BACKGROUND
in the past few decades, various systematic methods have been developed for the prediction of synthetic metabolic pathways for the production of chemicals by employing microorganisms  <cit> .
these methods can be classified by whether the approach is based on chemical structural changes, enzymatic information, and/or reaction mechanisms.
the method based on chemical structural changes is applied to reconstruct the network which represents the relationship among the biochemical compounds using the structure-based homology analysis  <cit> .
this method generates a variety of novel pathways, but prediction to specify the enzymes is difficult.
enzymatic information-based approach focuses on combination of gene knock outs and additions of pathways existing in different organisms  <cit> .
this method is practical to use, but predictions are limited to the synthesis of currently known biochemical compounds.
reaction mechanisms-based approach identifies product candidates that can be driven from a predetermined substrate using a knowledge-based expert system  <cit> .
this method predicts novel pathways and compounds according to the accumulated knowledge and rules, but it is limited to identifying biodegradation pathways.
to overcome the disadvantages of the aforementioned methods, the pathway prediction systems were established by combining the given reaction mechanisms and the starting and target compounds  <cit> .
these approaches can generate novel compounds and reactions with proposed enzyme candidates.
however, the starting and target compounds should be set as known compounds, and thus this method is difficult to be applied to the prediction of a synthetic pathway for a novel compound of interest.
a retrosynthesis model, which is a functional group-based synthesis method towards a target compound, has been applied to search desired target chemicals  <cit> .
however, the previous studies provided a huge set of predicted pathways, rather than suggesting more favorable pathways to achieve a goal of efficiently producing a desired chemical.
in this study, a system framework was developed to suggest promising enzyme candidates to synthesize desired chemicals based on combined information on chemical structural changes, enzyme characteristics, and reaction mechanisms.
the proposed system framework identifies structurally qualified enzymes for the synthesis of predetermined target chemicals and then ranks the enzymes via a prioritization scoring algorithm.
recently, a nice scoring technique to identify preferred pathways by using an automatic design approach for the metabolic pathways has been suggested  <cit> ; a scoring algorithm was developed for identifying a possible route from a considered host organism.
however, this approach cannot be applied to the novel pathways which are not present in the database.
thus, a new scoring algorithm was developed in this paper for the identification of desired novel synthetic pathways.
consequently, the more efficient metabolic pathways for the production of a desired chemical can be proposed.
RESULTS
using the system framework developed in this study, the novel synthetic pathways for the production of isobutanol, 3-hydroxypropionate , and butyryl-coa were predicted.
in summary, the steps composed of definition of a target compound, route generation, prioritization, and parameter optimization were taken to predict the novel synthetic pathways.
the prediction shows a high reliability, in which experimentally verified pathways for the synthesis of isobutanol, 3hp, and butyryl-coa belonged to top  <dig> %,  <dig> %, and  <dig> % of all the predicted pathway candidates, respectively.
prediction of synthetic pathways of the production of biofuels and evolutionary parameter optimization
recently, atsumi et al.
reported novel metabolic engineering strategies for the production of higher alcohols such as 1-propanol, 1-butanol, 2-methy-1-butanol, 3-methy-1-butanol, isobutanol, and 2-phenylethanol in escherichia coli  <cit> .
the six pathways were devised involving two well-known enzymes, 2-keto-acid decarboxylase  and alcohol dehydrogenase , which is based on the reaction mechanism that 2-keto acids can be converted to aldehydes and then to alcohol.
to testify their work, the system framework was employed.
the key novel synthetic pathways are presented in figure  <dig>
initially, for example, the structure of the target compound, isobutanol, was entered in the form of smiles  <cit> .
then, predefined reaction rules were applied to the target compound for generating substrates.
the generated substrates were regarded as intermediate target compounds, and the reaction rules were applied again.
the recursive generation step was completed when the generation loop has reached the predefined limit.
throughout the loop, various routes for the production of target compound were generated.
