010, ABAYE1011, ABAYE1026, ABAYE1027, ABAYE1028, ABAYE1030, ABAYE1039, ABAYE1047, ABAYE1052, ABAYE1066, ABAYE1067, ABAYE1083, ABAYE1094, ABAYE1098, ABAYE1103, ABAYE1104, ABAYE1106, ABAYE1113, ABAYE1114, ABAYE1115, ABAYE1118, ABAYE1119, ABAYE1123, ABAYE1126, ABAYE1127, ABAYE1128, ABAYE1138, ABAYE1141, ABAYE1142, ABAYE1145, ABAYE1147, ABAYE1171, ABAYE1199, ABAYE1204, ABAYE1206, ABAYE1207, ABAYE1209, ABAYE1223, ABAYE1278, ABAYE1280, ABAYE1295, ABAYE1296, ABAYE1354, ABAYE1356, ABAYE1362, ABAYE1366, ABAYE1367, ABAYE1380, ABAYE1385, ABAYE1386, ABAYE1387, ABAYE1388, ABAYE1389, ABAYE1391, ABAYE1411, ABAYE1413, ABAYE1417, ABAYE1418, ABAYE1425, ABAYE1427, ABAYE1432, ABAYE1445, ABAYE1453, ABAYE1455, ABAYE1456, ABAYE1457, ABAYE1458, ABAYE1460, ABAYE1463, ABAYE1465, ABAYE1466, ABAYE1469, ABAYE1477, ABAYE1510, ABAYE1513, ABAYE1514, ABAYE1520, ABAYE1522, ABAYE1526, ABAYE1537, ABAYE1538, ABAYE1539, ABAYE1544, ABAYE1546, ABAYE1562, ABAYE1563, ABAYE1567, ABAYE1569, ABAYE1571, ABAYE1577, ABAYE1580, ABAYE1581, ABAYE1585, ABAYE1586, ABAYE1587, ABAYE1599, ABAYE1613, ABAYE1625, ABAYE1636, ABAYE1637, ABAYE1646, ABAYE1649, ABAYE1650, ABAYE1653, ABAYE1658, ABAYE1667, ABAYE1668, ABAYE1669, ABAYE1672, ABAYE1675, ABAYE1682, ABAYE1683, ABAYE1685, ABAYE1700, ABAYE1706, ABAYE1710, ABAYE1712, ABAYE1715, ABAYE1724, ABAYE1736, ABAYE1742, ABAYE1781, ABAYE1786, ABAYE1789, ABAYE1792, ABAYE1811, ABAYE1861, ABAYE1886, ABAYE1896, ABAYE1897, ABAYE1909, ABAYE1913, ABAYE1914, ABAYE1916, ABAYE1921, ABAYE1937, ABAYE1940, ABAYE1943, ABAYE1944, ABAYE1945, ABAYE1946, ABAYE1947, ABAYE1948, ABAYE1953, ABAYE1955, ABAYE1970, ABAYE1983, ABAYE 1989, ABA191989 ABAYE2067, ABAYE2076, ABAYE2077, ABAYE2088, ABAYE2090, ABAYE2108, ABAYE2116, ABAYE2118, ABAYE2129, ABAYE2153, ABAYE2179, ABAYE2181, ABAYE2184, ABAYE2188, ABAYE2191, ABAYE2209 , ABAYE2219, ABAYE2220, ABAYE2227, ABAYE2246, ABAYE2248, ABAYE2250, ABAYE2270, ABAYE2288, ABAYE2290, ABAYE2291, ABAYE2292, ABAYE2304, ABAYE2306, ABAYE2307, ABAYE2310, ABAYE2311, ABAYE2317, ABAYE2318, ABAYE2329, ABAYE2333, ABAYE2342, ABAYE2344, ABAYE2366, ABAYE2367, ABAYE2368 , ABAYE2369, ABAYE2370, ABAYE2377, ABAYE2385, ABAYE2388, ABAYE2396, ABAYE2422, ABAYE2438, ABAYE2439, ABAYE2457, ABAYE2460, ABAYE2481, ABAYE2483, ABAYE2491, ABAYE2493, ABAYE2533, ABAYE2562, ABAYE2566, ABAYE2577, ABAYE2578, ABAYE2589, ABAYE2592, ABAYE2593, ABAYE2594, ABAYE2595 , ABAYE2596, ABAYE2601, ABAYE2606, ABAYE2607, ABAYE2613, ABAYE2614, ABAYE2618, ABAYE2628, ABAYE2630, ABAYE2631, ABAYE2641, ABAYE2646, ABAYE2663, ABAYE2666, ABAYE2678, ABAYE2764, ABAYE2767, ABAYE2771, ABAYE2776, ABAYE2777, ABAYE2778, ABAYE2783, ABAYE2790, ABAYE2791, ABAYE2794 , ABAYE2799, ABAYE2803, ABAYE2809, ABAYE2810, ABAYE2819, ABAYE2822, ABAYE2823, ABAYE2824, ABAYE2829, ABAYE2832, ABAYE2836, ABAYE2837, ABAYE2838, ABAYE2843, ABAYE2845, ABAYE285 2, ABAYE2867, ABAYE2868, ABAYE2869, ABAYE2871, ABAYE2878, ABAYE2905, ABAYE2909, ABAYE2910, ABAYE2927, ABAYE2928, ABAYE2929, ABAYE2940, ABAYE2951, ABAYE2955, ABAYE2958, ABAYE2964, ABAYE2964, ABAYE2964 ABAYE2993, ABAYE3001, ABAYE3003, ABAYE3004, ABAYE3006, ABAYE3007, ABAYE3015, ABAYE3016, ABAYE3025, ABAYE3028, ABAYE3031, ABAYE3037, ABAYE3047, ABAYE3048, ABAYE3049, ABAYE3050, ABAYE3051, ABAYE3052, ABAYE3053, ABAYE3054, ABAYE3055, ABAYE3056, ABAYE3057, ABAYE3058, ABAYE3059, ABAYE3060, ABAYE3065, ABAYE3067, ABAYE3078, ABAYE3079, ABAYE3086, ABAYE3097, ABAYE3101, ABAYE3104, ABAYE3105, ABAYE3114, ABAYE3129, ABAYE3130, ABAYE3131, ABAYE3132, ABAYE3133, ABAYE3151, ABAYE3153, ABAYE3154, ABAYE3159, ABAYE3160, ABAYE3169, ABAYE3174, ABAYE3175, ABAYE3176, ABAYE3179, ABAYE3181, ABAYE3184, ABAYE3186, ABAYE3187, ABAYE3188, ABAYE3191, ABAYE3192, ABAYE3193, ABAYE3228, ABAYE3238, ABAYE3239, ABAYE3240, ABAYE3244, ABAYE3250, ABAYE3258, ABAYE3258, 62, ABAYE3263, ABAYE3267, ABAYE3269, ABAYE3272, ABAYE3276, ABAYE3278, ABAYE3280, ABAYE3281, ABAYE3282, ABAYE3283, ABAYE3284, ABAYE3292, ABAYE3293, ABAYE3296, ABAYE33, ABAYE3315, ABAYE3315 ABAYE3373, ABAYE3378, ABAYE3379, ABAYE3393, ABAYE3395, ABAYE3424, ABAYE3426, ABAYE3428, ABAYE3429, ABAYE3443, ABAYE3447, ABAYE3463, ABAYE3470, ABAYE3471, ABAYE3497, ABAYE3498, ABAYE3507, ABAYE3508, ABAYE3511, ABAYE3518, ABAYE3519, ABAYE3524, ABAYE3530, ABAYE3531, ABAYE3537, ABAYE3540, ABAYE3544, ABAYE3546, ABAYE3568, ABAYE