the system then detects known chemicals and displays them so as to select a starting compound .
the referred reaction rules are shown in figure 2b.
among the detected known chemicals, 2-ketoisovalerate was selected as the starting compound.
after the starting compound was determined, the routes from the starting compound to the target compound were retrieved for further analysis.
the routes for the production of the target compound are defined as the base routes.
the identified base routes for the synthesis of the isobutanol are shown in the bottom of figure 2a.
using the mechanisms defined in every reaction step of base routes, the biochemical reactions in the kegg database  <cit>  were classified into the individual groups.
finally, all the routes from the starting compound to the target compound defined as the reaction route candidates were determined by combination of the reactions in each group.
as shown in figure  <dig>  two base routes for the synthesis of isobutanol were identified and two groups,  <dig> reactions in b.co.
<dig> and  <dig> reactions in b.c.
<dig> , were classified for each base route.
finally,  <dig>  reaction route candidates were determined.
next, a prioritization method was applied to decide which route candidates are preferred by estimating five priority factors: binding site covalence, chemical similarity, thermodynamic favorability, pathway distance, and organism specificity.
throughout the prioritization step, reaction route candidates were rearranged into enzyme-based routes which were defined as enzyme route candidates.
if multiple reactions are related to one enzyme, the values of binding site covalence and chemical similarity of the enzyme are determined by the highest values of those of the related reactions.
figure  <dig> shows the results of prioritization by the estimation of five factors for the synthesis of isobutanol.
finally, the preference of each enzyme route candidate was determined as a score calculated by the weighted sum of each factor .
in the initial predictions, the six pathways were positioned within top  <dig> % of the predicted candidates.
specially, isobutanol was within top  <dig> % as the best result.
from the initial prediction results, each three factor including thermodynamic favorability, pathway distance, and organism specificity is consistent for the six pathways.
the other hand, the other factors including binding site covalence and chemical similarity are varied.
it is caused that the same enzymes are applied to design the six pathways.
among the results of atsumi et al.
<cit> , the production rate of isobutanol was at least three times higher than the production rates of other higher alcohols.
also, the predicted rank for the synthetic pathway via kdc and adh for the production of isobutanol is higher than other pathways.
therefore, the pathway was considered to be more suitable to produce isobutanol.
for the accurate estimate of the relative influence of each factor which is expressed as a parameter, novel synthetic pathway for the production of isobutanol is selected.
to identify the optimal parameters, the evolutionary parameter optimization shown as equation  <dig> in methods was performed  <cit> .
when the parameter values of  <dig> were used without optimization, the experimentally proven synthetic pathways of isobutanol was ranked at the 20th out of  <dig>  enzyme route candidates.
after the evolutionary parameter optimization, the parameter set was changed from { <dig>   <dig>   <dig>   <dig>  1} to { <dig> ,  <dig> ,  <dig> ,  <dig> ,  <dig> } and the rank of the synthetic pathway was improved to the 17th .
the ranks of six pathways were improved within top  <dig> % of the predicted candidates than the initial predictions positioned within top  <dig> % as mentioned above.
in addition, there were enzyme route candidates that always have higher values in the final priority scores than those of the experimentally proven pathways .
it means that they have the superior values in all factors.
thus, the superior enzyme route candidates might be used as superior synthetic pathways for more efficient production of the target chemical.
enzyme route candidates have higher values in all factors compared to the experimentally identified pathways.
prediction of synthetic pathways for the production of 3hp
to examine the performance of the system framework developed in this study, the synthetic pathways for the production of 3hp were predicted as another example.
3hp is one of the top value added chemicals suggested by the u.s. department of energy  <cit> .
other than the suggested seven metabolic pathways for the production of 3hp from glucose  <cit> , alternative pathways from acryloyl-coa were identified.
the structure of 3hp and its existing and alternative synthetic pathways from acryloyl-coa are shown in figure 6a.
to identify the synthetic pathways for the production of 3hp from acryloyl-coa, two base routes shown in figure 6b and  <dig>  reaction route candidates were generated.
next, reaction route candidates were further analyzed quantitatively in order to identify more promising routes by employing a prioritization algorithm.
during the prioritization,  <dig>  enzyme route candidates were generated and evaluated.
the experimentally proven synthetic pathway from acryloyl-coa to 3hp through ec <dig> .