3572, ABAYE3588, ABAYE3612, ABAYE3614, ABAYE3616, ABAYE3644, ABAYE3661, ABAYE3670, ABAYE3671, ABAYE3675, ABAYE3678, ABAYE3696, ABAYE3697, ABAYE3713, ABAYE3715, ABAYE3716, ABAYE3717, ABAYE3718, ABAYE3719, ABAYE3720, ABAYE3721, ABAYE3723, ABAYE3731, ABAYE3732, ABAYE3740, ABAYE3750, ABAYE3763, ABAYE3764, ABAYE3766, ABAYE3767, ABAYE3768, ABAYE3773, ABAYE3774, ABAYE3791, ABAYE3792, ABAYE3793, ABAYE3795, 796, ABAYE3797, ABAYE3800, ABAYE3801, ABAYE3802, ABAYE3803, ABAYE3804, ABAYE3807, ABAYE3814, ABAYE3815, ABAYE3823, ABAYE3825, ABAYE3834, ABAYE3835, ABAYE3839, ABAYE3846, ABAYE3851, ABAYE3852, ABAYE3871, ABAYE3872, ABAYE3885, ABAYE3887, p2ABAYE0004, p3ABAYE0020, p3ABAYE0024, method based on a gene family consisting of p3ABAYE0029.
[Revision under Rule 26 02.04.2010]
The method of claim 15, wherein performing step (b) comprises: (i) using the linear programming method by expressing the constructed Acinetobacter genus microbial metabolic network with the following equation, wherein the linear The application of the scheme is characterized by the reflection of all the nutrient conditions necessary for the growth of the cell; And equation 1
Where S is the amount of change of X over time, X is the concentration of metabolite, and t is the time. The method comprising the step of determining if the growth rate of 0 as the first essential metabolite: Equation 2
Where j m is the consumption equation of each metabolite; V jm is the metabolic flow value of the corresponding consumption equation.
The method of claim 19, wherein the nutrient is 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, Guanosine, L-Histidine, L-Homoserine, Isocitrate, L-Isoleucine, Isomaltose, L-Leucine, L-Lysine, (S ) -Malate, L-Methionine, Maltose, D-Mannitol, N-Acetyl-D-glucosamine, Sodium, NH 3 , Nitrite, Nitrate, O 2 , L-Ornithine, L-Phenylalanine, Orthophosphate, L-Proline, Putrescine, As L-Serine, (S) -Lactate, Sulfate, Spermidine, Succinate, Sucrose, L-Threonine, alpha, alpha-Trehalose, L-Tryptophan, Taurine, L-Tyrosine, Uracil, Urea, Uridine, L-Valine and Xanthine Characterized in that selected from the group consisting Way.
The method of claim 15, wherein the primary essential metabolite obtained in step (b) 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- (erythro-1,2,3-trihydroxypropyl) dihydropteridine triphosphate, 2-Amino-4-hydroxy-6-hydroxymethyl-7,8-dihydropteridine, 2- Dehydro-3-deoxy-D-arabino-heptonate 7-phosphate, 2-Dehydro-3-deoxy-D-octonate, 2-Dehydro-3-deoxy-D-octonate 8-phosphate, 2-Dehydropantoate, 2-Demethylmenaquinone, 2-Oxobutanoate, 2-Oxoglutarate, 2-succinyl-6-hydroxy-2,4-cyclohexadiene-1-carboxylate, 3-Amino-2-oxopropyl phosphate, 3-Dehydroquinate, 3-Dehydroshikimate, 3-Hydroxy-4-phospho -hydroxy-alpha-ketobutyrate, 3-Methyl -2-oxobutanoic acid, 4,6-Dideoxy-4-oxo-dTDP-D-glucose, 4-amino-4-deoxychorismate, 4-Aminobenzoate, 4-Phospho-D-erythronate, 5,10-Methylenetetrahydrofolate, 5- Amino-6- (5'-phosphoribitylamino) uracil, 5-Amino-6- (5'-phosphoribosylamino) uracil, 5-Amino-6-ribitylamino-2,4 (1H, 3H) -pyrimidinedione, 5-O- ( 1-Carboxyvinyl) -3-phosphoshikimate, 5-Phospho-alpha-D-ribose 1-diphosphate, 6,7-Dimethyl-8- (1-D-ribityl) lumazine, Acetyl- [acyl-carrier protein], Acetyl- CoA, Acyl-carrier protein, ADP, all-trans-Octaprenyl diphosphate, alpha-D-Glucose, alpha-D-Glucose 6-phosphate, alpha-D-Mannose 1-phosphate, AMP, ATP, beta-Alanine, beta- D-Fructose 1,6-bisphosphate, beta-D-Fructose 6-phosphate, beta-D-Glucose, beta-hydroxy dodecanoic acid, beta-hydroxy tetradecanoic acid, Cardiolipin (biomass component), CDP, CDP-diacylglycerol, Chorismate, CO 2 , CoA, Cofactors and vitamins, CTP, D-4'-Phosphopantothenate, dADP, D-alanine, D-alanyl-D-alanine, D-Arabinose 5-phosphate, dATP, dCDP, dCTP, Deamino-NAD + , Decanoyl- [ acyl-carrier protein], Dephospho-CoA, D-Erythrose 4-phosphate, dGDP, D-Glucosamine 1-phosphate, D-Glucosamine 6-phosphate, D-Glucose 1-phosphate, D-Glutamate, D-Glyceraldehyde 3-phosphate , dGTP, Dihydrofolate, Dihydropteroate, D-Mannose 6-phosphate, DNA (biomass component), DNA 5-methylcytosine, Dodecanoyl- [acyl-carrier protein], D-Ribose 5-phosphate, D-Ribulose 5-phosphate, dTDP, dTDP-4-dehydro-6-deoxy-L-mannose, dTDP-6-deoxy-L-mannose, dTDP-glucose, dTMP, dTTP, dUMP, Exopolysaccharide, Flavin adenine dinucleotide, FMN, GDP, GDP-mannose, Glycerone phosphate , Glycine, GMP, GTP, H 2 O 2 , HCO 3 , Heptadecanoyl- [acyl-carrier protein], Heptadecenoyl- [acyl-carrier protein], Hexadecanoyl- [acyl-carrier protein], Hexadecenoyl- [acyl-carrier protein] , Iminoaspartate, IMP, Isochorismate, L, L-2,6-Diaminopimelate, L-3,4-Dihydroxy-2-butanone 4-phosphate, L-Alanine, L-Arginine, L-Asparagine, L-Aspartate, L- Aspartate 4-semialdehyde, L-Cysteine, L-Glutamate, L-Glutamine, L-Histidine, Lipids other than phospholipid, Lippolysaccharide, L-Isoleucine, L-Leucine, L-Lysine, L-Methionine, L-Phenylalanine, L-Proline, L-Serine, L-Threonine, L-Tryptophan, L-Tyrosine, L-Valine, Malonyl- [acyl-carrier protein], Malonyl-CoA, menaquinol, menaquinone, meso-2,6-Diaminoheptanedioate, N6- (1,2-Dicarboxyethyl) -AMP, N-Acetyl-D-glucosamine 1-phosphate, NAD +, NADP +, NADPH, NH3, Nicotinate D-ribonucleotide, N-Succinyl-2-amino-6-oxopimelate, N-Succinyl-L-2,6-diaminopimelate, Octadecanoyl- [acyl-carrier protein], Octadecenoyl- [acyl-carrier