<dig>  and ec <dig> .
<dig>  was ranked at the second out of  <dig>  enzyme route candidates .
since the existing pathway is superior enzyme route candidate of the experimentally proven pathway, evolutionary optimization does not change the parameter values and the rank.
this result demonstrates the efficiency and reliability of the developed system framework for identifying novel synthetic pathways for the production of desired chemicals.
prediction of alternative synthetic pathways for the production of 1-butanol
in this paper, the alternative synthetic pathway for the production of 1-butanol from 2-ketovalerate  <cit> , as atsumi et al.
presented, has been identified.
since the two step synthetic pathway for the production of 1-butanol from butyryl-coa already exists in kegg database, the synthetic pathways to the butyryl-coa were explored.
the constructed alternative pathways with base routes are shown in figure  <dig>  during the route generation process,  <dig>  reaction route candidates and  <dig>  enzyme route candidates were identified.
the enzyme route candidates are quantitatively analyzed by the prioritization method and the resulting top  <dig> pathways are shown in table  <dig>  among the top  <dig> pathways, the 8th ranked enzyme route candidate, a novel pathway via ec <dig> .
<dig>  and ec <dig> .
<dig> , was successfully synthesized to produce butyryl-coa from 2-ketoisovalerate.
this pathway is structurally identical compared to the existing pathway; however, no organism has been found to produce the butyryl-coa via the enzymes.
in other words, the pathway obtained lower score in the organism specificity.
that is the reason why the pathway is ranked at the 8th.
after the evolutionary optimization, the rank is slightly changed to the 7th and the parameter set is changed to { <dig> ,  <dig> ,  <dig> ,  <dig> ,  <dig> }.
through this work, the novel alternative synthetic pathway for the production of 1-butanol has been identified.
this study demonstrates the applicability of the developed method and system framework.
xb is the binding site covalence, xc is the chemical similarity, xt is the thermodynamic favorability, xp is the pathway distance, and xo is the organism specificity.
the final priority x is evaluated by equation 6a with the previously estimated parameter set { <dig> ,  <dig> ,  <dig> ,  <dig> ,  <dig> }.
6th ranked enzyme route candidate is the superior set of the experimentally proven pathway which is ranked at the 8th.
CONCLUSIONS
in this study, a system framework was established to identify promising enzyme candidates to synthesize desired chemicals.
this approach can also be applied to find the novel pathways for the biodegradation of chemicals.
through this work,  <dig> reaction rules representing numerous biochemical reactions were set up for qualitative analysis.
the most notable feature of the study is the development of a new quantitative analysis method, prioritization scoring algorithm.
using the novel estimation methods, new opportunities of enzymes can be predicted with greater precision.
moreover, the parameters are estimated by an evolutionary optimization method, and thus more accurate scores can be estimated as more experimentally validated data are added.
this in silico prediction system is expected to contribute significantly to in vivo or in vitro experiments.

 in the past few decades, various systematic methods have been developed for the prediction of synthetic metabolic pathways for the production of chemicals by employing microorganisms. these methods can be classified by whether the approach is based on chemical structural changes, enzymatic information, and/or reaction mechanisms. the method based on chemical structural changes is applied to reconstruct the network which represents the relationship among the biochemical compounds using the structure-based homology analysis. this method generates a variety of novel pathways, but prediction to specify the enzymes is difficult. enzymatic information-based approach focuses on combination of gene knock outs and additions of pathways existing in different organisms. this method is practical to use, but predictions are limited to the synthesis of currently known biochemical compounds. reaction mechanisms-based approach identifies product candidates that can be driven from a predetermined substrate using a knowledge-based expert system. this method predicts novel pathways and compounds according to the accumulated knowledge and rules, but it is limited to identifying biodegradation pathways. to overcome the disadvantages of the aforementioned methods, the pathway prediction systems were established by combining the given reaction mechanisms and the starting and target compounds. these approaches can generate novel compounds and reactions with proposed enzyme candidates. however, the starting and target compounds should be set as known compounds, and thus this method is difficult to be applied to the prediction of a synthetic pathway for a novel compound of interest. a retrosynthesis model, which is a functional group-based synthesis method towards a target compound, has been applied to search desired target chemicals. however, the previous studies provided a huge set of predicted pathways, rather than suggesting more favorable pathways to achieve a goal of efficiently producing a desired chemical. in this study, a system framework was developed to suggest promising enzyme candidates to synthesize desired chemicals based on combined information on chemical structural changes, enzyme characteristics, and reaction mechanisms. the proposed system framework identifies structurally qualified enzymes for the synthesis of predetermined target chemicals and then ranks the enzymes via a prioritization scoring algorithm. recently, a nice scoring technique to identify preferred pathways by using an automatic design approach for the metabolic pathways has been suggested; a scoring algorithm was developed for identifying a possible route from a considered host organism. however, this approach cannot be applied to the novel pathways which are not present in the database. thus, a new scoring algorithm was developed in this paper for the identification of desired novel synthetic pathways. consequently, the more efficient metabolic pathways for the production of a desired chemical can be proposed.  using the system framework developed in this study, the novel synthetic pathways for the production of isobutanol, 3-hydroxypropionate, and butyryl-coa were predicted. in summary, the steps composed of definition of a target compound, route generation, prioritization, and parameter optimization were taken to predict the novel synthetic pathways. the prediction shows a high reliability, in which experimentally verified pathways for the synthesis of isobutanol, 3hp, and butyryl-coa belonged to top %, %, and % of all the predicted pathway candidates, respectively. prediction of synthetic pathways of the production of biofuels and evolutionary parameter optimization recently, atsumi et al. reported novel metabolic engineering strategies for the production of higher alcohols such as 1-propanol, 1-butanol, 2-methy-1-butanol, 3-methy-1-butanol, isobutanol, and 2-phenylethanol in escherichia coli. the six pathways were devised involving two well-known enzymes, 2-keto-acid decarboxylase and alcohol dehydrogenase, which is based on the reaction mechanism that 2-keto acids can be converted to aldehydes and then to alcohol. to testify their work, the system framework was employed. the key novel synthetic pathways are presented in figure initially, for example, the structure of the target compound, isobutanol, was entered in the form of smiles. then, predefined reaction rules were applied to the target compound for generating substrates. the generated substrates were regarded as intermediate target compounds, and the reaction rules were applied again. the recursive generation step was completed when the generation loop has reached the predefined limit. throughout the loop, various routes for the production of target compound were generated. the system then detects known chemicals and displays them so as to select a starting compound. the referred reaction rules are shown in figure 2b. among the detected known chemicals, 2-ketoisovalerate was selected as the starting compound. after the starting compound was determined, the routes from the starting compound to the target compound were retrieved for further analysis. the routes for the production of the target compound are defined as the base routes. the identified base routes for the synthesis of the isobutanol are shown in the bottom of figure 2a. using the mechanisms defined in every reaction step of base routes, the biochemical reactions in the kegg database were classified into the individual