protein] , O-Phospho-4-hydroxy-L-threonine, Orthophosphate, O-succinylbenzoate, O-succinylbenzoate-CoA, Oxygen, Pantetheine 4'-phosphate, Pentadecanoyl- [acyl-carrier protein], Peptidoglycan (biomass component), Peptidoglycan precursor Phosphatidate, Phosphatidylethanolamine, Phosphatidylglycerol, Phosphatidylglycerophosphate, Phosphatidylserine, Phosphoenolpyruvate, Phospholipids (biomass component), Propanoyl- [acyl-carrier protein], Propanoyl-CoA, Proteins, Pyrridoxal idoxal 5'-phosphate, Pyridoxine, Pyridoxine 5'-phosphate, Pyruvate, Quinolinate, Riboflavin, RNA, S-Adenosyl-L-methionine, Shikimate, Shikimate 3-phosphate, sn-Glycerol 3-phosphate, Succinyl-CoA, Tetradecanoyl- [acyl-carrier protein], Tetrahydrofolate, Thioredoxin, Thioredoxin disulfide, Thymidine, Thymine, UDP, UDP-D-galactose, UDP-glucose, UDP-N-acetyl-3- (1-carboxyvinyl) -D-glucosamine, UDP- N-acetyl-D-galactosamine, UDP-N-acetyl-D-glucosamine, UDP-N-acetylmuramate, UDP-N-acetylmuramoyl-L-alanine, UDP-N-acetylmuramoyl-L-alanyl-D-gamma-glutamyl- meso-2,6-diaminopimelate, UDP-N-acetylmuramoyl-L-alanyl-D-glutamate, UDP-N-acetylmuramoyl-L-alanyl-D-glutamyl-6-carboxy-L-lysyl-D-alanyl-D- alanine, UMP, Undecaprenyl diphosphate, Undecaprenyl phosphate, Undecaprenyl-diphospho-N-acetylmuramoyl- (N-acetylglucosamine) -L-alanyl-D-glutaminyl-meso-2,6-diaminopimeloyl- (glycyl) 5-D-alanyl-D -alanine, Undecaprenyl-diphospho-N-acetylmuramoyl- (N-acetylglucosamine) -L-alanyl-D-glutaminyl-meso-2,6-diaminopimeloyl -D-alanyl-D-alanine, Undecaprenyl-diphospho-N-acetylmuramoyl- (N-acetylglucosamine) -L-alanyl-D-glutamyl-meso-2,6-diaminopimeloyl-D-alanyl-D-alanine, Undecaprenyl-diphospho -N-acetylmuramoyl-L-alanyl-D-glutamyl-meso-2,6-diaminopimeloyl-D-alanyl-D-alanine, UTP, and Xanthosine 5'-phosphate.
The method of claim 15, wherein the fifth essential metabolite 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.
Drug target enzymes of the genus Acinetobacter selected according to the method of claim 15 are 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 dedeoxyatase One or more Acinetobacter genus microbial enzymes selected from the group consisting of D-xylulose-5-phosphate reductoisomerase, pyridoxine 5-phosphate synthase, 3-deoxy-manno-octulosonate cytidylyltransferase, and dihydropteroate synthase How to use.
Acinetobacter ( Acinetobacter ) characterized in that the gene group encoding the drug target enzyme of the genus Acinetobacter ( Acinetobacter ) selected according to the method as a drug target gene of the microorganism of the genus Acinetobacter , Acinetobacter ) Screening method of drug target gene for the microorganism of the genus.
ABAYE0036, ABAYE0082, ABAYE0377, ABAYE0907, ABAYE1417, ABAYE1418, ABAYE1539, ABAYE1581, ABAYE1682, ABAYE1683, ABAYE1685, AYEYE, 176, ABA395, ABA395, ABA35 A method for using drug targets of at least one Acinetobacter genus microbial gene selected from the group.
Essential metabolites, which participate in at least three or more enzymatic reaction formulas of the metabolic network model of the target microorganism, and at least two or more simultaneously select the metabolites when the essential metabolites are consumed. Product screening method.