groups. finally, all the routes from the starting compound to the target compound defined as the reaction route candidates were determined by combination of the reactions in each group. as shown in figure two base routes for the synthesis of isobutanol were identified and two groups, reactions in b.co. and reactions in b.c., were classified for each base route. finally, reaction route candidates were determined. next, a prioritization method was applied to decide which route candidates are preferred by estimating five priority factors: binding site covalence, chemical similarity, thermodynamic favorability, pathway distance, and organism specificity. throughout the prioritization step, reaction route candidates were rearranged into enzyme-based routes which were defined as enzyme route candidates. if multiple reactions are related to one enzyme, the values of binding site covalence and chemical similarity of the enzyme are determined by the highest values of those of the related reactions. figure shows the results of prioritization by the estimation of five factors for the synthesis of isobutanol. finally, the preference of each enzyme route candidate was determined as a score calculated by the weighted sum of each factor. in the initial predictions, the six pathways were positioned within top % of the predicted candidates. specially, isobutanol was within top % as the best result. from the initial prediction results, each three factor including thermodynamic favorability, pathway distance, and organism specificity is consistent for the six pathways. the other hand, the other factors including binding site covalence and chemical similarity are varied. it is caused that the same enzymes are applied to design the six pathways. among the results of atsumi et al., the production rate of isobutanol was at least three times higher than the production rates of other higher alcohols. also, the predicted rank for the synthetic pathway via kdc and adh for the production of isobutanol is higher than other pathways. therefore, the pathway was considered to be more suitable to produce isobutanol. for the accurate estimate of the relative influence of each factor which is expressed as a parameter, novel synthetic pathway for the production of isobutanol is selected. to identify the optimal parameters, the evolutionary parameter optimization shown as equation in methods was performed. when the parameter values of were used without optimization, the experimentally proven synthetic pathways of isobutanol was ranked at the 20th out of enzyme route candidates. after the evolutionary parameter optimization, the parameter set was changed from { 1} to {,,,, } and the rank of the synthetic pathway was improved to the 17th. the ranks of six pathways were improved within top % of the predicted candidates than the initial predictions positioned within top % as mentioned above. in addition, there were enzyme route candidates that always have higher values in the final priority scores than those of the experimentally proven pathways. it means that they have the superior values in all factors. thus, the superior enzyme route candidates might be used as superior synthetic pathways for more efficient production of the target chemical. enzyme route candidates have higher values in all factors compared to the experimentally identified pathways. prediction of synthetic pathways for the production of 3hp to examine the performance of the system framework developed in this study, the synthetic pathways for the production of 3hp were predicted as another example. 3hp is one of the top value added chemicals suggested by the u.s. department of energy. other than the suggested seven metabolic pathways for the production of 3hp from glucose, alternative pathways from acryloyl-coa were identified. the structure of 3hp and its existing and alternative synthetic pathways from acryloyl-coa are shown in figure 6a. to identify the synthetic pathways for the production of 3hp from acryloyl-coa, two base routes shown in figure 6b and reaction route candidates were generated. next, reaction route candidates were further analyzed quantitatively in order to identify more promising routes by employing a prioritization algorithm. during the prioritization, enzyme route candidates were generated and evaluated. the experimentally proven synthetic pathway from acryloyl-coa to 3hp through ec. and ec. was ranked at the second out of enzyme route candidates. since the existing pathway is superior enzyme route candidate of the experimentally proven pathway, evolutionary optimization does not change the parameter values and the rank. this result demonstrates the efficiency and reliability of the developed system framework for identifying novel synthetic pathways for the production of desired chemicals. prediction of alternative synthetic pathways for the production of 1-butanol in this paper, the alternative synthetic pathway for the production of 1-butanol from 2-ketovalerate, as atsumi et al. presented, has been identified. since the two step synthetic pathway for the production of 1-butanol from butyryl-coa already exists in kegg database, the synthetic pathways to the butyryl-coa were explored. the constructed alternative pathways with base routes are shown in figure during the route generation process, reaction route candidates and enzyme route candidates were identified. the enzyme route candidates are quantitatively analyzed by the prioritization method and the resulting top pathways are shown in table among the top pathways, the 8th ranked enzyme route candidate, a novel pathway via ec. and ec., was successfully synthesized to produce butyryl-coa from 2-ketoisovalerate. this pathway is structurally identical compared to the existing pathway; however, no organism has been found to produce the butyryl-coa via the enzymes. in other words, the pathway obtained lower score in the organism specificity. that is the reason why the pathway is ranked at the 8th. after the evolutionary optimization, the rank is slightly changed to the 7th and the parameter set is changed to {,,,, }. through this work, the novel alternative synthetic pathway for the production of 1-butanol has been identified. this study demonstrates the applicability of the developed method and system framework. xb is the binding site covalence, xc is the chemical similarity, xt is the thermodynamic favorability, xp is the pathway distance, and xo is the organism specificity. the final priority x is evaluated by equation 6a with the previously estimated parameter set {,,,, }. 6th ranked enzyme route candidate is the superior set of the experimentally proven pathway which is ranked at the 8th.  in this study, a system framework was established to identify promising enzyme candidates to synthesize desired chemicals. this approach can also be applied to find the novel pathways for the biodegradation of chemicals. through this work, reaction rules representing numerous biochemical reactions were set up for qualitative analysis. the most notable feature of the study is the development of a new quantitative analysis method, prioritization scoring algorithm. using the novel estimation methods, new opportunities of enzymes can be predicted with greater precision. moreover, the parameters are estimated by an evolutionary optimization method, and thus more accurate scores can be estimated as more experimentally validated data are added. this in silico prediction system is expected to contribute significantly to in vivo or in vitro experiments. 
as the proofs of concept, the novel synthetic pathways for the production of isobutanol, 3-hydroxypropionate, and butyryl-coa were predicted. the prediction shows a high reliability, in which experimentally verified synthetic pathways were listed within the top % of the identified pathway candidates. in these approaches, novel pathways were predicted based on chemical structure changes, enzymatic information, and/or reaction mechanisms, but the approaches generating a huge number of predicted results are difficult to be applied to real experiments. in addition, new concepts of binding site covalence, estimation of pathway distance and organism specificity were taken into account to identify the best synthetic pathway. in the present study, we propose a system framework employing a retrosynthesis model with a prioritization scoring algorithm. it is expected that the system framework developed in this study would be useful for the in silico design of novel metabolic pathways to be employed for the efficient production of chemicals, fuels and materials. there have been several methods developed for the prediction of synthetic metabolic pathways leading to the production of desired chemicals. parameters of these factors can be evolutionarily optimized when a newly proven synthetic pathway is registered. this new strategy allows deducing the novel promising pathways for the synthesis of a desired chemical together with information on enzymes involved based on structural changes and reaction mechanisms present in the system database.
 there have been several methods developed for the prediction of synthetic metabolic pathways leading to the production of desired chemicals. in these approaches, novel pathways were predicted based on chemical structure changes, enzymatic information, and/or reaction mechanisms, but the approaches generating a huge number of predicted results are difficult to be applied to real experiments. also, some of these methods focus on specific pathways, and thus are limited to expansion to the whole metabolism.  in the present study, we propose a system framework employing a retrosynthesis model with a prioritization scoring algorithm. this new strategy allows deducing the novel promising pathways for the synthesis of a desired chemical together with information on enzymes involved based on structural changes and reaction mechanisms present in the system database. the prioritization scoring algorithm employing tanimoto coefficient and group contribution method allows examination of structurally qualified pathways to recognize which pathway is more appropriate. in addition, new concepts of binding site covalence, estimation of pathway distance and organism specificity were taken into account to identify the best synthetic pathway. parameters of these factors can be evolutionarily optimized when a newly proven synthetic pathway is registered. as the proofs of concept, the novel synthetic pathways for the production of isobutanol, 3-hydroxypropionate, and butyryl-coa were predicted. the prediction shows a high reliability, in which experimentally verified synthetic pathways were listed within the top % of the identified pathway candidates.  it is expected that the system framework developed in this study would be useful for the in silico design of novel metabolic pathways to be employed for the efficient production of chemicals, fuels and materials. 